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1
Ha, Duy Hung, Dac-Binh Ha, Van-Truong Truong, Van-Duc Phan, and Q. S. Vu5. "Performance enhancement of wireless sensor network by using non-orthogonal multiple access and sensor node selection schemes." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 2 (2021): 886–94. https://doi.org/10.11591/ijeecs.v21.i2.pp886-894.
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In this paper, we investigate a relaying wireless sensor network (WSN) with the non-orthogonal multiple access (NOMA) and sensor node selection schemes over rayleigh fading. Precisely, the system consists of two sensor clusters, a sink node, and an amplify-and-forward (AF) relay. These sensors applying the NOMA and sensor node selection schemes transmit the sensing data from the sensor clusters via the relay to the sink. We derived the expressions of outage probability and throughput for two sensor nodes. We also provide numerical results to examine the behavior of the system. Finally, we verify the validity of our analysis by using the monte-carlo simulation.
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Rajkumar, Dhamodharan Udaya Suriya, Krishna Prasad Karani, Rajendran Sathiyaraj, and Pellakuri Vidyullatha. "Optimal shortest path selection using an evolutionary algorithm in wireless sensor networks." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 6 (2024): 6743. http://dx.doi.org/10.11591/ijece.v14i6.pp6743-6752.
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A wireless sensor network comprises of distributed independent devices, called sensors that monitor the physical conditions of the environment for various applications, such as tracking and observing environmental changes. Sensors have the ability to detect information, process it, and forward it to neighboring sensor nodes. Wireless sensor networks are facing many issues in terms of scalability, which necessitates numerous nodes and network range. The route chosen between the source node and the destination node with the shortest distance determines how well the network performs. In this paper, evolutionary algorithm based shortest path selection provides high end accessibility of path nodes for data transmission among source and destination. It employs the best fitness function methodology, which involves the replication of input, mutation, crossover, and mutation methods, to produce efficient outcomes that align with the best fitness function, thereby determining the shortest path. This is a probabilistic technique that receives input from learning models and provides the best results. The execution results are presented well compared with earlier methodologies in terms of path cost, function values, throughput, packet delivery ratio, and computation time.
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Cao, Li, Yinggao Yue, and Yong Zhang. "A Data Collection Strategy for Heterogeneous Wireless Sensor Networks Based on Energy Efficiency and Collaborative Optimization." Computational Intelligence and Neuroscience 2021 (September 29, 2021): 1–13. http://dx.doi.org/10.1155/2021/9808449.
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In the clustering routing protocol, prolonging the lifetime of the sensor network depends to a large extent on the rationality of the cluster head node selection. The selection of cluster heads for heterogeneous wireless sensor networks (HWSNs) does not consider the remaining energy of the current nodes and the distribution of nodes, which leads to an imbalance of network energy consumption. A strategy for selecting cluster heads of HWSNs based on the improved sparrow search algorithm- (ISSA-) optimized self-organizing maps (SOM) is proposed. In the stage of cluster head selection, the proposed algorithm establishes a competitive neural network model at the base station and takes the nodes of the competing cluster heads as the input vector. Each input vector includes three elements: the remaining energy of the node, the distance from the node to the base station, and the number of neighbor nodes of the node. The best cluster head is selected through the adaptive learning of the improved competitive neural network. When selecting the cluster head node, comprehensively consider the remaining energy, the distance, and the number of times the node becomes a cluster head and optimize the cluster head node selection strategy to extend the network life cycle. Simulation experiments show that the new algorithm can reduce the energy consumption of the network more effectively than the basic competitive neural network and other algorithms, balance the energy consumption of the network, and further prolong the lifetime of the sensor network.
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Nisha, M., and S. Poongavanam. "Best Communication Node Election for well-organized Path in Flat Topology." Indonesian Journal of Electrical Engineering and Computer Science 8, no. 2 (2017): 555. http://dx.doi.org/10.11591/ijeecs.v8.i2.pp555-556.
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<p>There has been an increasing attentiveness in the uses of sensor networks. Because sensors are normally controlled in on-board power supply, proficient supervision of the network is essential in improving the life of the sensor.<strong> </strong>The majority research protocols objective at offering link breakage reducing and mitigating from the same. Yet, selecting the well-organized communication do all the beneficial to the transmission process thus demonstrating better improvement in the network performance. In this article, we propose Best Communication Node Election for well-organized Path in Flat Topology The main goal of this<strong> </strong>work is to choose the best data transmission node in flat topology for improve the multi hop routing. This scheme, the best communication node selection based on Path Metric and this Path Metric is measured by the packet obtained rate, dropped rate, latency rate and node energy. This scheme provide guarantees quality of Service in the network.</p>
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Atul Pawar. "Energy-Efficient Cluster Formation in Wireless Sensor Networks." Journal of Information Systems Engineering and Management 10, no. 14s (2025): 595–603. https://doi.org/10.52783/jisem.v10i14s.2330.
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Sensor nodes that are wireless are extremely energy-constrained devices. Due to a number of sensor node limitations, including size and cost, their battery life is limited. Furthermore, the majority of Wireless Sensor Network (WSN) applications make it impossible to recharge or swap out sensor node batteries. Thus, one of the main challenges in wireless sensor networks is making the best use of node energy. An efficient way to maximize node energy utilization and extend the lifespan of an energy-constrained wireless sensor network is to cluster sensor nodes. In order to extend the lifespan of sensor networks, we present a location-based protocol for WSNs in this paper that supports energy-efficient clustering, cluster head selection/rotation, and data routing. With the fewest transmit-receive operations, the suggested clustering technique guarantees balanced size cluster formation within the sensing field. Even though the cluster head and sensor nodes in a cluster have different energy needs, the cluster head rotation protocol guarantees balanced node energy dissipation. In order to establish balanced energy consumption across the cluster's nodes and so extend the network's lifespan, the cluster head rotation protocol has been devised. Simulation findings show that by using effective clustering, cluster head selection/rotation, and data routing, the suggested protocol extends network lifetime.
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Spoorthi, K., Saha Snehanshu, and Mathur Archana. "Discrete Path Selection and Entropy Based Sensor Node Failure Detection in Wireless Sensor Networks." Cybernetics and Information Technologies 16, no. 3 (2016): 137–53. http://dx.doi.org/10.1515/cait-2016-0039.
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Abstract Exertion of wireless sensor networks has been increasing in recent years, and it imprints in almost all the technologies such as machine industry, medical, military and civil applications. Due to rapid growth in electronic fabrication technology, low cost, efficient, multifunctional and accurate sensors can be produced and thus engineers tend to incorporate many sensors in the area of deployment. As the number of sensors in the field increases, the probability of failure committed by these sensors also increases. Hence, efficient algorithms to detect and recover the failure of sensors are paramount. The current work concentrates mainly on mechanisms to detect sensor node failures on the basis of the delay incurred in propagation and also the energy associated with sensors in the field of deployment. The simulation shows that the algorithm plays in the best possible way to detect the failure in sensors. Finally, the Boolean sensing model is considered to calculate the network coverage of the wireless sensor network for various numbers of nodes in the network.
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Santos-Ruiz, Ildeberto, Francisco-Ronay López-Estrada, Vicenç Puig, Guillermo Valencia-Palomo, and Héctor-Ricardo Hernández. "Pressure Sensor Placement for Leak Localization in Water Distribution Networks Using Information Theory." Sensors 22, no. 2 (2022): 443. http://dx.doi.org/10.3390/s22020443.
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This paper presents a method for optimal pressure sensor placement in water distribution networks using information theory. The criterion for selecting the network nodes where to place the pressure sensors was that they provide the most useful information for locating leaks in the network. Considering that the node pressures measured by the sensors can be correlated (mutual information), a subset of sensor nodes in the network was chosen. The relevance of information was maximized, and information redundancy was minimized simultaneously. The selection of the nodes where to place the sensors was performed on datasets of pressure changes caused by multiple leak scenarios, which were synthetically generated by simulation using the EPANET software application. In order to select the optimal subset of nodes, the candidate nodes were ranked using a heuristic algorithm with quadratic computational cost, which made it time-efficient compared to other sensor placement algorithms. The sensor placement algorithm was implemented in MATLAB and tested on the Hanoi network. It was verified by exhaustive analysis that the selected nodes were the best combination to place the sensors and detect leaks.
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S, Kavya, and Praveen Kumar R. "Forward Node Selection by Evaluating Link Quality Using Fuzzy Logic in WBAN." International Journal of Electrical and Electronics Research 12, no. 2 (2024): 512–19. http://dx.doi.org/10.37391/ijeer.120224.
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WBAN technology plays a vital role in human life monitoring and maintaining health remotely without being hospitalized, particularly during pandemic situations. The miniature-sized and heterogeneous sensors involved in WBAN with limited resources face reliability as a key challenge that limits the growth of WBAN technology. Designing an efficient routing protocol helps to achieve reliable data transmission between sensor nodes in WBAN. The proposed Fuzzy logic-based Forward Node Selection chooses the best node to transmit the data by introducing fuzzy logic on routing parameters such as link quality, data rate, node’s residual energy and node-to-node distance. The key advantages of our proposed system are to extend the network lifetime and boost the packet delivery ratio. The efficiency of our proposed method is estimated by comparing the parameters of network lifetime and packet delivery ratio with DTS and EARP protocols.
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Susila, S. G., and J. Arputhavijayaselvi. "Multipart Layer Node Deployment and Computational Technique with Finest Cluster Head Selection for Network Lifetime Enhancement." Journal of Computational and Theoretical Nanoscience 13, no. 10 (2016): 6642–48. http://dx.doi.org/10.1166/jctn.2016.5609.
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The continual research and development in wireless sensor networks, power is most vital resource because each sensor node has limited battery power. Numerous clustering concept routing protocols have been developed to balance and enhance lifetime of the sensor nodes in wireless sensor networks. Available clustering routing protocols are select cluster heads periodically and they considered only how can select cluster heads energy-efficiently and the most excellent selection of cluster heads, without considering energy-efficient period of the cluster heads replacement. Herein paper, it is employed different formulae in homogeneous merged layer node deployment system, which has a threshold-based cluster head selection mechanism for clustering routing protocols of wireless sensor networks. The proposed routing protocol is minimizes the number of cluster head selection difficulty by using threshold of residual energy comparison. Reducing the amount of difficulty for cluster head selection procedure yields better life span of the whole sensor networks and it is compared with the available clustering routing protocols. In the proposed system of work, node scheduling or activation techniques are also integrated and the obtained simulation results illustrate that the best to the obtainable clustering protocols in wireless sensor networks (WSNs).
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Rao, Varun, Sandeep Nukala, Abirami G, Deepa R, and Revathi Venkataraman. "Huffman coding packet balancer based data compression techniques in Wireless Sensor Network." International Journal of Engineering & Technology 7, no. 2.24 (2018): 531. http://dx.doi.org/10.14419/ijet.v7i2.24.12152.
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In Wireless Sensor Networks, sensor devices perform sensing and communicating task over a network for data delivery from source to destination. Due to the heavy loaded information, during packet transmission, sensor node will drain off its energy frequently, thus led to packet loss. The novelty of the proposed work is mainly reducing the loss of packet and energy consumption during transmission. Thus, Huffman coding packet balancer select the best path between the intermediate nodes and are compared based on transmitting power, receiving and sensing power these measure the QOS in wireless sensor network. To satisfy the QOS of the node, compressed packet from source to destination is done by choosing the best intermediate node path. The advantages of the proposed work is minimum packet loss and minimize the end to end delay. Sparse recovery is used to reconstruct the path selection when there is high density of node.
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Narmeen, Ramsha, and Jaehak Chung. "Relay Selection for Capacity Increase in Underwater Acoustic Sensor Network." Sensors 21, no. 19 (2021): 6605. http://dx.doi.org/10.3390/s21196605.
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In long distance sensor nodes, propagation delay is the most crucial factor for the successful transmission of data packets in underwater acoustic sensors networks (UWAs). Therefore, to cope with the problem of propagation delay, we propose examining and selecting the best relay node (EBRN) technique based on checking the eligibility and compatibility of RN and selecting the best RN for UWAs. In the EBRN technique, the source node (S) creates a list of the best RNs, based on the minimum propagation delay to the midpoint of a direct link between S and the destination node (D). After that, the S attaches the list of selected RNs and transmit to the D along with data packets. Finally, from the list of selected RNs, the process of retransmission is performed. To avoid collision among control packets, we use a backoff timer that is calculated from the received signal strength indicator (RSSI), propagation delay and transmission time, whereas the collision among data packets is avoided by involving single RN in a particular time. The performance of the proposed EBRN technique is analyzed and evaluated based on throughput, packet loss rate (LR), packet delivery ratio (PDR), energy efficiency, and latency. The simulation results validate the effectiveness of the proposed EBRN technique. Compared with the existing schemes such as underwater cooperative medium access control (UCMAC) and shortest path first (SPF), the proposed EBRN technique performs remarkably well by increasing the throughput, PDR, and energy efficiency while decreasing the latency and LR in UWAs.
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Loganathan, Sathyapriya, and Jawahar Arumugam. "Clustering Algorithms for Wireless Sensor Networks Survey." Sensor Letters 18, no. 2 (2020): 143–49. http://dx.doi.org/10.1166/sl.2020.4193.
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This paper aims to discuss a comprehensive survey on clustering algorithms for wireless sensor networks (WSN). The several real-time applications adopted the WSN with the advance features. But the capacity and size of the battery used in the sensor nodes are limited. Battery replacement or recharging is very difficult in most outdoor applications. Hence handling this kind of network is one of the issues. One of the best solutions to the energy issue is Clustering. Clustering is to balance the energy consumption of the whole network by cluster-based architecture to prolong the network lifetime. Sensor nodes grouped into clusters; one sensor node selects as the cluster head for each cluster. The cluster head sensor node collects the data from their sensor member nodes and forwards them to the sink node. In cluster-based architecture, cluster formation and the selection of the cluster head node decides the network lifetime. The paper discusses the for and against various clustering algorithms. It suggests the vital parameters for developing energy-efficient clustering algorithms and steps to overcome the limitations.
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Liu, Jianhua, Guangxue Yue, Shigen Shen, Huiliang Shang, and Hongjie Li. "A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks." Scientific World Journal 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/950618.
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The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security.
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Du, Yong-wen, Zhang-min Wang, Gang Cai, and Jun-hui Gong. "Load-balanced routing algorithm based on cluster heads optimization for wireless sensor networks." MATEC Web of Conferences 232 (2018): 04050. http://dx.doi.org/10.1051/matecconf/201823204050.
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In order to solve the problem of unbalanced load consumption of nodes for wireless sensor networks (WSNs), this paper proposes a load-balanced routing algorithm based on cluster heads optimization for wireless sensor network. The proposed algorithm first applies first-order wireless transmission model to calculate the optimal number of clusters, then calculate nodes competitiveness rating by fuzzy algorithm considering the residual energy of node and distance from the node to base station, cluster head selection uses unequal clustering algorithm according to the competitiveness of nodes. By node competitiveness and energy management mechanism which cooperate with each other to select the best cluster heads. Use connected optimization between clusters to search multi-hop paths base station for reducing energy consumption of node, and consider transmission energy consumption, residual energy, transmission distance and other factors. The experimental results show that the proposed algorithm compared with LEACH and UCDP algorithm, can balance loading and effectively extend the life cycle of wireless sensor network.
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Ramalingam, Rajakumar, Dinesh Karunanidy, Aravind Balakrishnan, et al. "OGWO-CH: Hybrid Opposition-Based Learning with Gray Wolf Optimization Based Clustering Technique in Wireless Sensor Networks." Electronics 11, no. 16 (2022): 2593. http://dx.doi.org/10.3390/electronics11162593.
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A Wireless Sensor Network (WSN) is a group of autonomous sensors that are distributed geographically. However, sensor nodes in WSNs are battery-powered, and the energy drainage is a significant issue. The clustering approach holds an imperative part in boosting the lifespan of WSNs. This approach gathers the sensors into clusters and selects the cluster heads (CHs). CHs accumulate the information from the cluster members and transfer the data to the base station (BS). Yet, the most challenging task is to select the optimal CHs and thereby to enhance the network lifetime. This article introduces an optimal cluster head selection framework using hybrid opposition-based learning with the gray wolf optimization algorithm. The hybrid technique dynamically trades off between the exploitation and exploration search strategies in selecting the best CHs. In addition, the four different metrics such as energy consumption, minimal distance, node centrality and node degree are utilized. This proposed selection mechanism enhances the network efficiency by selecting the optimal CHs. In addition, the proposed algorithm is experimented on MATLAB (2018a) and validated by different performance metrics such as energy, alive nodes, BS position, and packet delivery ratio. The obtained results of the proposed algorithm exhibit better outcome in terms of more alive nodes per round, maximum number of packets delivery to the BS, improved residual energy and enhanced lifetime. At last, the proposed algorithm has achieved a better lifetime of ≈20%, ≈30% and ≈45% compared to grey wolf optimization (GWO), Artificial bee colony (ABC) and Low-energy adaptive clustering hierarchy (LEACH) techniques.
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Vijay, Shams Tabrez Siddiqui, Ritu, et al. "Intertwine Connection-Based Routing Path Selection for Data Transmission in Mobile Cellular Networks and Wireless Sensor Networks." Wireless Communications and Mobile Computing 2022 (August 4, 2022): 1–9. http://dx.doi.org/10.1155/2022/8398128.
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In a network setting, a sensor node's round-trip delay time over hostile nodes compromises the node's ability to transmit data from the sender node to the destination node. Minimum distance path discovery causes the path failure, since aggressive nodes are available. Node connectivity is poor which should cause the packet loss; it does not control more energy consumption, since packet broadcasting is repeated for many times using that path. So, the proposed intertwine connection-based routing path selection (ICBRPS) technique allows only energy efficient routing path, path connectivity is important, and routing path is damaged because of the presence of aggressive nodes. It hacks the information from sensor and operates unpredictable manner. The objective of this presented ICBRPS scheme is to improve the routing path in efficient manner. If any damages occur during the transmission of data, then the alternate best node connectivity path is created by energetic route discovery method. The performance metrics of parameters are delay, network overhead, energy consumption, packet loss, packet delivery ratio, and connectivity ratio. It enhances the connectivity rate and reduces the energy consumption.
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Dr. Mukesh Kalla, Asha Rawat,. "Clustering Algorithm for Energy- Efficient Wireless Sensor Network." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (2021): 877–84. http://dx.doi.org/10.17762/turcomat.v12i5.1500.
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Wireless networks data aggregation allows in-network processing, reduces packet transmission and data redundancy, and thus helps extend wireless sensor systems to the full duration of their lives. There have been many ways of dividing the network into clusters, collecting information from nodes and adding it to the base station, to extend wireless sensor network life. Certain cluster algorithms consider the residual energy of the nodes when selecting clusterheads and others regularly rotate the selection head of the cluster. However, we seldom investigate the network density or local distance. In this report we present an energy-efficient clustering algorithm that selects the best cluster heads of the system after dividing the network into clusters. The cluster head selection depends on the distance between the base station nodes and the remaining power of this approach.Each node's residual energy is compared to the node count. Our results show that the solution proposed more efficiently extends the life of the wireless sensor network. The algorithm prolongs the life and effectiveness of the Wireless Sensor Network.
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Chen, Zhengchuan, Mingjun Xu, Min Wang, and Yunjian Jia. "Joint Optimization of Data Freshness and Fidelity for Selection Combining-Based Transmissions." Entropy 24, no. 2 (2022): 200. http://dx.doi.org/10.3390/e24020200.
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Motivated by big data applications in the Internet of Things (IoT), abundant information arrives at the fusion center (FC) waiting to be processed. It is of great significance to ensure data freshness and fidelity simultaneously. We consider a wireless sensor network (WSN) where several sensor nodes observe one metric and then transmit the observations to the FC using a selection combining (SC) scheme. We adopt the age of information (AoI) and minimum mean square error (MMSE) metrics to measure the data freshness and fidelity, respectively. Explicit expressions of average AoI and MMSE are derived. After that, we jointly optimize the two metrics by adjusting the number of sensor nodes. A closed-form sub-optimal number of sensor nodes is proposed to achieve the best freshness and fidelity tradeoff with negligible errors. Numerical results show that using the proposed node number designs can effectively improve the freshness and fidelity of the transmitted data.
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Ullah, Ubaid, Anwar Khan, Mahdi Zareei, Ihsan Ali, Hasan Ali Khattak, and Ikram Ud Din. "Energy-Effective Cooperative and Reliable Delivery Routing Protocols for Underwater Wireless Sensor Networks." Energies 12, no. 13 (2019): 2630. http://dx.doi.org/10.3390/en12132630.
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Underwater deployed sensors nodes are energy-constrained. Therefore, energy efficiency becomes crucial in underwater wireless sensor networks (U-WSNs). The adverse channel corrupts the packets and challenges their reliability. To handle these challenges, two routing schemes are introduced in this paper. They are effective energy and reliable delivery (EERD) and cooperative effective energy and reliable delivery (CoEERD). In EERD, the packets follow single-path routing and the best forwarder node is selected using a weight function such that packets are transferred via the reliable paths with low energy usage. Packet transfer via a single route in EERD has, however, compromised reliability as the undersea links bear harshness and unpredictability. Therefore, the CoEERD scheme adds cooperative routing to EERD, in which a relay node is introduced between a source–destination pair. The destination requests the relay when the packets it gets from the source are corrupted beyond a threshold value. Selection of weight function is unique and considers many factors to ensure low energy usage with reliability while considering nodes for data transfer. This also helps in selecting a single relay node rather than many relays in the conventional cooperative routing model. Based on simulation results, the EERD and CoEERD protocols have improved performance in energy usage, reliable packet transfer and delay.
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R.Gayathri*1, S.Kiruthika2 &. P.Keerthana3. "T-TRACKING ALGORITHM FOR DATA TRACKING IN WIRELESS SENSOR NETWORKS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 7, no. 4 (2018): 517–23. https://doi.org/10.5281/zenodo.1219647.
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In Wireless Sensor Network the sensor nodes are being dispersed spatially, so the target tracking has become a key factor. In the existing system they have used the Face Tracking for tracking the target. They have developed non-overlapping region called Face. In that they have used Brink Detection algorithm for selecting the edges and Optimal Selection algorithm for selecting sensor node in each face. However, if the selected node fails then tracking accuracy will be lost. In this paper we have a new tracking scheme, called t-Tracking is designed to overcome the target tracking problem in WSNs considering multiple objectives: low capturing time, high quality of tracking (QoT). A set of fully distributed tracking algorithms is proposed, which answers the query whether a target remains in a “specific area” (called a “face”). When a target moves from one face to another face all the possible movements will be mentioned. Then query will be sent to all those nodes about their energy and coverage area. Based on the response from those nodes the best nodes will be selected for continuing tracking when the target moves to the next face. The result of this t-Tracking is compared with already existing face tracking..
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Liu, Yi. "An integrated simulation system using fuzzy logic and network simulator 3 (ns-3) for actor node selection in wireless sensor and actor networks (WSANs): Performance evaluation considering different parameters." Journal of High Speed Networks 31, no. 1 (2025): 90–101. https://doi.org/10.1177/09266801241297291.
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The wireless sensor and actor networks (WSANs) are considered a fundamental technology for the Internet of Things (IoT). These networks comprise numerous sensor and actor nodes and are anticipated to be utilized in various sectors. In WSANs, actor nodes must be positioned and moved optimally to ensure an efficient communication network among the actor nodes, as well as connecting actor nodes with sensor and other actor nodes. This research focuses on the selection process of actor nodes within WSANs. The proposed system selects the optimal actor node by employing fuzzy logic (FL) and the network simulator 3 (ns-3). We investigate the performance of the proposed FL-based system by taking into account three parameters: distance to event from actor (DEA), number of sensors per actor (NSA), and task accomplishment time (TAT). The output parameter is the actor selection decision (ASD). We carried out qualitative evaluation by FL-based system. The simulation results revealed that ASD decreases as TAT, NSA, and DEA increase. We carried out a quantitative evaluation by using the ns-3 simulator. The performance evaluation demonstrated that packet loss increases by increasing NSA. Also, as TAT increases, both packet loss and delay time increase. Among the three actor nodes, Actor2 exhibited the best performance.
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Sujithra, T., and S. Anbarasu. "Balanced Energy Efficient Spanning Tree Approaches for Wireless Sensor Network with Sleep Scheduling Algorithm." Asian Journal of Computer Science and Technology 1, no. 1 (2012): 102–6. http://dx.doi.org/10.51983/ajcst-2012.1.1.1663.
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We Propose Balanced, Localized, Robust, Dynamic state changing and energy efficient spanning tree approaches for Wireless sensor networks which we call Balanced energy Efficient Spanning Tree with Sleep scheduling(BEESP-SS). They are based on the topologies. It is constructed using RNG. Localized Minimum Spanning tree is constructed based on these topologies(LMST).The actual routing tree is constructed based on the transmitter and receiver residual energy. We also consider different parent selection strategies while constructing routing tree and select the best among them. Our solution also involves the load balancing by measuring the energy level of the nodes in the spanning tree, because energy is drain out when large number of messages travelling through the particular node by limiting the messages travelled through the sensor nodes we can improve the lifetime of the spanning tree, it is done by partitioning the messages based on the energy level of the node in the spanning tree and redirect the messages to the some other nodes in the spanning tree. The proposed solution also adapted the Sleep Scheduling Algorithm, it wake up the sensor nodes in the network when it is needed. This paper also handles the route maintenance it includes node insertion and node deletion.
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Malik, Monika, Alok Joshi, and Gayatri Sakya. "Application of nature inspired optimization algorithm on hierarchal LEACH protocol for improved performance." Journal of Information and Optimization Sciences 44, no. 6 (2023): 1229–40. http://dx.doi.org/10.47974/jios-1460.
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In today’s scenario Wireless Sensor Network is playing a dynamic role with the advancement in IOT for mission critical applications due to the fact that these applications are either event driven or time driven applications. Sensor network comprises of battery operated tiny sensors for sensing any change in the environment since the battery life is limited so is the sensor life. One solution to overcome this problem is the use of clustering protocol. A lot of optimization techniques are employed for performance improvement of the hierarchal LEACH routing protocol. This paper explores the three types of Foraging behavior for cluster head selection which means the process to search for food or the energy of the node so that it can be elected as CH. A fitness function is defined relating to residual energy, CH distance to Base station, position of base station. Theses algorithm progresses on the basis of the energy of sensor node in the deployed network. Here the higher energy of node is analogous to food for which the search goes on; in doing so the best CH is selected. The algorithm uses the best location of the node. The overall performance of the network is improved in terms of Energy consumption; packet delivery ratio metrics the results are compared with the existing LEACH protocol.
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Kaddi, Mohammed, Ramadhan Masmoudi, and Mohammed Omari. "Energy-efficient routing protocol for WSN based on relay node selection and A-star algorithm." STUDIES IN ENGINEERING AND EXACT SCIENCES 5, no. 2 (2024): e7200. http://dx.doi.org/10.54021/seesv5n2-140.
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Due to miniaturization constraints and manufacturing costs, wireless sensor networks (WSN) sensor nodes are generally outfitted with restricted resources concerning computing capability, energy, data storage capacity, and data delivery rate. These constraints encourage a significant portion of the research issues in WSNs, particularly the energy constraint, which is a fundamental issue. This paper suggests an innovative routing protocol that optimizes energy use called RNS_A-star, which combines a routing algorithm using a relay node and an improved heuristic for the A-star algorithm. The RNS_A-star protocol first applies a data routing algorithm using a relay node, which allows either using a relay node or simply sending the intra-cluster data to the CH. Then, the A-star algorithm is used to construct a multi-hop routing route between the CHs and the base station (BS) in order to find the best path for reducing energy consumption during data transmission. Simulation results show that the suggested RNS_A-star protocol performs better than ECO-BAT, LEACH-IACA, and LEACH protocols regarding energy conservation and extending network lifetime.
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Rajalakshmi, M. C., and A. P. Gnana Prakash. "MeMLO: Mobility-Enabled Multi-Level Optimization Sensor Network." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (2017): 374. http://dx.doi.org/10.11591/ijece.v7i1.pp374-382.
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The paper presents a technique called as Mobility-enabled Multi Level Optimization (MeMLO) that addressing the existing problem of clustering in wireless sensor net-work (WSN). The technique enables selection of aggregator node based on multiple optimi-zation attribute which gives better decision capability to the clustering mechanism by choosing the best aggregator node. The outcome of the study shows MeMLO is highly capable of minimizing the halt time of mobile node that significantly lowers the transmit power of aggregator node. The simulation outcome shows negligible computational com-plexity, faster response time, and highly energy efficient for large scale WSN for longer simulation rounds as compared to conventional LEACH algorithm.
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M.C., Rajalakshmi, and Gnana Prakash A.P. "MeMLO: Mobility-Enabled Multi-Level Optimization Sensor Network." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 1 (2017): 374–82. https://doi.org/10.11591/ijece.v7i1.pp374-382.
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The paper presents a technique called as Mobility-enabled Multi Level Optimization (MeMLO) that addressing the existing problem of clustering in wireless sensor net-work (WSN). The technique enables selection of aggregator node based on multiple optimi-zation attribute which gives better decision capability to the clustering mechanism by choosing the best aggregator node. The outcome of the study shows MeMLO is highly capable of minimizing the halt time of mobile node that significantly lowers the transmit power of aggregator node. The simulation outcome shows negligible computational com-plexity, faster response time, and highly energy efficient for large scale WSN for longer simulation rounds as compared to conventional LEACH algorithm.
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Wang, Xun, Huarui Wu, Yisheng Miao, and Huaji Zhu. "A Hybrid Routing Protocol Based on Naïve Bayes and Improved Particle Swarm Optimization Algorithms." Electronics 11, no. 6 (2022): 869. http://dx.doi.org/10.3390/electronics11060869.
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Clustering of sensor nodes is a prominent method applied to wireless sensor networks (WSNs). In a cluster-based WSN scenario, the sensor nodes are assembled to generate clusters. The sensor nodes also have limited battery power. Therefore, energy efficiency in WSNs is crucial. The load on the sensor node and its distance from the base station (BS) are the significant factors of energy consumption. Therefore, load balancing according to the transmission distance is necessary for WSNs. In this paper, we propose a hybrid routing algorithm based on Naïve Bayes and improved particle swarm optimization algorithms (HRA-NP). The cluster heads (CHs) are selected according to the CH conditional probability, which is estimated by the Naïve Bayes classifier. After the selection of the CHs, the multi-hop routing algorithm is applied to the CHs. The best routing path from each CH to the BS is obtained from an improved particle swarm optimization (PSO) algorithm. Simulations were conducted on evaluation factors such as energy consumption, active sensor nodes per round, the sustainability of the network, and the standard deviation of a load on the sensor node. It was observed that HRA-NP outperforms comparable algorithms, namely DUCF, ECRRS, and FC-RBAT, based on the evaluation factors.
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Pise, Anil Audumbar, Byungun Yoon, Saurabh Singh, and Jude Imuede. "Dodecagonal Parameter-Based Energy-Efficient Routing in Wireless Sensor Networks." Journal of High-Frequency Communication Technologies 2, no. 03 (2024): 186–200. http://dx.doi.org/10.58399/nvdh415.
Full textAbstract:
Wireless Sensor Networks (WSNs) are composed of several sensor nodes (SN) that are dispersed geographically and interact with one another over wireless media in order to track and log physical data from their environment. At the moment, WSNs frequently use routing and clustering strategies to extend the life of their networks. This paper proposes a DODECAGONAL parameter-based Energy-Efficient Routing in WSN (DOPE-WSN) for improvement of network lifetime and saving the energy consumption. Initially the cluster is selected using Agglomerative clustering. In the second phase, Pelican optimization (PELO) based Cluster head selection (CHs) meant for considering Congestion, Node Degree, Node Density, Network area, Network Coverage, Number of clusters, Number of nodes, Communication cost, Distance, Residual Energy, Distance to neighbor, Node Centrality. Moreover, the Sooty Tern Optimization (STO) model are utilized for the determination of the best routing path for the cluster heads. Taking into account node degree, residual energy, and distance, the STO maximizes network performance. The suggested approach has undergone thorough testing for ensuring network durability and energy efficiency. The proposed model achieved a maximum 97% Packet Delivery Ratio (PDR) with 900 nodes in comparison with 91%, 89%, 83%, and 82% for CRPSH, HQCA, EACRLEACH, and BWO-IACO algorithms respectively.
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Pise, Anil Audumbar, Byungun Yoon, Saurabh Singh, and Jude Imuede. "Dodecagonal Parameter-Based Energy-Efficient Routing in Wireless Sensor Networks." Journal of High-Frequency Communication Technologies 2, no. 03 (2024): 186–200. http://dx.doi.org/10.58399/nvdh4158.
Full textAbstract:
Wireless Sensor Networks (WSNs) are composed of several sensor nodes (SN) that are dispersed geographically and interact with one another over wireless media in order to track and log physical data from their environment. At the moment, WSNs frequently use routing and clustering strategies to extend the life of their networks. This paper proposes a DODECAGONAL parameter-based Energy-Efficient Routing in WSN (DOPE-WSN) for improvement of network lifetime and saving the energy consumption. Initially the cluster is selected using Agglomerative clustering. In the second phase, Pelican optimization (PELO) based Cluster head selection (CHs) meant for considering Congestion, Node Degree, Node Density, Network area, Network Coverage, Number of clusters, Number of nodes, Communication cost, Distance, Residual Energy, Distance to neighbor, Node Centrality. Moreover, the Sooty Tern Optimization (STO) model are utilized for the determination of the best routing path for the cluster heads. Taking into account node degree, residual energy, and distance, the STO maximizes network performance. The suggested approach has undergone thorough testing for ensuring network durability and energy efficiency. The proposed model achieved a maximum 97% Packet Delivery Ratio (PDR) with 900 nodes in comparison with 91%, 89%, 83%, and 82% for CRPSH, HQCA, EACRLEACH, and BWO-IACO algorithms respectively.
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Dattatraya, Patil Yogita, Jayashree Agarkhed, and Siddarama Patil. "Multi Duty Cycle Scheduled Routing in Wireless Sensor Network-lifetime Maximization." International Journal of Computer Network and Information Security 13, no. 5 (2021): 55–67. http://dx.doi.org/10.5815/ijcnis.2021.05.05.
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Cluster-based protocols are best for applications that require reliability and a continuous functioning environment with a sustainable lifetime of WSN. The dynamic nature of the sensor node makes energy conservation a challenging issue. Sensor node scheduled based on sensing error for energy conservation compromise the accuracy of prediction. The high data accuracy achieved using a single duty cycle controller at each node with compromised throughput and increased routing overhead. Duty Cycle Controller managing a more number of control messages at the network level leads to control packet interference with data packet transmission, increasing packet drop and minimizing throughput. Also, the single-duty cycle controller at the network level leads to increased control overhead. The proposed multilevel cluster-based approach focuses on the appropriate cluster design, selection of cluster head, and sensor nodes scheduling based on sensing error. The proposed method applies a multi-duty cycle controller at each cluster level, and control messages handled are related to nodes in a cluster. Thus has less interference and packet drop leading to maximum throughput than existing methods. The simulation results demonstrated that the proposed method with sensor nodes scheduled at individual cluster levels using a multi-duty cycle controller exhibited improved network lifetime, throughput, and reduced energy consumption compared with the state-of-the-art techniques.
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Nguyen, Nhan Duc, Duong Trong Bui, Phuc Huu Truong, and Gu-Min Jeong. "Position-Based Feature Selection for Body Sensors regarding Daily Living Activity Recognition." Journal of Sensors 2018 (September 13, 2018): 1–13. http://dx.doi.org/10.1155/2018/9762098.
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This paper proposes a novel approach to recognize activities based on sensor-placement feature selection. The method is designed to address a problem of multisensor fusion information of wearable sensors which are located in different positions of a human body. Precisely, the approach can extract the best feature set that characterizes each activity regarding a body-sensor location to recognize daily living activities. We firstly preprocess the raw data by utilizing a low-pass filter. After extracting various features, feature selection algorithms are applied separately on feature sets of each sensor to obtain the best feature set for each body position. Then, we investigate the correlation of the features in each set to optimize the feature set. Finally, a classifier is applied to an optimized feature set, which contains features from four body positions to classify thirteen activities. In experimental results, we obtain an overall accuracy of 99.13% by applying the proposed method to the benchmark dataset. The results show that we can reduce the computation time for the feature selection step and achieve a high accuracy rate by performing feature selection for the placement of each sensor. In addition, our proposed method can be used for a multiple-sensor configuration to classify activities of daily living. The method is also expected to deploy to an activity classification system-based big data platform since each sensor node only sends essential information characterizing itself to a cloud server.
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S.Sankar and P.Srinivasan. "Fuzzy Sets Based Cluster Routing Protocol For Internet of Things." International Journal of Fuzzy System Applications 8, no. 3 (2019): 70–93. http://dx.doi.org/10.4018/ijfsa.2019070103.
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Increasing the lifetime of low power and lossy networks (LLN) is a major challenge, as the nodes have low power, low memory, and low processing capacity. Clustering is a technique used to minimize the energy consumption of sensor nodes. This article proposes a fuzzy sets-based cluster routing protocol (FC-RPL) to extend the network lifetime in LLN. It has three processes: cluster formation, cluster head selection, and cluster head parent selection. It forms the clusters based on the Euclidean distance. It applies the fuzzy set over the metrics residual energy, number of neighbors and centrality, to select the cluster head in each cluster. The cluster head node chooses the best parent node in the DODAG for data transfer. The simulation is performed using COOJA simulator. The simulation result shows that FC-RPL extends the network lifetime by 15-25% and increases the packet delivery ratio by 2-6%.
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Samara, Ghassan, Mohammad Hassan, and Yahya Zayed. "An Intelligent Vice Cluster Head Election Protocol in WSN." International Journal of Advances in Soft Computing and its Applications 13, no. 3 (2021): 202–22. http://dx.doi.org/10.15849/ijasca.211128.14.
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Wireless sensor networks (WSNs) has a practical ability to link a set of sensors to build a wireless network that can be accessed remotely; this technology has become increasingly popular in recent years. Wi-Fi-enabled sensor networks (WSNs) are used to gather information from the environment in which the network operates. Many obstacles prevent wireless sensor networks from being used in a wide range of fields. This includes maintaining network stability and extending network life. In a wireless network, sensors are the most essential component. Sensors are powered by a battery that has a finite amount of power. The battery is prone to power loss, and the sensor is therefore rendered inoperative as a result. In addition, the growing number of sensor nodes off-site affects the network's stability. The transmission and reception of information between the sensors and the base consumes the most energy in the sensor. An Intelligent Vice Cluster Head Selection Protocol is proposed in this study (IVC LEACH). In order to achieve the best performance with the least amount of energy consumption, the proposed hierarchical protocol relies on a fuzzy logic algorithm using four parameters to calculate the value of each node in the network and divides them into three hierarchical levels based on their value. This improves network efficiency and reliability while extending network life by 50 percent more than the original Low Energy Adaptive Clustering Hierarchy protocol. Keywords: Wireless Sensor Networks, Sensors, Communication Protocol, Fuzzy logic, Leach protocol.
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Sultan, Salman Md, Muhammad Waleed, Jae-Young Pyun, and Tai-Won Um. "Energy Conservation for Internet of Things Tracking Applications Using Deep Reinforcement Learning." Sensors 21, no. 9 (2021): 3261. http://dx.doi.org/10.3390/s21093261.
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The Internet of Things (IoT)-based target tracking system is required for applications such as smart farm, smart factory, and smart city where many sensor devices are jointly connected to collect the moving target positions. Each sensor device continuously runs on battery-operated power, consuming energy while perceiving target information in a particular environment. To reduce sensor device energy consumption in real-time IoT tracking applications, many traditional methods such as clustering, information-driven, and other approaches have previously been utilized to select the best sensor. However, applying machine learning methods, particularly deep reinforcement learning (Deep RL), to address the problem of sensor selection in tracking applications is quite demanding because of the limited sensor node battery lifetime. In this study, we proposed a long short-term memory deep Q-network (DQN)-based Deep RL target tracking model to overcome the problem of energy consumption in IoT target applications. The proposed method is utilized to select the energy-efficient best sensor while tracking the target. The best sensor is defined by the minimum distance function (i.e., derived as the state), which leads to lower energy consumption. The simulation results show favorable features in terms of the best sensor selection and energy consumption.
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Sharmin, Afsah, F. Anwar, and S. M. A. Motakabber. "A novel bio-inspired routing algorithm based on ACO for WSNs." Bulletin of Electrical Engineering and Informatics 8, no. 2 (2019): 718–26. http://dx.doi.org/10.11591/eei.v8i2.1492.
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The methods to achieve efficient routing in energy constrained wireless sensor networks (WSNs) is a fundamental issue in networking research. A novel approach of ant colony optimization (ACO) algorithm for discovering the optimum route for information transmission in the WSNs is proposed here for optimization and enhancement. The issue of path selection to reach the nodes and vital correspondence parameters, for example, the versatility of nodes, their constrained vitality, the node residual energy and route length are considered since the communications parameters and imperatives must be taken into account by the imperative systems that mediate in the correspondence procedure, and the focal points of the subterranean insect framework have been utilized furthermore. Utilizing the novel technique and considering both the node mobility and the existing energy of the nodes, an optimal route and best cost from the originating node to the target node can be detected. The proposed algorithm has been simulated and verified using MATLAB and the simulation results demonstrate that new ACO based algorithm achieved improved performance, about 30% improvement compared with the traditional ACO algorithm, and faster convergence to determine the best cost route, and recorded an improvement in the energy consumption of the nodes per transmission.
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Afsah, Sharmin, Anwar F., and M. A. Motakabber S. "A novel bio-inspired routing algorithm based on ACO for WSNs." Bulletin of Electrical Engineering and Informatics 8, no. 2 (2019): 718–28. https://doi.org/10.11591/eei.v8i2.1492.
Full textAbstract:
The methods to achieve efficient routing in energy constrained wireless sensor networks (WSNs) is a fundamental issue in networking research. A novel approach of ant colony optimization (ACO) algorithm for discovering the optimum route for information transmission in the WSNs is proposed here for optimization and enhancement. The issue of path selection to reach the nodes and vital correspondence parameters, for example, the versatility of nodes, their constrained vitality, the node residual energy and route length are considered since the communications parameters and imperatives must be taken into account by the imperative systems that mediate in the correspondence procedure, and the focal points of the subterranean insect framework have been utilized furthermore. Utilizing the novel technique and considering both the node mobility and the existing energy of the nodes, an optimal route and best cost from the originating node to the target node can be detected. The proposed algorithm has been simulated and verified using MATLAB and the simulation results demonstrate that new ACO based algorithm achieved improved performance, about 30% improvement compared with the traditional ACO algorithm, and faster convergence to determine the best cost route, and recorded an improvement in the energy consumption of the nodes per transmission.
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Yan, Jiangyu, and Bing Qi. "CARA: A Congestion-Aware Routing Algorithm for Wireless Sensor Networks." Algorithms 14, no. 7 (2021): 199. http://dx.doi.org/10.3390/a14070199.
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Congestion control is one of the key research topics in relation to the routing algorithms of wireless sensor networks (WSNs). In this paper, we propose a congestion-aware routing algorithm (CARA) for unlimited-lifetime wireless sensor networks by integrating the geographic distance and traffic load of sensor nodes. The algorithm takes alleviating congestion as the primary purpose and considers the traffic of the node itself and local network traffic. According to the geographic distance between nodes, CARA defines four decision parameters (node load factor, forward rate, cache remaining rate, and forward average cache remaining rate), selecting the best node as the next-hop through the multi-attribute decision-making method. Compared with the two existing algorithms for congestion control, our simulation results suggest that the CARA algorithm alleviates network congestion and meets reasonable network delay and energy consumption requirements.
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Shamshirband, Shahaboddin, Javad Hassannataj Joloudari, Mohammad GhasemiGol, Hamid Saadatfar, Amir Mosavi, and Narjes Nabipour. "FCS-MBFLEACH: Designing an Energy-Aware Fault Detection System for Mobile Wireless Sensor Networks." Mathematics 8, no. 1 (2019): 28. http://dx.doi.org/10.3390/math8010028.
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Wireless sensor networks (WSNs) include large-scale sensor nodes that are densely distributed over a geographical region that is completely randomized for monitoring, identifying, and analyzing physical events. The crucial challenge in wireless sensor networks is the very high dependence of the sensor nodes on limited battery power to exchange information wirelessly as well as the non-rechargeable battery of the wireless sensor nodes, which makes the management and monitoring of these nodes in terms of abnormal changes very difficult. These anomalies appear under faults, including hardware, software, anomalies, and attacks by raiders, all of which affect the comprehensiveness of the data collected by wireless sensor networks. Hence, a crucial contraption should be taken to detect the early faults in the network, despite the limitations of the sensor nodes. Machine learning methods include solutions that can be used to detect the sensor node faults in the network. The purpose of this study is to use several classification methods to compute the fault detection accuracy with different densities under two scenarios in regions of interest such as MB-FLEACH, one-class support vector machine (SVM), fuzzy one-class, or a combination of SVM and FCS-MBFLEACH methods. It should be noted that in the study so far, no super cluster head (SCH) selection has been performed to detect node faults in the network. The simulation outcomes demonstrate that the FCS-MBFLEACH method has the best performance in terms of the accuracy of fault detection, false-positive rate (FPR), average remaining energy, and network lifetime compared to other classification methods.
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Haque, Ahshanul, and Hamdy Soliman. "Hierarchical Early Wireless Forest Fire Prediction System Utilizing Virtual Sensors." Electronics 14, no. 8 (2025): 1634. https://doi.org/10.3390/electronics14081634.
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Deploying thousands of sensors across remote and challenging environments—such as the Amazon rainforest, Californian wilderness, or Australian bushlands—is a critical yet complex task for forest fire monitoring, while our backyard emulation confirmed the feasibility of small-scale deployment as a proof of concept, large-scale scenarios demand a scalable, efficient, and fault-tolerant network design. This paper proposes a Hierarchical Wireless Sensor Network (HWSN) deployment strategy with adaptive head node selection to maximize area coverage and energy efficiency. The network architecture follows a three-level hierarchy as follows: The first level incorporates cells of individual sensor nodes that connect to dynamically assigned cell heads. The second level involves the aggregated clusters of such cell heads, each with an assigned cluster head. Finally, dividing all cluster heads into regions, each with a region head, directly reports all the collected information from the forest floor to a central control sink room for decision making analysis. Unlike traditional centralized or uniformly distributed models, our adaptive approach leverages a greedy coverage maximization algorithm to dynamically select head nodes that contribute to the best forest sensed data coverage at each level. Through extensive simulations, the adaptive model achieved over 96.26% coverage, using significantly fewer nodes, while reducing node transmission distances and energy consumption. This facilitates the real-world deployment of our HWSN model in large-scale, remote forest regions, with very promising performance.
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Díez-González, Javier, Rubén Álvarez, David González-Bárcena, Lidia Sánchez-González, Manuel Castejón-Limas, and Hilde Perez. "Genetic Algorithm Approach to the 3D Node Localization in TDOA Systems." Sensors 19, no. 18 (2019): 3880. http://dx.doi.org/10.3390/s19183880.
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Positioning asynchronous architectures based on time measurements are reaching growing importance in Local Positioning Systems (LPS). These architectures have special relevance in precision applications and indoor/outdoor navigation of automatic vehicles such as Automatic Ground Vehicles (AGVs) and Unmanned Aerial Vehicles (UAVs). The positioning error of these systems is conditioned by the algorithms used in the position calculation, the quality of the time measurements, and the sensor deployment of the signal receivers. Once the algorithms have been defined and the method to compute the time measurements has been selected, the only design criteria of the LPS is the distribution of the sensors in the three-dimensional space. This problem has proved to be NP-hard, and therefore a heuristic solution to the problem is recommended. In this paper, a genetic algorithm with the flexibility to be adapted to different scenarios and ground modelings is proposed. This algorithm is used to determine the best node localization in order to reduce the Cramér-Rao Lower Bound (CRLB) with a heteroscedastic noise consideration in each sensor of an Asynchronous Time Difference of Arrival (A-TDOA) architecture. The methodology proposed allows for the optimization of the 3D sensor deployment of a passive A-TDOA architecture, including ground modeling flexibility and heteroscedastic noise consideration with sequential iterations, and reducing the spatial discretization to achieve better results. Results show that optimization with 15% of elitism and a Tournament 3 selection strategy offers the best maximization for the algorithm.
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Jenila, L., and R. Aroul Canessane. "Cross Layer Based Dynamic Traffic Scheduling Algorithm for Wireless Multimedia Sensor Network." International Journal of Electrical and Electronics Research 10, no. 2 (2022): 399–404. http://dx.doi.org/10.37391/ijeer.100256.
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The data traffic volume is generally huge in multimedia networks since it comprises multimodal sensor nodes also communication takes place with variable capacity during video transmission. The data should be processed in a collision free mode. Therefore, the packets should be scheduled and prioritized dynamically. Dynamic traffic scheduling and optimal routing protocol with cross layer design is proposed here to select the energy efficient nodes and to transmit the scheduled data effectively. At first, the optimal routes are discovered by selecting the best prime nodes then the packets are dynamically scheduled on the basis of severity of data traffic. The proposed method works in two stages such as (i) Selection of chief nodes and (ii) Dynamic packet scheduling. The first stage of this mechanism is chief node selection and these chief nodes are selected for optimal routing. Selection of chief nodes is done by estimating the distance between the nodes, and energy value of the nodes. This stage makes the network energy efficient. The second stage is involved with dynamic scheduling of packets and sending the packets with respect to the Packet Priority of queue index key value. Real-time data packets (PQP1) have very high priority and it is scheduled using Earliest Deadline First Scheduling (EDFS) algorithm when compared to non-real time data packets (PQP2 and PQP3) which is scheduled on basis of First Come First Serve (FCFS) manner. This process minimizes the congestion and avoids the unnecessary transmission delay. Therefore, the results are analyzed through the simulation process and the efficiency of the proposed methodology is 56% better than the existing methodologies.
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Somula, Ramasubbareddy, Yongyun Cho, and Bhabendu Kumar Mohanta. "SWARAM: Osprey Optimization Algorithm-Based Energy-Efficient Cluster Head Selection for Wireless Sensor Network-Based Internet of Things." Sensors 24, no. 2 (2024): 521. http://dx.doi.org/10.3390/s24020521.
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The Internet of Things (IoT) has transformed various aspects of human life nowadays. In the IoT transformative paradigm, sensor nodes are enabled to connect multiple physical devices and systems over the network to collect data from remote places, namely, precision agriculture, wildlife conservation, intelligent forestry, and so on. The battery life of sensor nodes is limited, affecting the network’s lifetime, and requires continuous maintenance. Energy conservation has become a severe problem of IoT. Clustering is essential in IoT to optimize energy efficiency and network longevity. In recent years, many clustering protocols have been proposed to improve network lifetime by conserving energy. However, the network experiences an energy-hole issue due to picking an inappropriate Cluster Head (CH). CH node is designated to manage and coordinate communication among nodes in a particular cluster. The redundant data transmission is avoided to conserve energy by collecting and aggregating from other nodes in clusters. CH plays a pivotal role in achieving efficient energy optimization and network performance. To address this problem, we have proposed an osprey optimization algorithm based on energy-efficient cluster head selection (SWARAM) in a wireless sensor network-based Internet of Things to pick the best CH in the cluster. The proposed SWARAM approach consists of two phases, namely, cluster formation and CH selection. The nodes are clustered using Euclidean distance before the CH node is selected using the SWARAM technique. Simulation of the proposed SWARAM algorithm is carried out in the MATLAB2019a tool. The performance of the SWARAM algorithm compared with existing EECHS-ARO, HSWO, and EECHIGWO CH selection algorithms. The suggested SWARAM improves packet delivery ratio and network lifetime by 10% and 10%, respectively. Consequently, the overall performance of the network is improved.
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Moungla, Hassine, Nora Touati, and Ahmed Mehaoua. "Cost Efficient Deployment and Reliable Routing Modeling Based Multi-Objective Optimization for Dynamic Wireless Body Sensor Networks Topology." International Journal of E-Health and Medical Communications 4, no. 4 (2013): 16–33. http://dx.doi.org/10.4018/ijehmc.2013100102.
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Wireless Body Sensor Networks (WBSNs), like any other sensor networks, suffer from limited energy and are highly distributed network, where its nodes organize by themselves and each of them has the flexibility of collecting and transmitting patient biomedical information to a sink. When a knowledge was sent to a sink from a path that doesn't have a definite basis, the routing is a crucial challenge in Wireless Body Area Sensor Networks. Furthermore, reliability and routing delay are the considerable factors in these types of networks. More attention should be given to the energy routing issue and frequent topology's change in WBSNs. That increases the dynamics of network topology, and complicates the relay selection process in cooperative communications. Unreliable communication over the wireless channel complicates communication protocols and results in low data yield (Stathopoulos 2005). The deployment sensors step is a crucial and complex task due to several independent objectives and constraints. This paper presents a Min-Max multi-commodity flow model for WBSNs which allows preventing sensor node saturation and taking best action against reliability and the path loss, by imposing an equilibrium use of sensors during the routing process. This model is based on the authors' optimal sensors deployment method for WBSNs. Simulations results show that the algorithm balances the energy consumption of nodes effectively and maximize the network lifetime. It will meet the enhanced WBSNs requirements, including better delivery ratio, less reliable routing overhead.
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Nageswararao, Malisetti, and Kumar Pamula Vinay. "The effectiveness of jaya optimization for energy aware cluster based routing in wireless sensor networks." i-manager’s Journal on Wireless Communication Networks 13, no. 1 (2024): 18. http://dx.doi.org/10.26634/jwcn.13.1.20965.
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The Internet of Things (IoT) has significantly impacted human life, enhancing quality of life and transforming various commercial sectors. The sensor nodes in the IoT are interconnected to facilitate the passage of data to the sink node over the network. Due to the constraints of battery power, energy in the nodes is preserved through the utilization of clustering techniques. Choosing a Cluster Head (CH) is crucial for prolonging the network's lifespan and increasing its throughput during the clustering process. Numerous optimization techniques have been developed to select the best Cluster Head (CH) to enhance energy efficiency in network nodes. Therefore, using incorrect CH selection methods leads to longer convergence times and faster depletion of sensor batteries. This research proposes a method that incorporates a CH selection strategy using the Jaya optimization method. The proposed methodology is evaluated against existing algorithms in terms of network longevity and energy efficiency. The simulation results indicate that the Jaya optimization algorithm-based CH selection scheme (Jaya-EEC) is much more effective in terms of network longevity compared to LEACH, LEACH-E, and PSO-C. Specifically, Jaya-EEC outperforms LEACH by 72%, LEACH-E by 64%, and PSO-C by 60%.
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Prakoso, Bagas Mardiasyah, Ahmad Zainudin, Prima Kristalina, and Rizqi Fauzil Azhar. "Performance Evaluation of Distribution Node in Case of LEACH Implementation on Wireless Sensor Network." Jurnal Elektronika dan Telekomunikasi 18, no. 2 (2018): 67. http://dx.doi.org/10.14203/jet.v18.67-74.
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Wireless sensor networks consisting of sensor nodes can be used as an effective tool for collecting data in various situations. Nodes are usually placed randomly in an area to perform sensing and monitor various parameters related to environmental conditions in various locations. One of the major problems in wireless sensor networks is developing energy-efficient routing protocols that have a significant impact on the overall life of sensor networks so it is important to make energy savings in these limited energy sources to extend network life. This paper proposes a hardware design and Low-Energy Adaptive Clustering Hierarchy (LEACH) routing protocol configuration for power saving by utilizing cluster head selection mechanism. The cluster head selection process is performed periodically based on LEACH algorithm enables the node to have the best lifetime responsible for communication between the nodes and the server as well as the effort to save energy consumption of limited energy sources to extend network life. So that makes the process of sending information more effective and optimal. The system has been able to display data information along with the position of nodes in the web server with an average of 42 seconds of computing time in a rotation of the system so that it can be done 85 times in 1 hour. The system is able to provide real-time information with a throughput of more than 1.052 Kbps and packet loss of no more than 6.7%. In addition, energy savings can up to 6.5% of the existing energy in a lithium battery.
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MAHFOUDH, SAOUCENE, and PASCALE MINET. "EOLSR: AN ENERGY EFFICIENT ROUTING PROTOCOL IN WIRELESS AD HOC AND SENSOR NETWORKS." Journal of Interconnection Networks 09, no. 04 (2008): 389–408. http://dx.doi.org/10.1142/s0219265908002345.
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Energy efficiency is a key issue in wireless ad hoc and sensor networks. In order to maximize network lifetime, several directions have been explored, among them energy efficient routing. In this paper, we show how to extend the standardized OLSR routing protocol, in order to make it energy efficient. This extension selects the path minimizing the energy consumed in the end-to-end transmission of a flow packet and avoids nodes with low residual energy. As it has been shown that two-path routing is energy efficient, we compare this extension with a two-path source routing strategy (with different links or different nodes). Moreover, to take into account residual node energy, the native selection of multipoint relays of OLSR is changed. Three selection algorithms based on the minimum residual energy are evaluated. An extensive performance evaluation allows us to choose for EOLSR (Energy efficient OLSR) the best variant maximizing both network lifetime and delivery rate.
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Kondratjevs, K., A. Zabasta, and V. Selmanovs-Pless. "Development of Solar Powered Feeding Scheme for Wireless Sensor Networks in low Solar Density Conditions / Bezvadu Sensoru Tīklu Elektroapgādes Sistēmas Izstrāde, Kas Izmanto Saules Paneļus Un Darbojas Pazeminātas Saules Radiācijas Apstākļos." Latvian Journal of Physics and Technical Sciences 52, no. 4 (2015): 43–56. http://dx.doi.org/10.1515/lpts-2015-0022.
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Abstract In the recent years, there has been significant research focus on the safety and reliability of data harvesting and optimal energy consuming by wireless sensor network nodes. If external electrical power fails, the node needs to be able to send notifications to the utility demanding the use of backup energy strategies. The authors of the research offer an approach that can help to use PV panels as an alternative power source for WSN nodes in particular irradiation conditions. Survey and testing of the main types of PV panels offered on the market in conditions closed to real ones, in which WSN nodes are maintained, have been implemented. Based on the test results, maximum power control module parameters can be calculated in order to achieve the best effectiveness of the power control system for a selected type of PV panel or panel group. The novelty of the research is an approach that includes an original test bed design for PV testing, PV testing method and selection of design and MPP control module parameters, which ensure maximum effectiveness of WSN node power feeding.
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Zhao, Kun, Kegang Pan, and Bangning Zhang. "Cooperative Transmission in Mobile Wireless Sensor Networks with Multiple Carrier Frequency Offsets: A Double-Differential Approach." Mathematical Problems in Engineering 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/853821.
Full textAbstract:
As a result of the rapidly increasing mobility of sensor nodes, mobile wireless sensor networks (MWSNs) would be subject to multiple carrier frequency offsets (MCFOs), which result in time-varying channels and drastically degrade the network performance. To enhance the performance of such MWSNs, we propose a relay selection (RS) based double-differential (DD) cooperative transmission scheme, termed RSDDCT, in which the best relay sensor node is selected to forward the source sensor node’s signals to the destination sensor node with the detect-and-forward (DetF) protocol. Assuming a Rayleigh fading environment, first, exact closed-form expressions for the outage probability and average bit error rate (BER) of the RSDDCT scheme are derived. Then, simple and informative asymptotic outage probability and average BER expressions at the large signal-to-noise ratio (SNR) regime are presented, which reveal that the RSDDCT scheme can achieve full diversity. Furthermore, the optimum power allocation strategy in terms of minimizing the average BER is investigated, and simple analytical solutions are obtained. Simulation results demonstrate that the proposed RSDDCT scheme can achieve excellent performance over fading channels in the presence of unknown random MCFOs. It is also shown that the proposed optimum power allocation strategy offers substantial average BER performance improvement over the equal power allocation strategy.
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Mariappan, Dinesh Babu, R. Saminathan, and K. M. Baalamurugan. "Cooperative Hyper-Scheduling based improving Energy Aware Life Time Maximization in Wireless Body Sensor Network Using Topology Driven Clustering Approach." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 6 (2023): 09–20. http://dx.doi.org/10.17762/ijritcc.v11i6.6766.
Full textAbstract:
The Wireless Body Sensor Network (WBSN) is an incredible developing data transmission network for modern day communication especially in Biosensor device networks. Due to energy consumption in biomedical data transfer have impacts of sink nodes get loss information on each duty cycle because of Traffic interruptions. The reason behind the popularity of WBSN characteristics contains number of sensor nodes to transmit data in various dense regions. Due to increasing more traffic, delay, bandwidth consumption, the energy losses be occurred to reduce the lifetime of the WBSN transmission. So, the sensor nodes are having limited energy or power, by listening to the incoming signals, it loses certain amount of energy to make data losses because of improper route selection. To improve the energy aware lifetime maximization through Traffic Aware Routing (TAR) based on scheduling. Because the performance of scheduling is greatly depending on the energy of nodes and lifetime of the network. To resolve this problem, we propose a Cooperative Hyper-scheduling (CHS) based improving energy aware life time maximization (EALTM) in Wireless Body sensor network using Topology Driven Clustering Approach (TDCA).Initially the method maintains the traces of transmission performed by different Bio-sensor nodes in different duty cycle. The method considers the energy of different nodes and history of earlier transmission from the Route Table (RT) whether the transmission behind the Sink node. Based on the RT information route discovery was performed using Traffic Aware Neighbors Discovery (TAND) to estimate Data Transmission Support Measure (DTSM) on each Bio-sensor node which its covers sink node. These nodes are grouped into topology driven clustering approach for route optimization. Then the priority is allocated based on The Max-Min DTSM, the Cooperative Hyper-scheduling was implemented to schedule the transmission with support of DTSM to reduce the energy losses in WBSN. This improves the energy level to maximization the life time of data transmission in WBSN than other methods to produce best performance in throughput energy level.
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Pathak, Tanya, Vinay Kumar Singh, and Anurag Sharma. "ENERGY EFFICIENT ROUTING PROTOCOL FOR INCREASING LIFETIME OF WIRELESS SENSOR NETWORK." International Journal of Engineering Technologies and Management Research 5, no. 2 (2020): 240–48. http://dx.doi.org/10.29121/ijetmr.v5.i2.2018.654.
Full textAbstract:
In the recent years, an efficient design of a Wireless Sensor Network has become important in the area of research. The major challenges in the design of Wireless Sensor Network is to improve the network lifetime. The main difficulty for sensor node is to survive in that monitoring area for the longer time that means there is a need to increase the lifetime of the sensor nodes by optimizing the energy and distance.
 There are various existing routing protocols in which optimal routing can be achieved like Data-Centric, Hierarchical and Location-based routing protocols. In this paper, new power efficient routing protocol is being proposed that not only select the shortest path between the source node and sink node for data transmission but also maximizes the lifetime of the participating nodes by selecting the best path for sending the data packet across the network. The main objective of this research is to develop a faster algorithm to find the energy efficient route for Wireless Sensor Network. Simulation results shows that this strategy achieves long network lifetime when compared to the other standard protocols.