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Journal articles on the topic 'Self-organized wireless networks'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Rogers, A., E. David, and N. R. Jennings. "Self-Organized Routing for Wireless Microsensor Networks." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 35, no. 3 (May 2005): 349–59. http://dx.doi.org/10.1109/tsmca.2005.846382.

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2

Decotignie, Jean-Dominique. "Propagation delays in self-organized wireless sensor networks." IFAC Proceedings Volumes 36, no. 13 (July 2003): 53–57. http://dx.doi.org/10.1016/s1474-6670(17)32464-3.

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3

Han, Dan, and Lingmei Fu. "A Routing Algorithms for Resource Constrained Wireless Self-organized Networks." International Journal of Online Engineering (iJOE) 13, no. 11 (November 22, 2017): 136. http://dx.doi.org/10.3991/ijoe.v13i11.7750.

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<p><span style="font-size: medium;"><span style="font-family: 宋体;">To explore the algorithms for wireless self-organized networks, through the NS-2 network simulation platform, the simulation analysis is made on the performances of multi hop data transmission of the existing four typical Ad hoc network routing protocols. And the energy saving strategy of Ad hoc network routing protocol SFR (Selection Forwarding Routing) based on network average node connection degree is discussed and analyzed, which is suitable for intensive Ad hoc network. The simulation data showed that, SFR protocol can, under the premise of ensuring the network coverage rate the same as that of flooding algorithm, reduce more than 56.1% redundant information in the network, and reduce the energy consumption of network by more than 30.2%. Finally, it is concluded that the selection forwarding routing has quite good performance.</span></span></p>

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4

Rizvi, Syed, Kelsey Karpinski, and Abdul Razaque. "Novel Architecture of Self-organized Mobile Wireless Sensor Networks." Journal of Computing Science and Engineering 9, no. 4 (December 30, 2015): 163–76. http://dx.doi.org/10.5626/jcse.2015.9.4.163.

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5

Peltomaki, Matti, Juha-Matti Koljonen, Olav Tirkkonen, and Mikko Alava. "Algorithms for Self-Organized Resource Allocation in Wireless Networks." IEEE Transactions on Vehicular Technology 61, no. 1 (January 2012): 346–59. http://dx.doi.org/10.1109/tvt.2011.2151891.

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6

Dixit, S., E. Yanma, and O. K. Tonguz. "On the design of self-organized cellular wireless networks." IEEE Communications Magazine 43, no. 7 (July 2005): 86–93. http://dx.doi.org/10.1109/mcom.2005.1470827.

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7

Hyder, Waheeduddin, Javier Poncela, Miguel-Angel Luque, and Pablo Otero. "Self-Organized Fast Routing Protocol for Radial Underwater Networks." Sensors 18, no. 12 (November 28, 2018): 4178. http://dx.doi.org/10.3390/s18124178.

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An underwater wireless sensor networks (UWSNs) is an emerging technology for environmental monitoring and surveillance. One of the side effects of the low propagation speed of acoustic waves is that routing protocols of terrestrial wireless networks are not applicable. To address this problem, routing strategies focused on different aspects have been proposed: location free, location based, opportunistic, cluster based, energy efficient, etc. These mechanisms usually require measuring additional parameters, such as the angle of arrival of the signal or the depth of the node, which makes them less efficient in terms of energy conservation. In this paper, we propose a cross-layer proactive routing initialization mechanism that does not require additional measurements and, at the same time, is energy efficient. The algorithm is designed to recreate a radial topology with a gateway node, such that packets always use the shortest possible path from source to sink, thus minimizing consumed energy. Collisions are avoided as much as possible during the path initialization. The algorithm is suitable for 2D or 3D areas, and automatically adapts to a varying number of nodes, allowing one to expand or decrease the networked volume easily.

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8

Smys, S., and Jennifer S. Raj. "A self-organized structure for mobility management in wireless networks." Computers & Electrical Engineering 48 (November 2015): 153–63. http://dx.doi.org/10.1016/j.compeleceng.2015.09.024.

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9

Tan, Qing, and Xiao Jing Yue. "Comparative Performance Analysis of Flat and Hierarchical Routing in Wireless Sensor Network." Applied Mechanics and Materials 685 (October 2014): 587–90. http://dx.doi.org/10.4028/www.scientific.net/amm.685.587.

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Wireless sensor network is composed of a set of sensors in a wireless network of self-organized. Research on topological structure of wireless sensor network is focused in two directions, namely plane topology structure and hierarchical topology structure. This paper gives a detailed analysis of wireless sensor networks in the flat routing protocols and hierarchical routing protocols, and compares the advantages and disadvantages of the performance of two kinds of protocol by simulation experiment.

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10

Gong, Bei, Jingxuan Zhu, and Yubo Wang. "Construction of Trusted Routing Based on Trust Computation." Wireless Communications and Mobile Computing 2021 (April 19, 2021): 1–10. http://dx.doi.org/10.1155/2021/6657580.

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In the field of applied IoT, a large number of wireless sensor devices are tasked with data production and collection, providing IoT subjects with a large amount of basic data to support top-level IoT applications. However, there is a considerable risk of being attacked on such sensor networks that are organized in a wireless form. These relatively independent network devices have extremely limited performance and lifetime, a problem that can be supplemented in a centralized network with base stations by relying on the performance of the core nodes of the network, but in a decentralized self-organizing network, they can have a serious adverse impact on the implementation of security solutions. Considering the fundamental nature of the data generated by such end devices in IoT application services, the protection of their security is also directly related to the quality of upper layer services provided. The main research result of this paper is the design of a trust routing scheme for self-organizing networks. The scheme is based on a comprehensive evaluation of data transmission rate, transmission delay, and other factors related to the operation status of the self-organized network and improves the efficiency of the overall work of the self-organized network by reducing the performance consumption of individual nodes of the self-organized network and balancing the network load.

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11

Kominami, Daichi, Masashi Sugano, Masayuki Murata, and Takaaki Hatauchi. "Controlled and self-organized routing for large-scale wireless sensor networks." ACM Transactions on Sensor Networks 10, no. 1 (November 2013): 1–27. http://dx.doi.org/10.1145/2529920.

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12

Youssef, Sherin M., Meer A. Hamza, and Salma F. Fayed. "EQOWSN: Evolutionary-based query optimization over self-organized wireless sensor networks." Expert Systems with Applications 36, no. 1 (January 2009): 81–92. http://dx.doi.org/10.1016/j.eswa.2007.09.062.

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13

Hyder, Waheeduddin, Miguel-Ángel Luque-Nieto, Javier Poncela, and Pablo Otero. "Self-Organized Proactive Routing Protocol for Non-Uniformly Deployed Underwater Networks." Sensors 19, no. 24 (December 12, 2019): 5487. http://dx.doi.org/10.3390/s19245487.

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Electromagnetic (EM) waves cannot propagate more than few meters in sea water due to the high absorption rate. Acoustic waves are more suitable for underwater communication, but they travel very slowly compared to EM waves. The typical speed of acoustic waves in water is 1500 m/s, whereas speed of EM waves in air is approximately 3 × 108 m/s. Therefore, the terrestrial wireless sensor network (WSN) protocols assume that the propagation delay is negligible. Hence, reactive protocols are deemed acceptable for WSNs. Other important issues related to underwater wireless sensor networks (UWSNs) are determining the position of the underwater nodes and keeping a time synchronization among the nodes. Underwater nodes can neither determine their position nor synchronize using Global Navigation Satellite Systems (GNSS) because of the short penetration of EM waves in sea water. The limited mobility of UWSN nodes and variation in the propagation speed of acoustic waves make time synchronization a challenging task for underwater acoustic networks (UASNs). For all these reasons, WSN protocols cannot be readily used in UASNs. In this work, a protocol named SPRINT is designed to achieve high data throughput and low energy operation in the nodes. There is a tradeoff between the throughput and the energy consumption in the wireless networks. Longer links mean higher energy consumption. On the other hand, the number of relay nodes or hops between the source node and the final destination node is a key factor which affects the throughput. Each hop increases the delay in the packet forwarding and, as a result, decreases the throughput. Hence, energy consumption requires the nearest nodes to be chosen as forwarding nodes, whereas the throughput requires the farthest node to be selected to minimize the number of hops. SPRINT is a cross-layer, self-organized, proactive protocol which does not require positioning equipment to determine the location of the node. The routing path from the node to the gateway is formed based on the distance. The data sending node prefers to choose the neighbor node which is closest to it. The distance is measured by the signal strength between the two nodes.

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14

Khan, Murad, and Kijun Han. "An Optimized Network Selection and Handover Triggering Scheme for Heterogeneous Self-Organized Wireless Networks." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/173068.

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Optimizing the balance between different handover parameters for network selection is one of the challenging tasks for seamless communication in heterogeneous networks. Traditional approaches for network selection are mostly based on the Receive Signal Strength (RSS) from the Point of Attachment (PoA) of a network. Most of these schemes are suffered from high handover delay, false handover indications, and inappropriate network selection for handover. To address these problems, we present an optimized network selection scheme based on the speed of a mobile node. A mechanism based on two different thresholds on the speed of a Mobile Node (MN) is integrated in the proposed scheme. If the speed of an MN is greater than any of the threshold, the MN performs handover to a particular network. We employ Grey Relational Analysis (GRA) in the proposed scheme to select the best PoA of the selected network. Similarly, to deal with false handover indications, we proposed an optimized handover triggering technique. We compare our proposed scheme with existing schemes in context of energy consumption for scanning, frequent and failed handovers, packet loss ratio, and handover delay. The proposed scheme shows superior performance and it outperforms existing schemes used for similar purpose. Moreover, simulation results show the accuracy and performance of the proposed scheme.

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15

K, Kumaravel, and Sengaliappan M. "Performance routing with shortest path exploration in wireless mesh networks." Kongunadu Research Journal 7, no. 1 (April 15, 2020): 50–53. http://dx.doi.org/10.26524/krj.2020.8.

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In wireless mesh network the nodes are dynamically self-organized and self- configured networks create a changing topology and keep a mesh connectivity to offer Internet access to the users. The shortest path problem is one of the most fundamental problems in networking. This problem can be solved by manytechniques and algorithm. In this paper we find the shortest path by using the fittest nodes in the network. By using the fittest node we can send the packets to the destination without packet loss, delay in packets.Average end to end delay is decreased by increasing bandwidth and the results are shown.

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16

Sharama, Apurva, and Dr Jaswinder Singh. "Survey of technologies of self-organizing networks (SON)." International Journal of Engineering & Technology 7, no. 4 (September 24, 2018): 2581. http://dx.doi.org/10.14419/ijet.v7i4.16831.

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Due to increase in existing web availability, self organized systems are expected to give a quick, adaptable and cost-effective solution for satisfy the gap between limit and request/demand to adapt to the quick development in remote activity or wireless traffic. The main purpose of introducing SON algorithm is to simplify the network operations via automating repeated tasks in network operations. Hence, in SON empowered system operations, methods that hold the human administrator in manual system operations are substituted via programmed SON functions. Self organized systems or intelligent frameworks are required for remote portable systems to deal with broad number of clients in the meantime and to support the human administrator in manual system operations; that are substituted via automatic SON functions since the human administrators don't have to gather and examine the system information. Self organized networks are needed for the controlling the big challenge of mobile traffic growth and to reduce the cost efficiency. Efficient methods are required for automatic channel selection, power adjustment, and frequency assignment for autonomous interference coordination and coverage optimization.

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17

Hu, Jin Hui, Da Bin Hu, and Jian Bo Xiao. "Study of Positioning Technology in Sonobuoy Networks Based on DV-Hop Algorithm." Advanced Materials Research 711 (June 2013): 473–76. http://dx.doi.org/10.4028/www.scientific.net/amr.711.473.

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On the basis of analysis of sonobuoy using situation in the modern anti-warship warfare, wireless sensor networks with multiple sonobuoys are studied for detecting mission. The unknown nodes in the network are positioned by using of DV-Hop algorithm. The research results show that this method is practical and makes the network be self-organized and extensible.

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18

Lee, Kyu-Hong, and Hee-Sang Lee. "A Study on Energy Efficient Self-Organized Clustering for Wireless Sensor Networks." Journal of Korean Institute of Industrial Engineers 37, no. 3 (September 1, 2011): 180–90. http://dx.doi.org/10.7232/jkiie.2011.37.3.180.

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19

LI, Xi, and Hong JI. "Scalable peer-to-peer resource discovering scheme for wireless self-organized networks." Journal of China Universities of Posts and Telecommunications 16, no. 2 (April 2009): 47–57. http://dx.doi.org/10.1016/s1005-8885(08)60200-9.

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20

Qu, Hongchun, Xiaohai Liu, Wentong Wang, Xiaoming Tang, Linqin Cai, and Ping Wang. "A Biologically Inspired Strategy for Self-Organized Routing in Wireless Sensor Networks." Journal of Computational and Theoretical Nanoscience 12, no. 12 (December 1, 2015): 6006–10. http://dx.doi.org/10.1166/jctn.2015.4750.

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21

Qiao, Mu, Haitao Zhao, Li Zhou, Chunsheng Zhu, and Shengchun Huang. "Topology-Transparent Scheduling Based on Reinforcement Learning in Self-Organized Wireless Networks." IEEE Access 6 (2018): 20221–30. http://dx.doi.org/10.1109/access.2018.2823725.

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22

Elhoseny, Mohamed, Xiaohui Yuan, and M. Gunasekaran. "Special issue on machine learning applications for self-organized wireless sensor networks." Neural Computing and Applications 31, S1 (December 11, 2018): 1–2. http://dx.doi.org/10.1007/s00521-018-3926-y.

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23

Gajjar, Sachin, Mohanchur Sarkar, and Kankar Dasgupta. "Self Organized, Flexible, Latency and Energy Efficient Protocol for Wireless Sensor Networks." International Journal of Wireless Information Networks 21, no. 4 (September 30, 2014): 290–305. http://dx.doi.org/10.1007/s10776-014-0251-y.

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24

Saha, Dibakar, and Nabanita Das. "Self-organized area coverage in wireless sensor networks by limited node mobility." Innovations in Systems and Software Engineering 12, no. 3 (April 15, 2016): 227–38. http://dx.doi.org/10.1007/s11334-016-0277-7.

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25

Santhi, C., and D. Sharmila. "A self-organized location aware energy efficient protocol for wireless sensor networks." Computers & Electrical Engineering 41 (January 2015): 265–74. http://dx.doi.org/10.1016/j.compeleceng.2014.04.007.

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26

Smys, S., and G. Josemin Bala. "STAB-WIN: Self Organized, Topology Control Ability Backbone Node in Wireless Networks." Wireless Personal Communications 63, no. 3 (September 14, 2010): 529–48. http://dx.doi.org/10.1007/s11277-010-0148-8.

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27

Lee, Kyuhong, and Heesang Lee. "A Self-Organized and Smart-Adaptive Clustering and Routing Approach for Wireless Sensor Networks." International Journal of Distributed Sensor Networks 8, no. 1 (January 1, 2012): 156268. http://dx.doi.org/10.1155/2012/156268.

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Efficient energy consumption is a critical factor for the deployment and operation of wireless sensor networks (WSNs). In general, WSNs perform clustering and routing using localized neighbor information only. Therefore, some studies have used self-organized systems and smart mechanisms as research methods. In this paper, we propose a self-organized and smart-adaptive clustering (SOSAC) and routing method, which performs clustering in WSNs, operates the formed clusters in a smart-adaptive way, and performs cluster-based routing. SOSAC is comprised of three mechanisms, which are used to change the fitness value over time, to back up routing information in preparation for any potential breakdown in WSNs, and to adapt to the changes of the number of sensor nodes for a WSN. We compared the performance of the proposed SOSAC with that of a well-known clustering and routing protocol for WSNs. Our computational experiments demonstrate that the network lifetime, energy consumption, and scalability of SOSAC are better than those of the compared method.

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28

Benzerbadj, Ali, Bouabdellah Kechar, Ahcéne Bounceur, and Bernard Pottier. "Energy Efficient Approach for Surveillance Applications Based on Self Organized Wireless Sensor Networks." Procedia Computer Science 63 (2015): 165–70. http://dx.doi.org/10.1016/j.procs.2015.08.328.

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29

Lee, Kyuhong, and Heesang Lee. "Energy-Efficient Self-Organized Clustering with Splitting and Merging for Wireless Sensor Networks." International Journal of Distributed Sensor Networks 9, no. 3 (January 2013): 487846. http://dx.doi.org/10.1155/2013/487846.

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30

Kaur, Supreet, and Rajiv Mahajan. "Energy efficient clustering protocol for wireless sensor networks." Modern Physics Letters B 32, no. 32 (November 20, 2018): 1850400. http://dx.doi.org/10.1142/s0217984918504006.

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In this paper, a hybrid soft computing technique-based energy efficient protocol is proposed to improve the inter-cluster data aggregation in clustering based general self-organized tree based energy balance (GSTEB) routing protocol. Initially, improved ant colony optimization-based technique is used to select optimal cluster heads. Afterwards, a hybrid soft computing technique is utilized to communicate the data from cluster heads to sink. Extensive experiments have been done by considering the existing and proposed technique. Experimental results indicate that the proposed technique provides better network lifetime as compared to existing techniques.

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31

Liu, Zhiquan, Jianfeng Ma, Zhongyuan Jiang, Hui Zhu, and Yinbin Miao. "LSOT: A Lightweight Self-Organized Trust Model in VANETs." Mobile Information Systems 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/7628231.

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With the advances in automobile industry and wireless communication technology, Vehicular Ad hoc Networks (VANETs) have attracted the attention of a large number of researchers. Trust management plays an important role in VANETs. However, it is still at the preliminary stage and the existing trust models cannot entirely conform to the characteristics of VANETs. This work proposes a novel Lightweight Self-Organized Trust (LSOT) model which contains trust certificate-based and recommendation-based trust evaluations. Both the supernodes and trusted third parties are not needed in our model. In addition, we comprehensively consider three factor weights to ease the collusion attack in trust certificate-based trust evaluation, and we utilize the testing interaction method to build and maintain the trust network and propose a maximum local trust (MLT) algorithm to identify trustworthy recommenders in recommendation-based trust evaluation. Furthermore, a fully distributed VANET scenario is deployed based on the famous Advogato dataset and a series of simulations and analysis are conducted. The results illustrate that our LSOT model significantly outperforms the excellent experience-based trust (EBT) and Lightweight Cross-domain Trust (LCT) models in terms of evaluation performance and robustness against the collusion attack.

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32

Lee, Kyu Hong, and Hee Sang Lee. "Energy Efficient Sensor Configuration by Fishing Spider Inspired Mechanism." Applied Mechanics and Materials 284-287 (January 2013): 2049–55. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.2049.

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Wireless sensor networks have inherent characteristics that differ from other wireless networks. Therefore, topology configuration and routing methods in WSNs must address these characteristics. In this paper, we propose an energy efficient clustering model. This model was inspired by the behaviors and capabilities of the six-spotted fishing spider, Dolomedes triton. The suggested model performs cluster-heads selection and clustering in self-organized ways. In order to determine the cluster-heads and the cluster-members, each sensor node uses the local information and simple rules that have been inspired by the Dolomedes triton. We compared our model with a well-known cluster-based routing protocol that uses random fairness for the selection of sensor node cluster-heads. In our computational experiments, we have showed that the energy efficiency and lifetimes of our bio-inspired model exceeds those of the comparison protocol by only using simple bio-inspired mechanism. We also demonstrate our model’s good performance in terms of scalability, which is one of the important indicators of performance for self-organized wireless sensor networks.

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Zhang, Hong, Shigen Shen, Qiying Cao, Xiaojun Wu, and Shaofeng Liu. "Modeling and analyzing malware diffusion in wireless sensor networks based on cellular automaton." International Journal of Distributed Sensor Networks 16, no. 11 (November 2020): 155014772097294. http://dx.doi.org/10.1177/1550147720972944.

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Wireless sensor networks, as a multi-hop self-organized network system formed by wireless communication, are vulnerable to malware diffusion by breaking the data confidentiality and service availability, owing to their low configuration and weak defense mechanism. To reveal the rules of malware diffusion in the really deployed wireless sensor networks, we propose a model called Malware Diffusion Based on Cellular Automaton to describe the dynamics of malware diffusion based on cellular automaton. According to the model, we first analyze and obtain the differential equations, which can reflect the various state dynamics of sensor nodes with cellular automaton. Then, we attain the equilibrium points of the model Malware Diffusion Based on Cellular Automaton to determine the threshold for whether malware will diffuse or die out in wireless sensor networks. Furthermore, we compute the basic regeneration number of the model Malware Diffusion Based on Cellular Automaton using the next-generation matrix and prove the stability of the equilibrium points. Finally, via experimental simulation, we verify the effectiveness of the model Malware Diffusion Based on Cellular Automaton, which can provide administrators with the theoretical guidance on suppressing malware diffusion in wireless sensor networks.

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Saqib, Muhammad, Farrukh Zeeshan Khan, Muneer Ahmed, and Raja Majid Mehmood. "A critical review on security approaches to software-defined wireless sensor networking." International Journal of Distributed Sensor Networks 15, no. 12 (December 2019): 155014771988990. http://dx.doi.org/10.1177/1550147719889906.

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Wireless sensor networks (WSNs) are very prone to ongoing security threats due to its resource constraints and unprotected transmission medium. WSN contains hundreds and thousands of resource-constrained and self-organized sensor nodes. These sensor nodes are usually organized in a distributed manner; thus, it permits the creation of an ad hoc network without predefined infrastructure or centralized management. As WSNs are going to get control of real-time applications, where a malicious activity can cause serious damage, the inherent challenge is to fortify the security enforcement in these networks. As a solution, software-defined network (SDN) has come out and has been merged with WSN to form what is known as software-defined wireless sensor network (SDWSN). SDWSN has come into existence, and it legitimizes network operators with more flexibility and control over the network. SDWSN has more tightened the security enforcement based on the global view and centralized control of the network topology. Moreover, machine learning (ML)–based and deep learning (DL)–based network intrusion detection systems (NIDS) have been introduced to the SDN environment to protect the networks against anomaly threats. In this review article, we illustrated the SDN–based security approaches to WSN followed by its architectures, advantages, and possible security threats. Finally, ML/DL–based NIDS integrated with the SDN controller is proposed as a complete solution for the WSN environment to confront the ongoing anomaly threats and to sufficiently protect the network against both known and unknown attacks.

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Aarab, Zineb, Asmae El Ghazi, Rajaa Saidi, and Moulay Driss Rahmani. "Towards a context-aware Wireless Sensor Networks." International Journal of Engineering & Technology 7, no. 3 (August 22, 2018): 1869. http://dx.doi.org/10.14419/ijet.v7i3.15667.

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Recently, the development of wireless sensor networks (WSNs) is spreading rapidly. WSNs are highly distributed self-organized systems which comprise a large number of resource constrained sensor nodes. Developers of WSNs face many challenges from communication, memory, limited energy… Also, mobility has become a major concern for WSN researchers. Indeed, Mobile WSNs (MWSN) consist of mobile sensor nodes that can move on their own and also interact with the physical environment. Developing applications for MWSN is a complicated process because of the wide variety of WSN applications and low-level implementation details. Integrating context-awareness can improve MWSN applications results. In this paper, some research issues and challenges involved in the design of WSNs are presented. Model-Driven Engineering offers an effective solution to WSN application developers by hiding the details of lower layers and raising the level of abstraction. In this sense, we propose a context-aware WSN architecture and WSN metamodel to ease the work for developers in this field.

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36

ODA, Akihiro, and Hiroaki NISHI. "Self-Organized Link State Aware Routing for Multiple Mobile Agents in Wireless Network." IEICE Transactions on Communications E93-B, no. 8 (2010): 2012–21. http://dx.doi.org/10.1587/transcom.e93.b.2012.

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37

Aráuz, Julio, and Alberto Sánchez. "Self-organized Clustering for Improved Interference Mitigation in White Spaces." Journal of Telecommunications and Information Technology, no. 2 (June 30, 2017): 38–48. http://dx.doi.org/10.26636/jtit.2017.110517.

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In this paper a collaborative coexistence mechanism for white space base stations is proposed. We look at the case where these base stations operate in geographical areas where the density of used TV channels is such that only one channel is left for broadband access. We show how with cooperative closed loop control and a clustering strategy, it is possible to find feasible power assignments that provide a flexible and stable coverage solution. The framework under which we study our proposal is based on the IEEE 802.22 standard, which provides white space guidelines for applications in broadband access or machine-to-machine communications. We propose and evaluate a self-organized, collaborative power control and design strategy to enable effective coexistence of base stations under extreme bandwidth constraints. Finally, we also portray how proposed approach positively compares against others from different wireless access technologies.

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Kaur, Supreet, and Vijay Kumar Joshi. "A hybrid soft computing-based clustering protocol for wireless sensor networks." International Journal of Modern Physics B 33, no. 30 (December 10, 2019): 1950356. http://dx.doi.org/10.1142/s0217979219503569.

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In this paper, an inter-cluster data aggregation based on General Self-Organized Tree-based Energy Balance (GSTEB) routing protocol has been improved by proposing energy efficient protocol under hybrid soft computing. First, finest cluster heads are elected by using enhanced ant colony optimization (ACO) method. After that, information which has been gathered by cluster heads is sent to sink node by applying hybrid soft computing (i.e., hybridization of glow swarm and ACOs). Experimental analysis shows that network lifetime has been improved according to the proposed procedure in contrast with already available procedures.

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Sahoo, Prasan, Hiren Thakkar, and I.-Shyan Hwang. "Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks." Sensors 17, no. 12 (December 19, 2017): 2945. http://dx.doi.org/10.3390/s17122945.

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40

Singh, Gurpreet, Amanpreet Kaur, Aashdeep Singh, and Rohan Gupta. "Ant Based Zonal Routing in Mobile Adhoc Networks." International Journal of Engineering & Technology 7, no. 3.1 (August 4, 2018): 46. http://dx.doi.org/10.14419/ijet.v7i3.1.16795.

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Mobile Ad hoc network (MANET) is a collection of moving wireless nodes which form a temporary network topology without using any pre-existing network infrastructure. One of the challenges in MANET is to identify a path between the source and the destination nodes. MANET is highly deployable, self-organizing, autonomous and self-configuring network with the ability of rapid deployment. Nodes movement imposes high challenges to routing in MANET due to dynamically changing of topologies, low transmission power and asymmetric links. So well-organized routing is very critical task due to highly dynamic environment. Route instability occurs due to node mobility and leads to frequent change in topologies; therefore routing becomes one of the core issues. Many researchers are working on the expansion of routing protocols in MANET.

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Zhu, Li, and Lan Bai. "Network Routing Mechanism Simulation Research Based on VANETs." Applied Mechanics and Materials 651-653 (September 2014): 1868–74. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.1868.

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VANETs is a rapid developed wireless mobile MANETs network with special challenge nature. It is a distributed and self-organized communication network based on moving vehicle. This network has characteristics like limited bandwidth, strong mobility, strong dynamic network topology, limited node degrees freedom, equipment capacity constraints and weak physical security. These characteristics usually make typical routing protocol in mobile MANET show a low efficiency in mobile VANETs, even fail. MANET routing algorithm is roughly divided into two categories, namely table driven routing protocol and on-demand routing protocol. It is due to the particularity of driving cars on the road. So how to improve network routing protocol in the performance is now a challenging problem. The purpose of this article studies network routing mechanism based on wireless vehicular networks simulation method. On the basis of analyzing the performance of typical routing protocols in MANET, such as DSDV, AODV and DSR, the improved scheme of AODV on-demand routing algorithm is put forward.

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Byun, Heejung, and Junglok Yu. "Self-organized node coordination scheme based on a biological inter-cell signaling system for wireless sensor networks." Journal of High Speed Networks 19, no. 2 (2013): 147–54. http://dx.doi.org/10.3233/jhs-130469.

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Asha, A., and C. Arun. "Fuzzy based Distributed Self-Organized Secured G-Cast Routing Protocol for Energy-Efficient Heterogeneous Wireless Sensor Networks." Asian Journal of Research in Social Sciences and Humanities 7, no. 3 (2017): 985. http://dx.doi.org/10.5958/2249-7315.2017.00222.2.

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Asha, G., and R. Santhosh. "Soft computing and trust-based self-organized hierarchical energy balance routing protocol (TSHEB) in wireless sensor networks." Soft Computing 23, no. 8 (January 2, 2019): 2537–43. http://dx.doi.org/10.1007/s00500-018-03704-7.

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Sabet, Maryam, and Hamidreza Naji. "An energy efficient multi-level route-aware clustering algorithm for wireless sensor networks: A self-organized approach." Computers & Electrical Engineering 56 (November 2016): 399–417. http://dx.doi.org/10.1016/j.compeleceng.2016.07.009.

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Núñez-Martínez, José, Jorge Baranda, and Josep Mangues-Bafalluy. "Experimental evaluation of self-organized backpressure routing in a wireless mesh backhaul of small cells." Ad Hoc Networks 24 (January 2015): 103–14. http://dx.doi.org/10.1016/j.adhoc.2014.07.021.

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Zhang, Ya, and Fang Han. "Embedded Spectrum Sensor Network Architecture and Transmission Medium Test Based on TCP/IP." International Journal of Online Engineering (iJOE) 12, no. 05 (May 26, 2016): 38. http://dx.doi.org/10.3991/ijoe.v12i05.5734.

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Electromagnetic spectrum monitoring that fully covers spectrum resources guarantees the orderly use of key technologies. However, existing monitoring equipment and methods cannot satisfy the increasing demand. A feasible solution for this problem is a wireless sensor network that is developed using a wireless self-organized network technology for a new type of distributed information system. For the wireless spectrum-monitoring network used by software, this study analyzes the operating system and hardware platform and then tests the physical transport layer under different transmission rates. Factors that may affect transmission performance are also investigated. A two-layer network model is eventually used based on the network to adapt to the requirements and the minimum transmission rate. The first layer uses cable, wideband code-division multiple access (CDMA), and time-division synchronous CDMA; the second layer network uses Wi-Fi/cable. This two-layer network model combines two heterogeneous networks, thereby enabling perception among nodes and gateway nodes. The management center can smooth the data transmission process. To perform several tasks simultaneously, we design our own two layers at the application layer protocol, namely, transmission protocol and data. The two-stage ad-hoc network process, the working principle, and the implementation method of each network application layer module are analyzed. The new spectrum sensor network structure exhibits low power consumption, low cost, as well as distributed and self-organization characteristics. It can guarantee the safety of data transmission with a good transmission rate.

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Srikanth, N., and T. Shankar. "Comparison of self-organized tree hierarchy MAC protocol and PP-MAC for energy consideration in wireless sensor networks." Materials Today: Proceedings 33 (2020): 4756–63. http://dx.doi.org/10.1016/j.matpr.2020.08.359.

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Hong, Zhen, Xiaoman Pan, Ping Chen, Xianchuang Su, Ning Wang, and Wenqi Lu. "A Topology Control with Energy Balance in Underwater Wireless Sensor Networks for IoT-Based Application." Sensors 18, no. 7 (July 16, 2018): 2306. http://dx.doi.org/10.3390/s18072306.

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As part of the IoT-based application, underwater wireless sensor networks (UWSN), which are typically self-organized heterogeneous wireless network, are one of the research hot-spots using various sensors in marine exploration and water environment monitoring application fields, recently. Due to the serious attenuation of radio in water, acoustic or hybrid communication is a usual way for transmitting information among nodes, which dissipates much more energy to prevent the network failure and guarantee the quality of service (QoS). To address this issue, a topology control with energy balance, namely TCEB, is proposed for UWSN to overcome time-delay and other interference, as well as make the entire network load balance. With the given underwater network model and its specialized energy consumption model, we introduce the non-cooperative-game-based scheme to select the nodes with better performance as the cluster-heads. Afterwards, the intra-cluster and inter-cluster topology construction are, respectively, to form the effective communication links of the intra-cluster and inter-cluster, which aim to build energy-efficient topology to reduce energy consumption. With the demonstration of the simulation, the results show the proposed TCEB has better performance on energy-efficiency and throughput than three other representative algorithms in complex underwater environments.

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Semko, Viktor, and Oleksiy Semko. "METHOD OF MANAGING ROUTING OF DATA FLOWS IN HETEROGENEOUS NETWORKS UNDER CONFLICT, UNCERTAINTY AND DISTURBANCE." Cybersecurity: Education, Science, Technique 3, no. 11 (2021): 73–84. http://dx.doi.org/10.28925/2663-4023.2021.11.7384.

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This paper proposes a method of synthesis of data transmission routes in conflicting heterogeneous self-organized wireless data networks under external and internal influences. In this case, routing is understood as the process of determining in a data transmission network one or a set of routes (pathspaths) , that are optimal within the selected criteria between a given pair or set of network nodes. Thus, a route is a sequence of network nodes and data transmission paths that connect a pair of network nodes for communication. The method is based on a mathematical model of the data network operation in a virtual multidimensional parameter space. The model of operation is based on a graph-model of information interaction of network nodes in the process of data transmission between receptor nodes and acceptors in the transmission of data streams. Based on the problem statement, the price function is formally defined as the value of the virtual distance between the nodes of a heterogeneous data network. In contrast to the Floyd-Warshall and Dijkstra algorithms, the synthesis of the data transmission route takes into account both the load of the computing environment of network nodes and the state of information interaction channels of network nodes, as well as possible changes in network parameters during data transmission. The data transmission network is self-organized, has no dedicated nodes, which ensures its reliability under external and internal influences, conflicts in data transmission, as well as variable topology. The proposed method for synthesizing data transmission routes when controlling the routing of data flows in heterogeneous networks is focused on the possibility of implementing the basic model of open systems interaction within the framework of existing protocols - the OSI model, which is a reference network model for communications and the development of network protocols.

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