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Journal articles on the topic 'Cognitive mobile ad-hoc network'

Author: Grafiati

Published: 7 June 2025

Last updated: 16 July 2025

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1

Afridi, Muhammad Ishaq. "Cognition in a Cognitive Routing System for Mobile Ad-Hoc Network through Leaning Automata and Neural Network." Applied Mechanics and Materials 421 (September 2013): 694–700. http://dx.doi.org/10.4028/www.scientific.net/amm.421.694.

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A cognitive routing system intelligently selects one protocol at a time for specific routing conditions and environment in MANET. Cognition or self-learning can be achieved in a cognitive routing system for mobile ad-hoc network (MANET) through a learning system like learning automata or neural networks. This article covers the application of learning automata and neural network to achieve cognition in MANET routing system. Mobile Ad-hoc networks are dynamic in nature and lack any fixed infrastructure, so the implementation of cognition enhances the performance of overall routing system in these networks. In learning automata the process of learning is different from reasoning or decision making. Learning automata require little knowledge to take decisions. Neural network can be improved by increasing the number of neurons and changing parameters. Self-training enhance neural network performance and it select suitable protocol for a given network environment. Cognition in MANET is either based upon learning automata as in some wireless sensor networks or specialized cognitive neural networks like Elman network. Learning automata do not follow predetermine rules and has the ability to learn and evolve. The interaction of learning automata with the MANET environment results in the evolution of cognition system.

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Palanisamy, Ramesh, Senthil Jayapal, Anand M, and Jeelani Basha. "ENHANCED HYBRID COGNITIVE RADIO AD HOC NETWORKS (CRAHNs) FOR MOBILE NETWORK." International Journal of Computer Science and Mobile Computing 11, no. 11 (2022): 237–46. http://dx.doi.org/10.47760/ijcsmc.2022.v11i11.020.

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In sensor networks, a very crucial aspect of the maintenance of the communications of secure data is the data, which is the most difficult of all tasks. The sensor network consists of hierarchical elements like the Base Station (BS), the Cluster Head (CH) and the Sensor Nodes (SNs), and this will have three different keys, which are the public and private, the cluster and the master keys. Through the opportunistic use of the currently available wireless spectrum, cognitive radio (CR) technology is intended to address the issues in wireless networks brought on by the limited amount of range accessible and the inefficient use of spectrum. With the inherent capabilities of cognitive radio, CR networks will offer the most advanced spectrum-aware communication paradigm in wireless communications. However, the significant spectral fluctuation and various quality-of-service (QoS) requirements faced by CR networks provide unique difficulties. The distributed multihop design, the dynamic network topology, and the time- and location-varying spectrum availability are essential differentiating elements in cognitive radio ad hoc networks (CRAHNs).

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3

Omar, Shereen, Osama El Ghandour, and Ahmed M. Abd El-Haleem. "Multipath Activity Based Routing Protocol for Mobile ‎Cognitive Radio Ad Hoc Networks." Wireless Communications and Mobile Computing 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/5380525.

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Cognitive radio networks improve spectrum utilization by ‎sharing licensed spectrum with cognitive radio devices. In ‎cognitive radio ad hoc networks the routing protocol is one ‎of the most challenging tasks due to the changes in ‎frequency spectrum and the interrupted connectivity ‎caused by the primary user activity. In this paper, a multi‎path activity based routing protocol for cognitive radio ‎network (MACNRP) is proposed. The protocol utilizes ‎channel availability and creates multiple node-disjoint ‎routes between the source and destination nodes. The ‎proposed protocol is compared with D2CARP and FTCRP ‎protocols. The performance evaluation is conducted ‎through mathematical analysis and using OPNET ‎simulation. The performance of the proposed protocol ‎achieves an increase in network throughput; besides it ‎decreases the probability of route failure due to node ‎mobility and primary user activity. We have found that the ‎MACNRP scheme results in 50% to 75% reduction in ‎blocking probability and 33% to 78% improvement in ‎network throughput, with a reasonable additional routing ‎overhead and average packet delay. Due to the successful ‎reduction of collision between primary users and ‎cognitive users, the MACNRP scheme results in decreasing ‎the path failure rate by 50% to 87%.‎

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Qu, Yuben, Chao Dong, Song Guo, Shaojie Tang, Hai Wang, and Chang Tian. "Spectrum-Aware Network Coded Multicast in Mobile Cognitive Radio Ad Hoc Networks." IEEE Transactions on Vehicular Technology 66, no. 6 (2017): 5340–50. http://dx.doi.org/10.1109/tvt.2016.2621007.

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5

Sun, Yan, Jingwen Bai, Hao Zhang, Roujia Sun, and Chris Phillips. "A Mobility-Based Routing Protocol for CR Enabled Mobile Ad Hoc Networks." International Journal of Wireless Networks and Broadband Technologies 4, no. 1 (2015): 81–104. http://dx.doi.org/10.4018/ijwnbt.2015010106.

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With the fast development of hardware and chipset functionality and capability, smart devices equipped with advanced technologies, such as Cognitive Radio (CR) will offer promising opportunities for mobile network. The authors in this work design a mobility based routing protocol (CRMBR) which operates in CR enabled Mobile Ad hoc Networks (MANETs). The adopted cross layer structure transfers the cognitive sensing data, such as channel quality and available bandwidth, from Physical layer up to MAC/Network layers periodically. Network layer uses such information for executing route selection algorithm while MAC layer runs the sub-channel scheduling algorithm based on CR data before each transmission. CRMBR further employs an advanced acknowledgment scheme in MAC layer for sub-channel selection to reduce the control overhead while forwarding data in MANETs. The performance of CRMBR is investigated via simulations on OpNET platform and the results confirm its favorable operation within CR MANET environments compared to two classic routing protocols in Ad hot networks: AODV and DSR.

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Joshi, Gyanendra Prasad, Seung Yeob Nam, Chang-Su Kim, and Sung Won Kim. "A Cross-Layer-Based Routing Protocol for Ad Hoc Cognitive Radio Networks." International Journal of Distributed Sensor Networks 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/938191.

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This paper proposes a cross-layer-based routing protocol for mobile ad hoc cognitive radio networks. The routing layer receives the spectrum-availability-related information from the medium access control layer and selects the next hop node on the route according to the spectrum information. This paper examines the expectation of channel switching in a range of scenarios and proposes a novel route selection method to mitigate the frequent channel switching. The proposed protocol distributes the routing overheads among secondary users in the network and prolongs the network lifetime. An extensive simulation was performed to evaluate the proposed approach, and the results showed that the proposed protocol extends the network lifetime and maintains a higher data delivery ratio.

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Cacciapuoti, Angela Sara, Marcello Caleffi, and Luigi Paura. "Reactive routing for mobile cognitive radio ad hoc networks." Ad Hoc Networks 10, no. 5 (2012): 803–15. http://dx.doi.org/10.1016/j.adhoc.2011.04.004.

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8

Rajalakshmi, D., and K. Meena. "A Hybrid Intrusion Detection System for Mobile Adhoc Networks using FBID Protocol." Scalable Computing: Practice and Experience 21, no. 1 (2020): 137–45. http://dx.doi.org/10.12694/scpe.v21i1.1642.

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The security in a mobile ad hoc networks is more vulnerable and susceptible to the environment, because in this network no centralized environment for monitoring individual nodes activity during communication. The intruders are hacked the networks either locally and globally. Now a day’s mobile ad hoc network is an emerging area of research due to its unique characteristics. It’s more vulnerable to detect malicious activities, and error prone in nature due to their dynamic topology configuration. Based on their difficulties of intrusion detection system, in this paper proposed a novel approach for mobile ad hoc network is Fuzzy Based Intrusion Detection (FBID) protocol, to identify, analyze and detect a malicious node in different circumstances. This protocol it improves the efficiency of the system and does not degrade the system performance in real time.This FBID system is more efficient and the performance is compared with AODV, Fuzzy Cognitive Mapping with the following performance metrics: Throughput, Packet Delivery Ratio, Packets Dropped, Routing overhead, Propagation delay and shortest path for delivering packets from one node to another node. The System is robust. It produces the crisp output to the benefit of end users. It provides an integrated solution capable of detecting the majority of security attacks occurring in MANETs.

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9

Neeraj Verma, Pro. (Dr.) Awakash Mishra. "Considering Performance Issues in Ad Hoc Networking : A Comprehensive Study." Tuijin Jishu/Journal of Propulsion Technology 44, no. 4 (2023): 5514–25. http://dx.doi.org/10.52783/tjjpt.v44.i4.1930.

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Ad hoc networks have emerged as a versatile and dynamic communication paradigm with applications spanning from mobile devices and sensor networks to emergency response and military operations. However, their inherent decentralized and self-organizing nature gives rise to a myriad of performance challenges that must be comprehensively addressed to ensure reliable and efficient communication. This paper presents a comprehensive study of performance issues in ad hoc networking, aiming to provide a holistic understanding of the various factors impacting network performance. The study begins by examining the fundamental characteristics of ad hoc networks, highlighting their unique advantages and challenges. We delve into critical performance metrics such as throughput, latency, scalability, and energy efficiency, dissecting the factors that influence each of these metrics in ad hoc environments. The role of routing protocols, MAC layer design, and network topologies in shaping network performance is thoroughly analyzed. Furthermore, this study explores the impact of mobility patterns, traffic models, and interference on ad hoc network performance. It delves into the challenges posed by dynamic network topologies, node failures, and the need for adaptive mechanisms to maintain robust connectivity. Quality of service (QoS) considerations and their implications on performance are also discussed in detail. To provide a comprehensive view, we survey state-of-the-art solutions and techniques proposed in the literature to mitigate performance issues in ad hoc networks. These include adaptive routing algorithms, cross-layer optimization approaches, and novel communication paradigms like cognitive radio networks. Finally, we present a roadmap for future research directions in the field of ad hoc networking performance optimization. The goal is to inspire further investigation and innovation in addressing the evolving challenges faced by ad hoc networks, making them more reliable, efficient, and adaptable for a wide range of applications.

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10

Sangeetha, R., and S. NandhaKumar. "Detach the Intricate Network for Analyse Broadcast Protocols in AD HOC Network Using Random Channel Usability." International Journal of Advance Research and Innovation 3, no. 2 (2015): 44–48. http://dx.doi.org/10.51976/ijari.321511.

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Cognitive radio (CR) is one of today’s up-and-coming technologies. It facilitates communication because it creates greater efficiencies in mobile networks. CR allows unlicensed (secondary) users to exploit, in an opportunistic or ad hoc manner, the radio communications spectrum allocated to licensed (primary) users. CR is a promising potential solution to the problems caused by inflexibility in spectrum allocation policy, with attendant spectrum shortage. Due to facility in cognitive radio (CR) ad hoc networks, many unlicensed users may acquire different available channels depending on the locations and traffic of licensed users for efficient broadcast operation. By this strategy, proposed work enables the novel unified analytical model to estimate the efficiency of several protocols. First step is decompose the intricate network into a few simpler networks so that the successful broadcast ratio of these simpler networks is straightforward and also obtain successful broadcast ratio of the overall network can be acquired. These systematic models efficiently analyze all protocol without considering their design and specification.

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11

Lee, Jae-Joon, and Jaesung Lim. "Cognitive routing for multi-hop mobile cognitive radio ad hoc networks." Journal of Communications and Networks 16, no. 2 (2014): 155–61. http://dx.doi.org/10.1109/jcn.2014.000026.

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12

Prasenjit, Mahato* Krishna Satya Varma Mantena. "DESIGNING INTELLIGENT TRANSPORTATION SYSTEM FOR COGNITIVE RADIO MOBILE AD- HOC NETWORKS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 11 (2016): 518–22. https://doi.org/10.5281/zenodo.168437.

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Time and the Constraint are both typically interrelated and lead us to the next level high technological revolution journey where we analyses the Human Automation instead of System Automation. Technological in the View Point cognitive science Information technology will have to make high level of demanding journey; in that aspect we consider the best of the technical revolution in the Social media where we share the thoughts , informational to many more . In cognitive radio networks (CRNs), secondary users (SUs) can flexibly access primary users' (PUs') idle spectrum bands, but such spectrum opportunities are dynamic due to PUs' uncertain activity patterns. In a multi hop CRN consisting of SUs as relays; such spectrum dynamics will further cause the invalidity of predetermined routes. In this paper, we investigate spectrum-mobility-incurred route-switching problems in both spatial and frequency domains for CRNs, where spatial switching determines which relays and links should be reselected and frequency switching decides which channels ought to be reassigned to the spatial routes. The proposed route-switching scheme not only avoids conflicts with PUs but also mitigates spectrum congestion.

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13

Revanth, Banala, and M. Sakthivel. "Delay-Minimized Routing Protocol for Mobile Cognitive Ad-Hoc Networks." International Journal of Computer Sciences and Engineering 6, no. 7 (2018): 991–96. http://dx.doi.org/10.26438/ijcse/v6i7.991996.

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14

Tsukamoto, Kazuya, Shun Koba, Masato Tsuru, and Yuji Oie. "Cognitive Radio-Aware Transport Protocol for Mobile Ad Hoc Networks." IEEE Transactions on Mobile Computing 14, no. 2 (2015): 288–301. http://dx.doi.org/10.1109/tmc.2014.2320267.

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15

Chauhan, Alok Singh. "Design an Improved Trust-based Quality of Service AwareRouting in Cognitive Mobile Ad-Hoc Network." Wasit Journal of Computer and Mathematics Science 2, no. 4 (2023): 38–46. http://dx.doi.org/10.31185/wjcms.218.

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Mobile ad hoc networks (MANETs) are wireless networks that can be configured at will. It has no infrastructure and centralized control, so it is only suitable for provisional communications. In a dynamically topological and resource-constrained network, ensuring QoS and security is challenging. MANETs are dynamic networks, so navigating them can be challenging and more susceptible to attacks. MANET requires significant memory, speed, and transmission bandwidth for conventional security measures like cryptographic techniques. Consequently, these methods are unsuitable for identifying malicious behaviour or self-centered nodes. Nodes that are malicious, selfish, or malfunctioning can be identified based on the trust method, which calculates how much trust exists between them. A trust-based QOS-aware routing protocol is proposed in this paper to calculate trust in MANET (I-TQAR). The tree important performance metrics are considered for result validation such as delay, throughput and packet delivery ratio (PDR). I-TQAR offers significantly improved performance in all areas compared to the existing TQR and TQOR protocols.

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16

Naguib, Mohamed, Yahya Mohasseb, Hisham Dahshan, and Ahmed Elghandour. "An Enhanced Transport Layer Protocol for Cognitive Mobile Ad Hoc Networks." International Conference on Electrical Engineering 11, no. 11 (2018): 1–13. http://dx.doi.org/10.21608/iceeng.2018.30160.

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17

Chowdhury, K. R., and M. D. Felice. "Search: A routing protocol for mobile cognitive radio ad-hoc networks." Computer Communications 32, no. 18 (2009): 1983–97. http://dx.doi.org/10.1016/j.comcom.2009.06.011.

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18

Wu, Chien-Min, Yen-Chun Kao, and Kai-Fu Chang. "A Multichannel MAC Protocol for IoT-enabled Cognitive Radio Ad Hoc Networks." Advances in Technology Innovation 5, no. 1 (2020): 45–55. http://dx.doi.org/10.46604/aiti.2020.3946.

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Cognitive radios have the ability to dynamically sense and access the wireless spectrum, and this ability is a key factor in successfully building Internet-of-Things (IoT)-enabled mobile ad hoc networks. This paper proposes a contention-free token-based multichannel MAC protocol for IoT-enabled Cognitive Radio Ad Hoc Networks (CRAHNs). In this, secondary users of CRAHNs detect activity on the wireless spectrum and then access idle channels licensed by primary users. CRAHNs are divided into clusters, and the channel to use for transmission is determined dynamically from the probability of finding idle primary-user channels. The token-based MAC window size is adaptive, with adjustment according to actual traffic, which reduces both end-to-end MAC contention delay and energy consumption. High throughput and spatial reuse of channels can also be achieved using a dynamic control channel and dynamic schemes for contention windows. We performed extensive simulations to verify that the proposed method can achieve better performance in mobile CRAHNs than other MAC schemes can.

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Raj, K. Shashi. "Interference resilient stochastic prediction based dynamic resource allocation model for cognitive MANETs." Indian Journal of Science and Technology 13, no. 41 (2020): 4332–50. http://dx.doi.org/10.17485/ijst/v13i41.687.

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Background/Objectives: Being dynamic in nature, Mobile Ad-hoc Network (MANET) requires robust resource allocation strategy that can ensure both optimal transmission reliability and resource efficiency to meet Quality of Service (QoS) demands. The objective of this research is to address interference resilience requirement in MANETs which is must due to greedy nature of nodes especially when accessing resource or bandwidth and develop a highly robust stochastic prediction based resource allocation strategy. Methods: The proposed Interference Resilient Stochastic Prediction based Dynamic Resource Allocation model for Cognitive MANET (ISP-DRACM) intends to enable optimal resource allocation under interweave and underlay network setup with instantaneous as well as average interference conditions. It employs a joint power management and resource allocation strategy where it intends to maximize the weighted sum-rate of the secondary users under certain defined conditions like average power and stochastic interference level. Findings/Novelty: Inculcating resource allocation problem as controlled Markov Decision Process using Hidden Markov Model (HMM) and Lagrange relaxation, our proposed model achieves better resource allocation under limited noise or interference condition and hence achieves both costeffectiveness as well as QoS provision. This method has exhibited satisfactory performance towards spectrum allocation to the secondary users without imposing any significant interference for both interweave as well as underlay Cognitive Radio setup. Keywords: Cognitive mobile ad-hoc network; stochastic prediction; interference resilience; channel state information; dynamic resource allocation; underlay and overlay cognitive MANET

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K, Shashi Raj, K. Siddesh G, Mallikarjunaswamy S, and Vivek Raj K. "Interference resilient stochastic prediction based dynamic resource allocation model for cognitive MANETs." Indian Journal of Science and Technology 13, no. 41 (2020): 4332–50. https://doi.org/10.17485/IJST/v13i41.687.

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Abstract <strong>Background/Objectives</strong>: Being dynamic in nature, Mobile Ad-hoc Network (MANET) requires robust resource allocation strategy that can ensure both optimal transmission reliability and resource efficiency to meet Quality of Service (QoS) demands. The objective of this research is to address interference resilience requirement in MANETs which is must due to greedy nature of nodes especially when accessing resource or bandwidth and develop a highly robust stochastic prediction based resource allocation strategy. <strong>Methods</strong>: The proposed Interference Resilient Stochastic Prediction based Dynamic Resource Allocation model for Cognitive MANET (ISP-DRACM) intends to enable optimal resource allocation under interweave and underlay network setup with instantaneous as well as average interference conditions. It employs a joint power management and resource allocation strategy where it intends to maximize the weighted sum-rate of the secondary users under certain defined conditions like average power and stochastic interference level. <strong>Findings/Novelty</strong>: Inculcating resource allocation problem as controlled Markov Decision Process using Hidden Markov Model (HMM) and Lagrange relaxation, our proposed model achieves better resource allocation under limited noise or interference condition and hence achieves both costeffectiveness as well as QoS provision. This method has exhibited satisfactory performance towards spectrum allocation to the secondary users without imposing any significant interference for both interweave as well as underlay Cognitive Radio setup.<strong>Keywords</strong>: Cognitive mobile ad-hoc network; stochastic prediction; interference resilience; channel state information; dynamic resource allocation; underlay and overlay cognitive MANET 

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21

DUAN, J., and Y. LI. "An Optimal Spectrum Handoff Scheme for Cognitive Radio Mobile Ad Hoc Networks." Advances in Electrical and Computer Engineering 11, no. 3 (2011): 11–16. http://dx.doi.org/10.4316/aece.2011.03002.

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22

Jin, Xiaocong, Rui Zhang, Jingchao Sun, and Yanchao Zhang. "TIGHT: A Geographic Routing Protocol for Cognitive Radio Mobile Ad Hoc Networks." IEEE Transactions on Wireless Communications 13, no. 8 (2014): 4670–81. http://dx.doi.org/10.1109/twc.2014.2320950.

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23

Zhang, Jinbei, Yixuan Li, Zhuotao Liu, Fan Wu, Feng Yang, and Xinbing Wang. "On Multicast Capacity and Delay in Cognitive Radio Mobile Ad Hoc Networks." IEEE Transactions on Wireless Communications 14, no. 10 (2015): 5274–86. http://dx.doi.org/10.1109/twc.2015.2435734.

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24

Tang, H., F. R. Yu, M. Huang, and Z. Li. "Distributed consensus-based security mechanisms in cognitive radio mobile ad hoc networks." IET Communications 6, no. 8 (2012): 974. http://dx.doi.org/10.1049/iet-com.2010.0553.

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25

M. Mohamed Musthafa. "Improving Manets Qos Services using Dynamic Topology and Spectrum Sharing in Cognitive Radio-Manets." Journal of Information Systems Engineering and Management 10, no. 31s (2025): 322–34. https://doi.org/10.52783/jisem.v10i31s.5051.

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MANETs is the best wireless network and helps for unlimited mobility without depending on other infrastructure. The mobile network is a challenging task for maintaining quality of service, protective routing and dependable communication. The purpose model with QOS routing is to select a secure optimal route from starting to ending and have to satisfy two or more QOS constrains. In MANETs the Cognitive Radio technology is the top layer in mobile ad hoc networks. The role of CR is to control the topology in Cognitive Radio-MANETs. In existing system there is no fixed topology because of the interference, multi path propagation mobility. So, in proposed system to do network function properly we enhanced the efficient scheduling techniques and topology with ant colony optimization techniques. The QOS service is processed in heterogeneous networks. The algorithm such as cognitive radio spectrum sharing algorithm, and Hungarian algorithm are used to evaluate the data rate and spectrum utilization. The experimental results are performance detect spectrum utilization and increase the data rates. The simulation result is implemented in NS-2 shows better performance in throughput and data rates.

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Biswas, Rajorshi, and Jie Wu. "Minimizing The Number of Channel Switches of Mobile Users in Cognitive Radio Ad-Hoc Networks." Journal of Sensor and Actuator Networks 9, no. 2 (2020): 23. http://dx.doi.org/10.3390/jsan9020023.

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Cognitive radio (CR) technology is envisioned to use wireless spectrum opportunistically when the primary user (PU) is not using it. In cognitive radio ad-hoc networks (CRAHNs), the mobile users form a distributed multi-hop network using the unused spectrum. The qualities of the channels are different in different locations. When a user moves from one place to another, it needs to switch the channel to maintain the quality-of-service (QoS) required by different applications. The QoS of a channel depends on the amount of usage. A user can select the channels that meet the QoS requirement during its movement. In this paper, we study the mobility patterns of users, predict their next locations and probabilities to move there based on its history. We extract the mobility patterns from each user’s location history and match the recent trajectory with the patterns to find future locations. We construct a spectrum database using Wi-Fi access point location data and the free space path loss formula. We propose a machine learning-based mechanism to predict spectrum status of some missing locations in the spectrum database. We formulate a problem to select the current channel in order to minimize the total number of channel switches during a certain number of next moves of a user. We conduct an extensive simulation combining real and synthetic datasets to support our model.

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Kathiriya, Bhaveshkumar, and Divyesh Keraliya. "An Efficient Hybrid Analysis to Improve Data Rate Signal Transmission in Cognitive Radio Networks Using Multi- Hop." International Journal of Electrical and Electronics Research 11, no. 3 (2023): 682–88. http://dx.doi.org/10.37391/ijeer.110307.

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Spectrum scarcity problems can be resolved with the emerging communiqué technologies known as cognitive radio (CR). Cognitive radio networks (CRNs) will give mobile users greater bandwidth via wirelessly heterogeneity design and dynamic spectrum acquisition methods. The Cognitive Radio Mobile Ad-Hoc Network (CR-MANET) idea of Adaptive Routing a new network paradigm may be realized by using the functions of spectrum management to overcome such difficulties. Secondary users (SUs) have the freedom to opportunistically explore and make use of the open spaces on licensed channels. When a primary user (PU) interferes with a licensed channel, this forces the SU to leave it and switch to an open channel. Because of the constant channel switching those results, SUs degrades as a result. In this result recommends a number of channels, number of hop CRN that uses a fuzzy decision-making system that is genetically optimized for channel selection, channel switching, and spectrum allocation. According to study, the suggested architecture achieves higher PDR, throughput, latency, and transmission time than fuzzy and genetic algorithms. Through simulations the result demonstrates significant improvements in data rate performance, making it a promising solution for enhancing communication efficiency in cognitive radio networks.

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Tran, Thong Nhat, Toan-Van Nguyen, and Beongku An. "An Efficient Connected Dominating Set Clustering Based Routing Protocol with Dynamic Channel Selection in Cognitive Mobile Ad Hoc Networks." Electronics 8, no. 11 (2019): 1332. http://dx.doi.org/10.3390/electronics8111332.

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In mobile ad-hoc networks (MANETs), nodes are mobility naturally which renders a great challenge in topology controls. Connected dominating set (CDS) has been considered as an efficient solution to solve such a problem by constructing a virtual backbone network to achieve the scalability and efficiency of wireless networks. In this paper, we propose an efficient connected dominating set clustering based routing protocol with dynamic channel selection (CRD) in multi-channel cognitive radio MANETs to obtain high packet delivery ratio (PDR), low control overheads, low delay and low energy consumption when node is moving in high speed. Moreover, CRD protocol can apply for Vehicular Ad Hoc Network, IoT and 5G. The proposed CRD protocol includes clustering and routing phases under multi-channel cognitive radio approach. In the clustering phase, we propose CDS selection, CDS size reduction and CDS based clustering algorithms to formulate clusters and provide a set of intermediate nodes which is latter used as a route searching space for the routing phase. In the routing phase, a sending channel based focus region selection (CFS) algorithm is adopted dynamically to establish an efficient route from a set of intermediate nodes that avoids the affected region of a primary user. The CRD routing protocol is then implemented in environmental conditions close to reality (OMNET++ platform) to demonstrate its superiority over the conventional AODV protocol in terms of PDR, control overhead, delay and energy consumption.

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29

Ning, Guoqin, Kaushik R. Chowdhury, Jiaqi Duan, and Prusayon Nintanavongsa. "Licensed user activity estimation and track in mobile cognitive radio ad hoc networks." Computers & Electrical Engineering 39, no. 6 (2013): 1705–16. http://dx.doi.org/10.1016/j.compeleceng.2012.10.007.

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30

Indhumathi, L., and R. Vadivel. "Adaptive Delay Tolerant Routing Protocol (ADTRP) for Cognitive Radio Mobile Ad Hoc Networks." International Journal of Computer Applications 128, no. 6 (2015): 19–24. http://dx.doi.org/10.5120/ijca2015906570.

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31

Lu, Yuan, and Alexandra Duel-Hallen. "Channel-Aware Spectrum Sensing and Access for Mobile Cognitive Radio Ad Hoc Networks." IEEE Transactions on Vehicular Technology 65, no. 4 (2016): 2471–80. http://dx.doi.org/10.1109/tvt.2015.2421913.

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32

Raza, Anam, Waleed Ejaz, Syed Sohail Ahmed, and Hyung Seok Kim. "Consensus-Based Distributive Cooperative Spectrum Sensing for Mobile Ad Hoc Cognitive Radio Networks." International Journal of Distributed Sensor Networks 9, no. 12 (2013): 450626. http://dx.doi.org/10.1155/2013/450626.

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Guan, Quansheng, F. Richard Yu, Shengming Jiang, and Gang Wei. "Prediction-Based Topology Control and Routing in Cognitive Radio Mobile Ad Hoc Networks." IEEE Transactions on Vehicular Technology 59, no. 9 (2010): 4443–52. http://dx.doi.org/10.1109/tvt.2010.2069105.

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Atakan, Baris, and Ozgur B. Akan. "Biological Foraging-Inspired Communication in Intermittently Connected Mobile Cognitive Radio Ad Hoc Networks." IEEE Transactions on Vehicular Technology 61, no. 6 (2012): 2651–58. http://dx.doi.org/10.1109/tvt.2012.2198928.

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Barve, Sunita S., and Parag Kulkarni. "Multi-Agent Reinforcement Learning Based Opportunistic Routing and Channel Assignment for Mobile Cognitive Radio Ad Hoc Network." Mobile Networks and Applications 19, no. 6 (2014): 720–30. http://dx.doi.org/10.1007/s11036-014-0551-6.

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Oh, Hyukchun, Kyusung Shim, and Beongku An. "ACOQMR : ACO-based QoS Mesh Routing Protocol in Mobile Overlay Cognitive Ad-hoc Networks." Journal of the Institute of Electronics and Information Engineers 57, no. 2 (2020): 49–59. http://dx.doi.org/10.5573/ieie.2020.57.2.49.

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Yu, F., Minyi Huang, and Helen Tang. "Biologically inspired consensus-based spectrum sensing in mobile Ad Hoc networks with cognitive radios." IEEE Network 24, no. 3 (2010): 26–30. http://dx.doi.org/10.1109/mnet.2010.5464224.

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Kim, Jun-Hyeong, Hong-Beom Choi, Dohyung Kim, et al. "Multiple Metrics Based Multi-hop Clustering Technique for Cognitive Radio Mobile Ad Hoc Networks." Journal of Korean Institute of Communications and Information Sciences 44, no. 5 (2019): 879–87. http://dx.doi.org/10.7840/kics.2019.44.5.879.

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Chaudhari, Shilpa Shashikant, and Rajashekhar C. Biradar. "Traffic and mobility aware resource prediction using cognitive agent in mobile ad hoc networks." Journal of Network and Computer Applications 72 (September 2016): 87–103. http://dx.doi.org/10.1016/j.jnca.2016.06.010.

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Preveze, Barbaros. "A Novel Cognitive Method for Throughput Improvement of Mobile Multi-hop Ad Hoc Networks." Wireless Personal Communications 82, no. 1 (2014): 229–43. http://dx.doi.org/10.1007/s11277-014-2205-1.

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Guo, Songtao, Chuangyin Dang, and Xiaofeng Liao. "Distributed resource allocation with fairness for cognitive radios in wireless mobile ad hoc networks." Wireless Networks 17, no. 6 (2011): 1493–512. http://dx.doi.org/10.1007/s11276-011-0360-9.

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Kong, Linghe, Bowen Wang, Xi Chen, et al. "Joint adaptation framework in mobile ad hoc networks: A control theory perspective." Neurocomputing 270 (December 2017): 66–74. http://dx.doi.org/10.1016/j.neucom.2016.12.103.

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Kusyk, Janusz, M. Umit Uyar, and Cem Safak Sahin. "Survey on evolutionary computation methods for cybersecurity of mobile ad hoc networks." Evolutionary Intelligence 10, no. 3-4 (2018): 95–117. http://dx.doi.org/10.1007/s12065-018-0154-4.

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Chinnasamy, S., and R. Vadivel. "Energy Efficient Spectrum Aware Channel Sensing Routing Protocol for Cognitive Radio Mobile Ad-Hoc Networks." International Journal of Computer Applications 157, no. 3 (2017): 31–36. http://dx.doi.org/10.5120/ijca2017912649.

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Tang, Feilong, Minyi Guo, Song Guo, and Cheng-Zhong Xu. "Mobility Prediction Based Joint Stable Routing and Channel Assignment for Mobile Ad Hoc Cognitive Networks." IEEE Transactions on Parallel and Distributed Systems 27, no. 3 (2016): 789–802. http://dx.doi.org/10.1109/tpds.2013.216.

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Amiri-Doomari, Soodeh, Ghasem Mirjalily, and Jamshid Abouei. "Stability-based routing, link scheduling and channel assignment in cognitive radio mobile ad-hoc networks." Wireless Networks 25, no. 4 (2018): 2013–26. http://dx.doi.org/10.1007/s11276-018-1793-1.

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Moila, Ramahlapane Lerato, and Mthulisi Velempini. "A Model to Improve the Effectiveness and Energy Consumption to Address the Routing Problem for Cognitive Radio Ad Hoc Networks by Utilizing an Optimized Cuckoo Search Algorithm." Energies 14, no. 12 (2021): 3464. http://dx.doi.org/10.3390/en14123464.

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Abstract:

A cognitive radio ad hoc network (CRAHN) is a mobile network that can communicate without any form of centralized infrastructure. The nodes can learn about the environment and make routing decisions. Furthermore, distributed computing, spectrum mobility, and the Internet of Things have created large data sets, which require more spectrum for data transmission. Unfortunately, the spectrum is a scarce resource that underutilized by licensed users, while unlicensed users are overcrowding the free spectrum. The CRAHNs technology has emerged as a promising solution to the underutilization of the spectrum. The focus of this study is to improve the effectiveness and energy consumption of routing in order to address the routing problem of CRAHNs through the implementation of the optimized cuckoo search algorithm. In CRAHNs, the node and spectrum mobility cause some frequent link breakages within the network, which degrades the performance of the routing protocols. This requires a routing solution to this routing problem. The proposed scheme was implemented in NS2 installed in Linux operating system, with a cognitive radio cognitive network (CRCN) patch. From the experimental results, we observed that the proposed OCS-AODV scheme outperformed CS-DSDV and ACO-AODV schemes. It obtained at least 3.87% packet delivery ratio and 2.56% and lower packets lost. The scheme enabled the mobile nodes to adjust accordingly to minimize energy consumption. If not busy, they switch to an idle state to save battery power.

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Jalil Piran, Mohammad, Amjad Ali, and Doug Young Suh. "Fuzzy-Based Sensor Fusion for Cognitive Radio-Based Vehicular Ad Hoc and Sensor Networks." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/439272.

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In wireless sensor networks, sensor fusion is employed to integrate the acquired data from diverse sensors to provide a unified interpretation. The best and most salient advantage of sensor fusion is to obtain high-level information in both statistical and definitive aspects, which cannot be attained by a single sensor. In this paper, we propose a novel sensor fusion technique based on fuzzy theory for our earlier proposed Cognitive Radio-based Vehicular Ad Hoc and Sensor Networks (CR-VASNET). In the proposed technique, we considered four input sensor readings (antecedents) and one output (consequent). The employed mobile nodes in CR-VASNET are supposed to be equipped with diverse sensors, which cater to our antecedent variables, for example, The Jerk, Collision Intensity, and Temperature and Inclination Degree. Crash_Severity is considered as the consequent variable. The processing and fusion of the diverse sensory signals are carried out by fuzzy logic scenario. Accuracy and reliability of the proposed protocol, demonstrated by the simulation results, introduce it as an applicable system to be employed to reduce the causalities rate of the vehicles’ crashes.

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Al-mahdi, Hassan, and Yasser Fouad. "Design and analysis of routing protocol for cognitive radio ad hoc networks in Heterogeneous Environment." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 341. http://dx.doi.org/10.11591/ijece.v9i1.pp341-351.

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Abstract:

Multi-hop routing protocol in cognitive radio mobile ad hoc networks (CRMANETs) is a critical issue. Furthermore, the routing metric used in multi-hop CRMANETs should reflect the bands availability, the links quality, the PU activities and quality of service (QoS) requirements of SUs. For the best of our knowledge, many of researchers investigated the performance of the different routing protocols in a homogeneous environment only. In this paper, we propose a heterogeneous cognitive radio routing protocol (HCR) operates in heterogeneous environment (i.e. the route from source to destination utilize the licensed and unlicensed spectrum bands). The proposed routing protocol is carefully developed to make a tradeoff between the channel diversity of the routing path along with the CRMANETs throughput. Using simulations, we discuss the performance of the proposed HCR routing protocol and compare it with the AODV routing protocol using a discrete-event simulation which we developed using JAVA platform.

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Amiri-Doomari, Soodeh, Ghasem Mirjalily, and Jamshid Abouei. "Joint load balanced stable routing and communication segment assignment in mobile cognitive radio ad-hoc networks." International Journal of Communication Systems 31, no. 12 (2018): e3710. http://dx.doi.org/10.1002/dac.3710.

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