International Journal of Computer Networks and Applications

Open Access Open Access  Restricted Access Subscription Access

Improved Wolf Prey Inspired Protocol for Routing in Cognitive Radio Ad Hoc Networks


Affiliations
1 Department of Computer Science, VLB Janakiammal College of Arts and Science, Coimbatore, Tamil Nadu, India
2 Department of Information Technology, Bharathiar University, Coimbatore, Tamil Nadu, India
 

Fifth Generation (5G) technology has started providing the brand new facilities to the mobile communication world. With its enhanced performance and scalability, it has attracted many domains. Routing overhead in 5G networks is increased rapidly because of the complexity present in the route discovery process, where optimization in routing. Poor routing becomes a sophisticated and dynamic challenge in the 5G network. Hence, there exists a need for finding the best route in an optimized manner. This paper proposes an Improved Wolf Prey Inspired Protocol (IWPIP) for finding the ideal route in the dynamic environment like 5G based cognitive radio ad-hoc network. IWPIP focuses on finding the ideal route based on the reliability of route, shorter distance, and shorter hops that minimize the consumption of energy to increase the network lifetime. Before sending the data packets, routes are evaluated using a fitness function. IWPIP's efficiency has been demonstrated through comprehensive simulation, which resulted in promising outcomes in terms of throughput, packet delivery and drop ratio, delay, and energy consumption.

Keywords

Optimization, Routing, Bio-Inspired, Energy, Delay, Cognitive Radio Ad Hoc Networks, Wolf Prey Inspired Protocol.
User
Notifications
Font Size

  • F. Palmieri, "A Reliability and latency-aware routing framework for 5G transport infrastructures", Computer Networks, vol. 179, p. 107365, 2020. https://doi.org/10.1016/j.comnet.2020.107365

  • J. Mu, "An improved AODV routing for the zigbee heterogeneous networks in 5G environment", Ad Hoc Networks, vol. 58, pp. 13-24, 2017. https://doi.org/10.1016/j.adhoc.2016.12.002

  • Z. Li, Y. Hu, T. Hu and R. Ma, "PARS-SR: A scalable flow forwarding scheme based on Segment Routing for massive giant connections in 5G networks", Computer Communications, vol. 159, pp. 206-214, 2020. https://doi.org/10.1016/j.comcom.2020.05.014

  • H. Riasudheen, K. Selvamani, S. Mukherjee and I. Divyasree, "An efficient energy-aware routing scheme for cloud-assisted MANETs in 5G", Ad Hoc Networks, vol. 97, p. 102021, 2020. https://doi.org/10.1016/j.adhoc.2019.102021

  • A. Mesodiakaki, E. Zola, R. Santos and A. Kassler, "Optimal user association, backhaul routing and switching off in 5G heterogeneous networks with mesh millimeter wave backhaul links", Ad Hoc Networks, vol. 78, pp. 99-114, 2018. https://doi.org/10.1016/j.adhoc.2018.05.008

  • M. Abolhasan, M. Abdollahi, W. Ni, A. Jamalipour, N. Shariati and J. Lipman, "A Routing Framework for Offloading Traffic From Cellular Networks to SDN-Based Multi-Hop Device-to-Device Networks", IEEE Transactions on Network and Service Management, vol. 15, no. 4, pp. 1516-1531, 2018. https://doi.org/10.1109/TNSM.2018.2875696

  • H. Rastegarfar, T. Svensson and N. Peyghambarian, "Optical Layer Routing Influence on Software-Defined C-RAN Survivability", Journal of Optical Communications and Networking, vol. 10, no. 11, p. 866, 2018. https://doi.org/10.1364/JOCN.10.000866

  • Martin, L. Dooley and K. Wong, "5G multi-layer routing strategies for TV white space secondary user access", IET Communications, vol. 13, no. 12, pp. 1801-1807, 2019. https://doi.org/10.1049/iet-com.2018.5848

  • P. Yan, S. Choudhury, F. Al-Turjman and I. Al-Oqily, "An energy-efficient topology control algorithm for optimizing the lifetime of wireless ad-hoc IoT networks in 5G and B5G", Computer Communications, vol. 159, pp. 83-96, 2020. https://doi.org/10.1016/j.comcom.2020.05.010

  • Z. Ma, B. Li, Z. Yan and M. Yang, "Remaining bandwidth based multipath routing in 5G millimeter wave self-backhauling network", Wireless Networks, vol. 25, no. 7, pp. 3839-3855, 2019. https://doi.org/10.1007/s11276-018-01919-y

  • Z. Khan, P. Fan, F. Abbas, H. Chen and S. Fang, "Two-Level Cluster Based Routing Scheme for 5G V2X Communication", IEEE Access, vol. 7, pp. 16194-16205, 2019. https://doi.org/10.1109/ACCESS.2019.2892180

  • J.Ramkumar and R.Vadivel, "Performance Modeling of Bio-Inspired Routing Protocols in Cognitive Radio Ad Hoc Network to Reduce End-to-End Delay", International Journal of Intelligent Engineering and Systems, Vol.12, No.1, pp. 221-231, 2019. https://doi.org/10.22266/ijies2019.0228.22

  • X. Jin, R. Zhang, J. Sun and Y. Zhang, "TIGHT: A Geographic Routing Protocol for Cognitive Radio Mobile Ad Hoc Networks", IEEE Transactions on Wireless Communications, vol. 13, no. 8, pp. 4670-4681, 2014. https://doi.org/10.1109/TWC.2014.2320950

  • R. Sahu, S. Sharma, M.A. Rizvi, "ZBLE: Zone Based Leader Election Energy Constrained AOMDV Routing Protocol", International Journal of Computer Networks and Applications, Vol. 6, no. 3, pp. 39-46, 2019. https://doi.org/10.22247/ijcna/2019/49643

  • R. Yadav, R. Misra and D. Saini, "Energy aware cluster based routing protocol over distributed cognitive radio sensor network", Computer Communications, vol. 129, pp. 54-66, 2018. https://doi.org/10.1016/j.comcom.2018.07.020

  • H. Salameh, S. Otoum, M. Aloqaily, R. Derbas, I. Ridhawi and Y. Jararweh, "Intelligent jamming-aware routing in multi-hop IoT-based opportunistic cognitive radio networks", Ad Hoc Networks, vol. 98, p. 102035, 2020. https://doi.org/10.1016/j.adhoc.2019.102035

  • F. Tang, H. Zhang, L. Fu and X. Li, "Distributed Stable Routing with Adaptive Power Control for Multi-Flow and Multi-Hop Mobile Cognitive Networks," IEEE Transactions on Mobile Computing, vol. 18, no. 12, pp. 2829-2841, 2019. https://doi.org/10.1109/TMC.2018.2885762

  • J. Singh and M. Rai, "CROP: Cognitive radio ROuting Protocol for link quality channel diverse cognitive networks", Journal of Network and Computer Applications, vol. 104, pp. 48-60, 2018. https://doi.org/10.1016/j.jnca.2017.12.014

  • X. Tang, J. Zhou, S. Xiong, J. Wang and K. Zhou, "Geographic Segmented Opportunistic Routing in Cognitive Radio Ad Hoc Networks Using Network Coding," IEEE Access, vol. 6, pp. 62766-62783, 2018. https://doi.org/10.1109/ACCESS.2018.2875566

  • J.Ramkumar and R.Vadivel, "Improved frog leap inspired protocol (IFLIP) – for routing in cognitive radio ad hoc networks (CRAHN)", World Journal of Engineering, vol. 15, no. 2, pp. 306-311, 2018. https://doi.org/10.1108/WJE-08-2017-0260

  • J.Ramkumar and R.Vadivel, "CSIP—Cuckoo Search Inspired Protocol for Routing in Cognitive Radio Ad Hoc Networks", Advances in Intelligent Systems and Computing, Vol. 556, pp. 145-153, 2017. https://doi.org/10.1007/978-981-10-3874-7_14

  • I. Akyildiz, W. Lee and K. Chowdhury, "CRAHNs: Cognitive radio ad hoc networks", Ad Hoc Networks, vol. 7, no. 5, pp. 810-836, 2009. https://doi.org/10.1016/j.adhoc.2009.01.001

  • J.Ramkumar and R.Vadivel, "Intelligent Fish Swarm Inspired Protocol (IFSIP) For Dynamic Ideal Routing in Cognitive Radio Ad-Hoc Networks", International Journal of Computing and Digital Systems, Vol. 10, pp. 2-11. 2020. https://journal.uob.edu.bh:443/handle/123456789/3961

  • R. Rahim, S. Murugan, S. Priya, S. Magesh and R. Manikandan, "Taylor Based Grey Wolf Optimization Algorithm (TGWOA) For Energy Aware Secure Routing Protocol", International Journal of Computer Networks and Applications, vol. 7, no. 4, p. 93, 2020. https://doi.org/10.22247/ijcna/2020/196041


Abstract Views: 359

PDF Views: 0




  • Improved Wolf Prey Inspired Protocol for Routing in Cognitive Radio Ad Hoc Networks

Abstract Views: 359  |  PDF Views: 0

Authors

J. Ramkumar
Department of Computer Science, VLB Janakiammal College of Arts and Science, Coimbatore, Tamil Nadu, India
R. Vadivel
Department of Information Technology, Bharathiar University, Coimbatore, Tamil Nadu, India

Abstract


Fifth Generation (5G) technology has started providing the brand new facilities to the mobile communication world. With its enhanced performance and scalability, it has attracted many domains. Routing overhead in 5G networks is increased rapidly because of the complexity present in the route discovery process, where optimization in routing. Poor routing becomes a sophisticated and dynamic challenge in the 5G network. Hence, there exists a need for finding the best route in an optimized manner. This paper proposes an Improved Wolf Prey Inspired Protocol (IWPIP) for finding the ideal route in the dynamic environment like 5G based cognitive radio ad-hoc network. IWPIP focuses on finding the ideal route based on the reliability of route, shorter distance, and shorter hops that minimize the consumption of energy to increase the network lifetime. Before sending the data packets, routes are evaluated using a fitness function. IWPIP's efficiency has been demonstrated through comprehensive simulation, which resulted in promising outcomes in terms of throughput, packet delivery and drop ratio, delay, and energy consumption.

Keywords


Optimization, Routing, Bio-Inspired, Energy, Delay, Cognitive Radio Ad Hoc Networks, Wolf Prey Inspired Protocol.

References





DOI: https://doi.org/10.22247/ijcna%2F2020%2F202977