PERFORMANCE EVALUATION OF ROUTING ALGORITHM FOR MANET BASED ON THE MACHINE LEARNING TECHNIQUES
PDF

Keywords

wireless communication
Adhoc networks
MANET
routing protocols
reinforcement learning
energy consumption
transmission delay and packet delivery ratio

How to Cite

Duraipandian, M. 2019. “PERFORMANCE EVALUATION OF ROUTING ALGORITHM FOR MANET BASED ON THE MACHINE LEARNING TECHNIQUES”. Journal of Trends in Computer Science and Smart Technology 1 (1): 24-35. https://doi.org/10.36548/jtcsst.2019.1.003.

Abstract

The rapid advances in wireless communication technology has led to an extraordinary progress in the adhoc type of networking. The mobile adhoc networks being a subtype of the adhoc network almost poses the same characteristics of the adhoc network, presenting multiple challenges in framing a route for the transmission of the information from the source to the destination. So the paper proposes a routing method developed based on the reinforcement learning, exploiting the node information's to establish a route that is short and stable. The proposed method scopes to minimize the energy consumption, transmission delay, and improve the delivery ratio of the packets, enhancing the throughput. The efficiency of the proposed method is determined by validating its performance in the network simulator-II, in terms of the energy consumption, delay in the transmission and the packet delivery ratio.

PDF

References

Saeed, Nagham H., Maysam F. Abbod, and Hamed S. Al-Raweshidy. "MANET routing protocols taxonomy." In 2012 International Conference on Future Communication Networks, pp. 123-128. IEEE, 2012.

Bai, Yuxia, Yefa Mai, and Nan Wang. "Performance comparison and evaluation of the proactive and reactive routing protocols for MANETs." In 2017 Wireless Telecommunications Symposium (WTS), pp. 1-5. IEEE, 2017.

Nayak, Pad Malaya, and Pallavishree Sinha. "Analysis of random way point and random walk mobility model for reactive routing protocols for MANET using NetSim simulator." In 2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS), pp. 427-432. IEEE, 2015.

Er-Rouidi, Mohamed, Houda Moudni, Hicham Mouncif, and Abdelkrim Merbouha. "An energy consumption evaluation of reactive and proactive routing protocols in mobile ad-hoc network." In 2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV), pp. 437-441. IEEE, 2016.

Darabkh, Khalid A., and Mohammad SE Judeh. "An Improved Reactive Routing Protocol over Mobile Ad-hoc Networks." In 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC), pp. 707-711. IEEE, 2018.

Majd, Nahid Ebrahimi, Nam Ho, Thu Nguyen, and Jacob Stolmeier. "Evaluation of Parameters Affecting the Performance of Routing Protocols in Mobile Ad Hoc Networks (MANETs) with a Focus on Energy Efficiency." In Future of Information and Communication Conference, pp. 1210-1219. Springer, Cham, 2019.

Ghouti, Lahouari, Tarek R. Sheltami, and Khaled S. Alutaibi. "Mobility prediction in mobile ad hoc networks using extreme learning machines." Procedia Computer Science 19 (2013): 305-312.

Forster, Anna. "Machine learning techniques applied to wireless ad-hoc networks: Guide and survey." In 2007 3rd international conference on intelligent sensors, sensor networks and information, pp. 365-370. IEEE, 2007.

Darwish, Saad M., Amr Elmasry, and Shaymaa H. Ibrahim. "Optimal Shortest Path in Mobile Ad-Hoc Network Based on Fruit Fly Optimization Algorithm." In International Conference on Advanced Machine Learning Technologies and Applications, pp. 91-101. Springer, Cham, 2019.

Li, Fan, Xiaoyu Song, Huijie Chen, Xin Li, and Yu Wang. "Hierarchical Routing for Vehicular Ad Hoc Networks via Reinforcement Learning." IEEE Transactions on Vehicular Technology 68, no. 2 (2018): 1852-1865.

Ghasemnezhad, Solmaz, and Ali Ghaffari. "Fuzzy logic based reliable and real-time routing protocol for mobile ad hoc networks." Wireless Personal Communications 98, no. 1 (2018): 593-611.

Thangaramya, K., K. Kulothungan, R. Logambigai, M. Selvi, Sannasi Ganapathy, and A. Kannan. "Energy aware cluster and neuro-fuzzy based routing algorithm for wireless sensor networks in IoT." Computer Networks 151 (2019): 211-223.

Nallusamy, C., and A. Sabari. "Particle Swarm Based Resource Optimized Geographic Routing for Improved Network Lifetime in MANET." Mobile Networks and Applications 24, no. 2 (2019): 375-385.

Kwon, Kiwoong, Seong Hoon Kim, Minkeun Ha, and Daeyoung Kim. "Traffic-aware stateless multipath routing for fault-tolerance in IEEE 802.15. 4 wireless mesh networks." Wireless Networks 24, no. 5 (2018): 1755-1774.

Sajwan, Mohit, Devashish Gosain, and Ajay K. Sharma. "Hybrid energy-efficient multi-path routing for wireless sensor networks." Computers & Electrical Engineering 67 (2018): 96-113.