Hybrid Tasmanian Devil and Elephant Herding Model-Based Optimal Cluster Head Selection and Routing in MANET

Abstract

MANETs (Mobile AdHoc Networks) have major problems due to the resource-constrained nature of mobile nodes. MANET topology is highly uncertain due to the mobility of MANET nodes that affect the stability of interconnected links. This scenario results in an increased traffic overhead which affects the routing protocol performance and results in increased energy consumption. A routing scheme designed for MANET should be able to handle energy depletion issues and nodes’ mobility. This paper designs two novel schemes to enhance energy efficiency and network lifetime by performing clustering and routing in MANET. The Hybrid Tasmanian devil and Elephant herding optimization (HTDEHO) is used for clustering the MANET nodes to minimize the overhead, enhance the stability of the network topology, and reduce collision. The HTDEHO selects the optimal cluster head (CH) from a set of nodes based on their fitness value calculated by various parameters such as mobility-based node ranking, residual energy, distance, node degree, and optimal next hop CH selection. Dwarf mongoose optimization algorithm with Fuzzy variable (FDMO) algorithm selects optimal routing cost from CH to the base station based on various parameters such as throughput, delay, and distance. The efficiency of the proposed model is evaluated with different performance metrics such as energy consumption, throughput, end-to-end delay, and packet-dropping analysis. The performance of the proposed HTDEHO-FDMO classifier is compared with different techniques such as RDOAICRP, BFOA, MARP-HO, and FEKHO-QBA. Even after 170 iterations, the HTDEHO model retains a total of 10 alive nodes.

KEYWORDS:

• Clustering
• energy consumption
• fuzzy optimization
• MANET
• network lifetime
• routing

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Mitha Rachel Jose

Mitha Rachel Jose obtained her bachelor of technology degree in computer science and engineering from Kerala University. Then she obtained her Master’s degree in computer science and engineering from Anna University and pursuing PhD in computer science majoring in Manets from Noorul Islam University, Tamilnadu, India. She worked as in Mangalam College of Engineering under Mahatma Gandhi University for 7 years. Her specializations include image processing and wireless sensor networks. Her current research interests are wireless sensor networks and MANETS. Presently she is working as a research developer at Centria University of Applied Science, Finland.

S. Maria Celestin Vigila

S Maria Celestin Vigila is working as in the department of Information Technology, Noorul Islam centre for Higher Education, Kumaracoil. She received her BE and ME in computer science and engineering in 1996 and 1999, respectively. She received her PhD in the area of data security from the Anna University, Chennai in 2013. She is an active member of ISTE and IET. She is the reviewer for quite a few peer reviewed international journals. Her research interest includes cryptography and data security, wireless networks and information hiding. Email: [email protected]