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MCTRP: An Energy Efficient Tree Routing Protocol for Vehicular Ad Hoc Network Using Genetic Whale Optimization Algorithm - 2020

Research Area:  Vehicular Ad Hoc Networks


VANETs are wireless sensor networks that suffer from the drawback of highly mobile nodes. The main objective of any type of network is to achieve efficient transmission goals. The vehicles act as the transmitting nodes. Cognitive radio technology helps in sensing the spectrum in order to ensure the efficient usage of the reserved channels by all the nodes. Our proposed system incorporates a routing protocol with the cognitive radio technology for efficient channel assignment. The routing protocol applies a tree based structure for efficient routing within and between networks. The tree routing protocol is further altered by the inclusion of an efficient optimized scheme. The proposed technique involves a Genetic Whale Optimization Algorithm which helps in choosing a root channel for transmission. When the selected root channel becomes active, the other channels are disabled. The proposed tree routing protocol is called the modified cognitive tree routing protocol (MCTRP).Apart from routing this protocol also caters to the need of effective channel utilization by allocating the spectrum fairly. This scheme results in ranking the channels based on their transmission efficiency and also aims to reduce the inherent delay usually associated with VANETs. The protocol also handles link breakages efficiently. The proposed scenario is simulated in NS2 and is evaluated based on the major network metrics. Our protocol shows a sharp decline in the associated delay and guarantees effective channel utilization. The proposed MCTRP method is effective over other protocols, such as, CTRP and OLSR. The analytical results show that MCTRP promises minimum overheads with effective channel utilization than the existing protocols.

Author(s) Name:  Usha Mohanakrishnan,B. Ramakrishnan

Journal name:  Wireless Personal Communications

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s11277-019-06720-4

Volume Information:  volume 110, pages 185–206 (2020)