Background:
The restricted energy and network life is a critical issue in the real-time sensor network. The occurrence of low-energy and faulty intermediate nodes can increase communication failure. The number of intermediate
nodes affects the number of re-transmission, communication-failures, and increases the energy consumption on the routing
path. The existing protocols take the greedy decision on all possible intermediate nodes collectively by considering one or
more parameters.
Objective:
This work divides the distance between the source and destination into coverage-specific zones for restricting
the hop-count. Now each zone is processed individually and collectively for generating the energy effective and failure
preventive route.
Methods:
In this paper, the energy and coverage weighted BFS (Best First Model) algorithm is presented for route optimization in the sensor network. The max-min BFS is implied on sensor nodes of each zone and identified as the most reliable
and effective intermediate node. The individual and composite weighted rules are applied to energy and distance parameters. This new routing protocol discovered the energy-adaptive route.
Results:
The proposed model is simulated on a randomly distributed network, and the analysis is done in terms of network
life, energy consumption, hop count, and the number of route switching parameters. The comparative analysis is done
against the MCP, MT-MR, Greedy, and other state-of-art routing protocols.
Conclusion:
The comparative results validate the significance of the proposed routing protocol in terms of energy effectiveness, lesser route switching, and improved the network life.
IRPanet: Intelligent Routing Protocol in VANET for Dynamic Route Optimization
