An Ant Colony based Routing Algorithm for Wireless Sensor Network

Liu, Xiaodong; Li, Songyang; Wang, Miao

doi:10.14257/ijfgcn.2016.9.6.08

Cited by 15 publications

(1 citation statement)

References 12 publications

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“…An ant-based route calculation method to locate the best routes between a nourishment source and their nests is proposed in [13]. Here, for optimization the concentration of pheromone is influenced by the combination of the pheromone and the node energy and node delay.…”

Section: Introductionmentioning

confidence: 99%

A novel bio-inspired routing algorithm based on ACO for WSNs

2019

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The methods to achieve efficient routing in energy constrained wireless sensor networks (WSNs) is a fundamental issue in networking research. A novel approach of ant colony optimization (ACO) algorithm for discovering the optimum route for information transmission in the WSNs is proposed here for optimization and enhancement. The issue of path selection to reach the nodes and vital correspondence parameters, for example, the versatility of nodes, their constrained vitality, the node residual energy and route length are considered since the communications parameters and imperatives must be taken into account by the imperative systems that mediate in the correspondence procedure, and the focal points of the subterranean insect framework have been utilized furthermore. Utilizing the novel technique and considering both the node mobility and the existing energy of the nodes, an optimal route and best cost from the originating node to the target node can be detected. The proposed algorithm has been simulated and verified using MATLAB and the simulation results demonstrate that new ACO based algorithm achieved improved performance, about 30% improvement compared with the traditional ACO algorithm, and faster convergence to determine the best cost route, and recorded an improvement in the energy consumption of the nodes per transmission.

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Section: Introductionmentioning

confidence: 99%