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

Abstract

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.

Analyzing the impact of the number of nodes on the performance of the routing protocols in manet environment

“…(1) Packet Delivery Ratio: Packet Delivery Ratio (PDR) implies the proportion of the packets of data that got conveyed to the destination hub from some other source hubs [3,9]. This measurement shows the routing convention's quality in its conveyance of information bundles from source to goal.…”

“…The convention may ruin the determination of a fitting or suitable routing that is more effective than others. A few routing conventions with various direction procedures are recommended, for example, movement limitation, increment in power usage, decline the available data transfer capacity, and high accuracy rates despite the piece [8,9]. The primary contrasts between these methodologies are the component used to refresh data/information direction.…”

Energy efficient chaotic whale optimization technique for data gathering in wireless sensor network

“…However, the cost of computational complexity was not sufficient. A novel approach of ant colony optimization (ACO) algorithm was implemented in [22] for information transmission in the WSN. In this method optimal routing is based on the both the node mobility and the energy of the node.…”

Bio‐inspired Mimosa pudica algorithm for energy‐efficient wireless video sensor networks

“…The node which has the better cost value in the cluster acts as a cluster head. In Sharmin et al, 16 route path, node mobility, and node energy are the three parameters considered in an ant colony algorithm.…”