Cluster-based optimal sink repositioning technique for WSNs using an improved glowworm swarm optimisation and S* position search algorithm

Abstract

Wireless sensor network is a group of organised sensor nodes that are limited to their resources such as limited bandwidth, energy etc. The data gathered from sensor nodes will be forwarded to the sink node to take proper actions. In order to avoid the failures, the sink nodes should be positioned in the better place for the resource optimisation. In this paper, first we will apply clustering for grouping the nodes that are adjacent to sink node. Clustering is done by an improved glowworm swarm optimisation (IGSO) algorithm. The node which has the shortest path is selected for position. Hence, this approach is used to find the optimal position for all the sinks in order to optimise the lifetime of the network and move according with intelligent sink positioning.

An energy efficiency perceptive on MIMO‐OFDM systems using hybrid fruit fly‐based salp swarm optimization technique

“…At last, the best solution is achieved successfully using the proposed HFF-SSO. Hybrid optimization algorithms 32,33 are developed by combining two or more optimization principles or mechanisms. It is observed that promising solutions are obtained for some search problems by using the hybrid algorithm.…”

“…The ordered Eigenvalues for joint PDF (Probability Density Function) Ỹ obey the Wishart distribution in Equation (15).…”

“…In wireless communication systems, the DTX method is much more efficient while analyzing all the energy efficiency techniques because of transferring nature of radio signals without the data transmission, and thus, it shows its effectiveness in decreasing the consumption of system power. Recently in the base stations, the optimization [15][16][17][18] of power utilization has been determined to implement the DTX technique by some researchers. 19 When almost all the consequent cell users are not in the active state, the base station undergoes sleep mode in the network.…”