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Optimized and load balanced clustering for wireless sensor networks to increase the lifetime of WSN using MADM approaches

  • Prince Rajpoot
  • Pragya Dwivedi
Article
  • 46 Downloads

Abstract

The power utilization has verified as a major problem in wireless sensor networks (WSNs). Many researchers have provided efficient solutions for power utilization. Clustering is one of them that helps in topology control and ensures efficient power utilization. However, the clustering method should be effective that could obtain the best clusters. Comprehensive evolution of clustering protocols for the lifetime of sensor nodes is a unique approach to the total enhancement of the lifetime of WSNs. There are many conflicting factors that affect the efficiency of clustering, i.e. distance between CH and the base station, distance form node to cluster head (CH), maximum residual energy of CHs, etc. The coordination among these factors has a capability to insure the optimal power utilization by reducing power consumption and load balancing among the nodes and CHs. In this paper, we have considered total sixteen such factors and made coordination among them to select the best CHs. Multiple attribute decision-making methods are used to choose best set of CHs from the available alternatives that can fulfill the condition of coordination efficiently. The experimental results validate that the coordination among these sixteen factors put up one of the best demonstration for choosing best CHs.

Keywords

Wireless sensor network (WSN) Cluster head (CH) selection Load balancing MADM approaches Lifetime of WSN 

Abbreviations

AHP

Analytic hierarchy process

AMRP

Average minimum reachability power

BEENISH

Balanced energy efficient network integrated super heterogeneous protocol for wireless sensor networks

BS

Base station (sink)

CH

Cluster head

DWEHC

Distributed weight-based energy efficient hierarchical clustering

EDDEEC

Enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks

EECS

Energy efficient clustering scheme

EEHC

Energy efficient heterogeneous clustered scheme for wireless sensor networks

EEUC

Energy efficient unequal clustering

FLOC

Fast LOCal clustering

GA

Genetic algorithm

HEED

Hybrid energy-efficient distributed clustering

LEACH

Low-energy adaptive clustering hierarchy

LEACH-C

Low-energy adaptive clustering hierarchy-centralized

MADM

Multi-attribute decision making

MODM

Multi-objective decision making

PEACH

Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks

PROMETHEE

Preference ranking organization method for enrichment evaluations

WSN

Wireless sensor network

TOPSIS

Technique for order preference by similarity to ideal solution

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Authors and Affiliations

  1. 1.MNNIT AllahabadAllahabadIndia

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