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ACO optimized self-organized tree-based energy balance algorithm for wireless sensor network

AOSTEB
  • Vishal Kumar AroraEmail author
  • Vishal Sharma
  • Monika Sachdeva
Original Research
  • 35 Downloads

Abstract

Energy-efficient routing algorithms must handle power-limitation issue of the sensor nodes intelligently to prolong the network life of wireless networks. Accordingly, it is indispensable to collect and exchange the sensor data in an optimized way to reduce energy consumption. Subsequently, an ACO Optimized Self-Organized Tree-Based (AOSTEB) Energy Balance Algorithm for Wireless Sensor Network has been proposed that discovers an efficient route during intra-cluster communication. AOSTEB scheme operates in three phases: cluster-formation, multi-path creation, and data transmission. During cluster-formation, the desired number of sensor nodes are alleviated to the role of cluster-heads (CHs), and the remaining neighboring sensor nodes join the nearest CHs to form a cluster. Further, the multiple paths between the CH and member nodes are discovered using Ant Colony Optimization algorithm. A dynamic energy efficient optimized route is selected within a specific cluster on account of shortest distance and less energy-consumption to initiate the data exchange process within the cluster. The extensive simulation observations ascertain the efficiency of the proposed algorithm by demonstrating the prolonged network lifetime, enhanced stability period, and reduced energy consumption in contrast to the earlier reported works in wireless sensor networks.

Keywords

Wireless sensor network Energy efficient routing Ant colony optimization 

Notes

Acknowledgements

The authors of the work highly acknowledge the contribution of I.K.G Punjab Technical University, Kapurthala, Punjab, India.

Funding

This study is not funded from any grant.

Compliance with ethical standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Vishal Kumar Arora
    • 1
    Email author
  • Vishal Sharma
    • 2
  • Monika Sachdeva
    • 3
  1. 1.IKG PTUKapurthalaIndia
  2. 2.Department of Electronics and EngineeringShaheed Bhagat Singh State Technical CampusFerozepurIndia
  3. 3.Computer Science and Engineering DepartmentIKG PTUKapurthalaIndia

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