Maximizing lifetime of large-scale wireless sensor networks using multi-objective whale optimization algorithm View Full Text


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Article Info

DATE

2019-03-16

AUTHORS

Mohammed M. Ahmed, Essam H. Houssein, Aboul Ella Hassanien, Ayman Taha, Ehab Hassanien

ABSTRACT

The sink nodes in large-scale wireless sensor networks (LSWSNs) are responsible for receiving and processing the collected data from sensor nodes. Identifying the locations of sink nodes in LSWSNs play a vital role in term of saving energy. Furthermore, sink nodes have extremely extra resources such as large memory, powerful batteries, long-range antenna, etc. This paper proposes a multi-objective whale optimization algorithm (MOWOA) to determine the lowest number of sink nodes that cover the whole network. The major aim of MOWOA is to reduce the energy consumption and prolongs the lifetime of LSWSNs. To achieve these objectives, a fitness function has been formulated to decrease energy consumption and maximize the network’s lifetime. The experimental results revealed that the proposed MOWOA achieved a better efficiency in reducing the total power consumption by 26% compared with four well-known optimization algorithms: multi-objective grasshopper optimization algorithm, multi-objective salp swarm algorithm, multi-objective gray wolf optimization, multi-objective particle swarm optimization over all networks sizes. More... »

PAGES

1-17

References to SciGraph publications

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  • 2016. PSO-Based Multiple-sink Placement Algorithm for Protracting the Lifetime of Wireless Sensor Networks in PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION TECHNOLOGIES
  • 2004. A Tutorial on Evolutionary Multiobjective Optimization in METAHEURISTICS FOR MULTIOBJECTIVE OPTIMISATION
  • 2013-01. Sink Node Placement Strategies for Wireless Sensor Networks in WIRELESS PERSONAL COMMUNICATIONS
  • 2018-08. MOGOA algorithm for constrained and unconstrained multi-objective optimization problems in APPLIED INTELLIGENCE
  • 2019. S-shaped Binary Whale Optimization Algorithm for Feature Selection in RECENT TRENDS IN SIGNAL AND IMAGE PROCESSING
  • 2018. Maximizing Lifetime of Wireless Sensor Networks Based on Whale Optimization Algorithm in PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT SYSTEMS AND INFORMATICS 2017
  • 2009-03. Evolutionary multi-objective optimization: some current research trends and topics that remain to be explored in FRONTIERS OF COMPUTER SCIENCE IN CHINA
  • 2018-01-26. An Optimized K-Nearest Neighbor Algorithm for Extending Wireless Sensor Network Lifetime in THE INTERNATIONAL CONFERENCE ON ADVANCED MACHINE LEARNING TECHNOLOGIES AND APPLICATIONS (AMLTA2018)
  • 2002-09. Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks in WIRELESS NETWORKS
  • 2018-04. Grasshopper optimization algorithm for multi-objective optimization problems in APPLIED INTELLIGENCE
  • 2018-10. Improved Cuckoo Search and Chaotic Flower Pollination optimization algorithm for maximizing area coverage in Wireless Sensor Networks in NEURAL COMPUTING AND APPLICATIONS
  • 2011-09-03. Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction in MULTI-OBJECTIVE EVOLUTIONARY OPTIMISATION FOR PRODUCT DESIGN AND MANUFACTURING
  • 2005. Improving PSO-Based Multi-objective Optimization Using Crowding, Mutation and ∈-Dominance in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11235-019-00559-7

    DOI

    http://dx.doi.org/10.1007/s11235-019-00559-7

    DIMENSIONS

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