Lifetime Enhancement of Sensor Nodes Based On Optimized Sink Node Placement Approach

Lifetime Enhancement of Sensor Nodes Based On Optimized Sink Node Placement Approach

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2020 by IJETT Journal
Volume-68 Issue-10
Year of Publication : 2020
Authors : Narendra Mohan
DOI :  10.14445/22315381/IJETT-V68I10P202

Citation 

MLA Style: Narendra Mohan  "Lifetime Enhancement of Sensor Nodes Based On Optimized Sink Node Placement Approach" International Journal of Engineering Trends and Technology 68.10(2020):10-23. 

APA Style:Narendra Mohan. Lifetime Enhancement of Sensor Nodes Based On Optimized Sink Node Placement Approach  International Journal of Engineering Trends and Technology, 68(10),10-23.

Abstract
In Wireless Sensor Networks (WSNs), the sink node plays an essential task in which it collects or stores plenty of transmitted data from other sensor nodes. Optimal placements of sink nodes are a kind of procedure which enhances the network lifetime and minimize the energy consumption. Moreover, sink nodes contains additional resources like long-range antenna, powerful batteries, large memory and so on. Optimal placement of sink is considered as major problem in this work. So, an Enhanced Emperor Penguin Optimization (EEPO) is planned to place a lowest number of sink nodes in optimal locations to cover whole region. Initially, the sensor nodes are clustered using K-medoids algorithm to achieve this goal. After that, the sink nodes are optimally placed based on the EEPO algorithm. Moreover, the objective function is formulated to diminish the energy consumption and prolongs network lifetime. The proposed methodology (EEPO) is implemented using the Network Simulator (NS- 2) tool. Moreover, the performance parameters like, packet delivery ratio (PDR), energy consumption, localization error, network lifetimeand running time are analyzed and compared against existing methodologies like Harris Hawks Optimization (HHO), Particle Swarm optimization (PSO) and Grey Wolf Optimization (GWO) algorithm. When compared to the recent techniques, proposed method achieves better network lifetime with specified number of rounds.

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Keywords
Wireless Sensor Networks, Multiple Sink Nodes, Enhanced Emperor Penguin Optimization Algorithm, Network Lifetime Enhancement, K-Medoids Clustering Algorithm.