Energy-Aware Adaptive Weighted Grid Clustering Algorithm for Renewable Wireless Sensor Networks

Wireless sensor networks (WSNs), built from many battery-operated sensor nodes are distributed in the environment for monitoring and data acquisition. Subsequent to the deployment of sensor nodes, the most challenging and daunting task is to enhance the energy resources for the lifetime performance...

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Bibliographic Details
Published in:Future internet Vol. 9; no. 4; p. 54
Main Authors: Aslam, Nelofar, Xia, Kewen, Haider, Muhammad, Hadi, Muhammad
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.12.2017
Subjects:
Adaptive algorithms
Batteries
cluster head
Clustering
Clusters
Computer simulation
Cycle time
Energy conservation
Energy consumption
Energy management
Energy sources
Environmental monitoring
grid clustering routing protocol
Internet
Portable equipment
Power consumption
Remote sensors
Residual energy
Sensors
Shortest-path problems
vacation time
Wireless communications
wireless portable charging device (WPCD)
wireless power transfer
Wireless power transmission
Wireless sensor networks
wireless sensor networks (WSNs)
ISSN:1999-5903, 1999-5903
Online Access:Get full text
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Summary:Wireless sensor networks (WSNs), built from many battery-operated sensor nodes are distributed in the environment for monitoring and data acquisition. Subsequent to the deployment of sensor nodes, the most challenging and daunting task is to enhance the energy resources for the lifetime performance of the entire WSN. In this study, we have attempted an approach based on the shortest path algorithm and grid clustering to save and renew power in a way that minimizes energy consumption and prolongs the overall network lifetime of WSNs. Initially, a wireless portable charging device (WPCD) is assumed which periodically travels on our proposed routing path among the nodes of the WSN to decrease their charge cycle time and recharge them with the help of wireless power transfer (WPT). Further, a scheduling scheme is proposed which creates clusters of WSNs. These clusters elect a cluster head among them based on the residual energy, buffer size, and distance of the head from each node of the cluster. The cluster head performs all data routing duties for all its member nodes to conserve the energy supposed to be consumed by member nodes. Furthermore, we compare our technique with the available literature by simulation, and the results showed a significant increase in the vacation time of the nodes of WSNs.
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ISSN:1999-5903
1999-5903
DOI:10.3390/fi9040054