Efficient approach to maximise WSN lifetime using weighted optimum storage‐node placement, efficient and energetic wireless recharging, efficient rule‐based node rotation and critical‐state‐data‐passing methods. Issue 6 (1st November 2017)

• Record Type: Journal Article
• Authors: R.V., Labisha; E., Baburaj
• Is Part Of: IET networks. Volume 6:Issue 6(2017)
• Page Start: 203
• Page End: 217
• Publication Date: 2017-11-01
• Subjects: wireless sensor networks -- telecommunication power management -- telecommunication network routing -- telecommunication network topology -- energy consumption -- cooperative communication -- MIMO communication -- power utilisation; WSN lifetime maximisation -- weighted optimum storage‐node placement -- efficient wireless recharging -- energetic wireless recharging -- efficient rule‐based node rotation -- critical‐state‐data‐passing methods -- sensor nodes -- wireless sensor networks -- network life time -- power utilisation efficiency -- data storage -- data retrieval -- energy consumption minimisation -- weighted optimum SNP -- node rotation -- cooperative multiinput‐multioutput clustering -- cooperative multiinput‐multioutput routing -- WSN topology lifetime ratio; Computer network architectures -- Periodicals; Computer network protocols -- Periodicals; Information networks -- Periodicals; Telecommunication systems -- Periodicals; 004.605
• DOI: 10.1049/iet-net.2017.0035
• Languages: English
• ISSNs: 2047-4954

Abstract

Abstract : The sensor nodes of wireless sensor networks (WSNs) are usually positioned in remote or inaccessible areas and hence the physical maintenance such as battery replacement is more difficult. One of the core challenges of WSN is to increase the network life time, meaning that the efficiency of power utilisation should be the maximum. The major reasons for high power consumption are drawn out transmission path to reach sink, work load add‐ons on nodes closer to storage medium, and the energy necessary for storage. This study proposes a novel method of data storage and retrieval for WSN environment to improve the network lifetime by minimising the energy consumption. The proposed method accomplishes this milestone using four novel algorithms, namely weighted optimum storage‐node placement(SNP), efficient and energetic wireless recharging, efficient rule‐based node rotation and critical‐state‐data passing. The areas of influence of this proposed method are SNP, wireless recharging, node rotation and cooperative multi‐input–multi‐output clustering/routing. Simulation results claim that the proposed method multiplies the WSN topology lifetime ratio by a significant level and outperforms the earlier versions significantly.