Minimum spanning tree–based delay‐aware mobile sink traversal in wireless sensor networks. (30th January 2017)

• Record Type: Journal Article
• Authors: Nitesh, Kumar; Azharuddin, Md; Jana, Prasanta
• Is Part Of: International journal of communication systems. Volume 30:Number 13(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-01-30
• Subjects: Wireless sensor networks, mobile sink, rendezvous point, minimum spanning tree, delay‐bound path, network lifetime; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.3270
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: Energy efficient data collection in a delay‐bound application is a challenging issue for mobile sink–based wireless sensor networks. Many researchers have proposed the concept of rendezvous points (RPs) to design the path for the mobile sink. Rendezvous points are the locations in the network where the mobile sink halts and collects data from the nearby sensor nodes. However, the selection of RPs for the design of path has a significant impact on timely data collection from the network. In this paper, we propose an efficient algorithm for selection of the RPs for efficient design of mobile sink trajectory in delay‐bound applications of wireless sensor networks. The algorithm is based on a virtual path and minimum spanning tree and shown to maximize network lifetime. We perform extensive simulations on the proposed algorithm and compare results with the existing algorithms to demonstrate the efficiency of the proposed algorithm of various performance metrics. Abstract : Considering the challenges of path design of mobile sink in any delay‐bound application of wireless sensor networks, the article present an efficient algorithm for constructing an efficient rendezvous points–based mobile sink trajectory. The technique is based on a virtual path and minimum spanning tree. It considers several parameters to generate a cost function, which is latter used to select most suitable rendezvous points and is shown to outperform existing algorithms through simulation over various performance metrics.