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Research Article · Open access · Published 10 October 2018

A Comparative Study of Mobility Models for Wireless Sensor Networks

Anas Abu Taleb1

Journal of Computer Science, Volume 14, Issue 10, pp. 1279–1292 · doi.org/10.3844/jcssp.2018.1279.1292

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Abstract

Wireless sensor networks consist of hundreds or thousands of small, lightweight and low-powered sensor nodes that are deployed in the area of interest to collect information in an unattended manner. Since sensor nodes have limited battery, many research papers proposed techniques to enhance the performance and lifetime of wireless sensor networks. Using energy rich mobile sink to collect data from static sensor nodes is one of the techniques that can be used to improve the performance of wireless sensor networks. As a result, several mobility models were proposed to achieve this goal. In this study, we aim to study the performance of wireless sensor network under three mobility models for the mobile sink namely, depth first based mobility model, random waypoint mobility model and Gauss Markov mobility model. Consequently, ns-2 simulator is used to study the performance of the network under different scenarios and speeds of the mobile sink. Additionally, end-to-end delay, throughput and packet delivery ratio are the performance metrics considered in this study to measure the performance. Finally, AODV routing protocol is used to route messages from their sources to the mobile sink.

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Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.

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Taleb, A. A. (2018). A Comparative Study of Mobility Models for Wireless Sensor Networks. Journal of Computer Science, 14(10), 1279–1292. https://doi.org/10.3844/jcssp.2018.1279.1292

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A Comparative Study of Mobility Models for Wireless Sensor NetworksJournal of Computer Science · Volume 14, Issue 10 · pp. 1279–1292 · CC BY 3.0Download