QDVGDD: Query-Driven Virtual Grid based Data Dissemination for wireless sensor networks using single mobile sink
In wireless sensor networks, efficient resource management is a major concern for the battery operated sensor nodes. Data collection using mobile sink(s) is considered as a good strategy to prolong network lifetime and improve network coverage. Most of the existing mobile sink based data collection...
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Main Authors: | , , , |
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Format: | Article |
Published: |
Springer New York LLC
2017
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Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/77197/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021891030&doi=10.1007%2fs11276-017-1552-8&partnerID=40&md5=c2eb25d532920bbc7147c2a4448abf4f |
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Institution: | Universiti Teknologi Malaysia |
Summary: | In wireless sensor networks, efficient resource management is a major concern for the battery operated sensor nodes. Data collection using mobile sink(s) is considered as a good strategy to prolong network lifetime and improve network coverage. Most of the existing mobile sink based data collection schemes operate in event driven or periodic sensing modes. There are several application environments, which dictate query driven data collection using a mobile sink e.g., a mobile sink might require reinforced data reporting from one particular network segment compared to others. In this regard, the existing query driven data collection schemes either impose too many constraints on network operation or poorly perform when delivering the requested data to a mobile sink with variable speed. In this paper we propose Query-Driven Virtual Grid based Data Dissemination (QDVGDD) scheme that aims to improve data delivery performance to a mobile sink. The proposed scheme makes use of a virtual infrastructure thereby causing minimal network control overheads while delivering the requested data with high quality of service to the mobile sink. We carried out extensive simulation works in NS-2.35 to evaluate the performance of our QDVGDD at different sink’s speeds and network sizes. Simulation results reveal improved performance of QDVGDD in terms of data delivery latency, data delivery ratio, average energy consumption, and estimated network traffic as compared to other state-of-the-art. |
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