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An Energy-efficient Handover Algorithm for Wireless Sensor Networks

The recent advancements in the communication area have enabled the Internet of Things, a paradigm which extends the Internet to everyday objects. The Internet of Things enables many new applications, but also comes with great challenges; effective communication under limited power supply being the perhaps most important one. This thesis presents the design, implementation, and evaluation of an energy-efficient handover algorithm for the main building block in the creation of the Internet of Things: wireless sensor networks. Our low-power handover design is based on a careful breakdown and analysis of the potential power consumption of different components of the handover process. With the scanning part of the process being identified as the main drain of energy, the algorithm is designed to place the majority of the scanning responsibility on the mains powered access points, rather than on the low-power mobile nodes. The proposed algorithm has been implemented and its functionality and low power consumption have been empirically evaluated. We show that the design can reduce the energy consumption by several orders of magnitude compared to existing handover algorithms for wireless sensor networks. In addition, interesting fading effects were discovered in a sparsely deployed network scenario with limited access point coverage; most likely due to multipath propagation. For this case the handover performance was greatly reduced, relative our more normal coverage scenario. While these results illustrate that the absolute energy savings will differ from scenario to scenario, the potential energy savings made possible by the proposed algorithm significantly reduce the battery requirements of the devices in the emerging landscape of the Internet of Things; potentially even opening the door for new devices to connect.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-102447
Date January 2013
CreatorsSäveros, Fredrik
PublisherLinköpings universitet, Institutionen för datavetenskap, Linköpings universitet, Tekniska högskolan
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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