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Mobility based energy efficient and multi-sink algorithms for consumer home networks


Abstract:

With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can co...Show More

Abstract:

With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an important technique to improve home network performance including energy consumption, lifetime and end-to-end delay. Also, it can largely mitigate the hot spots near the sink node. The selection of optimal moving trajectory for sink node(s) is an NP-hard problem jointly optimizing routing algorithms with the mobile sink moving strategy is a significant and challenging research issue. The influence of multiple static sink nodes on energy consumption under different scale networks is first studied and an Energy-efficient Multi-sink Clustering Algorithm (EMCA) is proposed and tested. Then, the influence of mobile sink velocity, position and number on network performance is studied and a Mobile-sink based Energy-efficient Clustering Algorithm (MECA) is proposed. Simulation results validate the performance of the proposed two algorithms which can be deployed in a consumer home network environment1.
Published in: IEEE Transactions on Consumer Electronics ( Volume: 59, Issue: 1, February 2013)
Page(s): 77 - 84
Date of Publication: 04 April 2013

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I. Introduction

Many kinds of consumer products have been deployed in home automation networks. A home network usually contains a certain type of network connecting many consumer products, e.g. sensors, so that the users can control these appliances in an interactive, intelligent and automatic way to improve their Quality of Life (QoL).

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