NDLI: A Relay Node Based Hybrid Low Energy Adaptive Clustering Hierarchy for Wireless Sensor Networks

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A Relay Node Based Hybrid Low Energy Adaptive Clustering Hierarchy for Wireless Sensor Networks

Content Provider	Semantic Scholar
Author	Azim, Akramul Islam, Mohammad Mahfuzul
Copyright Year	2012
Abstract	Due to the necessity of saving energy cost in low-powered devices, extending the lifetime of a sensor node powered by battery in both homogeneous and heterogeneous wireless sensor networks (WSNs) is area of interest. To save battery power in sensor networks, many research works including low energy adaptive clustering hierarchy (LEACH) and its variants use clustering techniques to reduce energy spent by keeping most of the nodes in sleeping mode but making a good quality of service (QoS). However, LEACH lacks on optimizing the network life time due to loosing huge energy of sensor nodes selected as cluster heads for communications. In contrast, relay node based schemes use independent powerful relay nodes as cluster heads to save energy of the low energy sensor nodes. These schemes also suffer from a number of problems such as relay node placement, blind spots and immature death of cluster heads. LEACH and its variants except fixed LEACH, suffer from the problem of accomplishing huge energy of sensor nodes due to forming repeated cluster at each fixed time interval. Fixed LEACH surmounts the repeated clustering formation problem by forming fixed clusters only once, but wastes huge energy and incurs loss of information due to the premature death of cluster heads before expire a constant amount of round time. The research work in this paper uses the relay nodes as the cluster heads in addition to LEACH, however uses fixed LEACH (LEACH-F) when all relay node dies, and the round time of fixed LEACH is adjusted dynamically to decrease the probability of premature death of cluster heads.
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://sersc.org/journals/IJEIC/vol3_Is3/4.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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