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Sensors 2016, 16(1), 9;

Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things

Intelligent Systems and Advanced Telecommunication Laboratory, Department of Computer Science, University of the Western Cape, Private Bag X17, Bellville, Cape Town 7535, South Africa
Department of Computer Science, Namibia University of Science and Technology (NUST), Private Bag 13888, Windhoek 9000, Namibia
Author to whom correspondence should be addressed.
Academic Editor: Davide Brunelli
Received: 1 October 2015 / Revised: 29 November 2015 / Accepted: 8 December 2015 / Published: 23 December 2015
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Current generation wireless sensor routing algorithms and protocols have been designed based on a myopic routing approach, where the motes are assumed to have the same sensing and communication capabilities. Myopic routing is not a natural fit for the IoT, as it may lead to energy imbalance and subsequent short-lived sensor networks, routing the sensor readings over the most service-intensive sensor nodes, while leaving the least active nodes idle. This paper revisits the issue of energy efficiency in sensor networks to propose a clustering model where sensor devices’ service delivery is mapped into an energy awareness model, used to design a clustering algorithm that finds service-aware clustering (SAC) configurations in IoT settings. The performance evaluation reveals the relative energy efficiency of the proposed SAC algorithm compared to related routing algorithms in terms of energy consumption, the sensor nodes’ life span and its traffic engineering efficiency in terms of throughput and delay. These include the well-known low energy adaptive clustering hierarchy (LEACH) and LEACH-centralized (LEACH-C) algorithms, as well as the most recent algorithms, such as DECSA and MOCRN. View Full-Text
Keywords: service-aware clustering (SAC); Internet-of-Things (IoT); energy efficiency; clustering mechanisms; hybrid sensor networks service-aware clustering (SAC); Internet-of-Things (IoT); energy efficiency; clustering mechanisms; hybrid sensor networks

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Bagula, A.; Abidoye, A.P.; Zodi, G.-A.L. Service-Aware Clustering: An Energy-Efficient Model for the Internet-of-Things. Sensors 2016, 16, 9.

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