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Vol. 213, Issue 6, June 2017, pp. 9-23




Deployment Strategies and Clustering Protocols Efficiency

Chérif Diallo

Laboratoire Algébre, Cryptographie, Codes et Applications (ACCA) UFR Sciences appliquéeset de Technologies (UFR SAT) Université Gaston Berger, BP 234 Saint-Louis, Sénégal
Tel.: +221339612340, fax: +221339615338

E-mail: cherif.diallo@ugb.edu.sn


Received: 22 April 2017 /Accepted: 31 March 2017 /Published: 30 June2017

Digital Sensors and Sensor Sysstems


Abstract: Wireless sensor networks face significant design challenges due to limited computing and storage capacities and, most importantly, dependence on limited battery power. Energy is a critical resource and is often an important issue to the deployment of sensor applications that claim to be omnipresent in the world of future. Thus optimizing the deployment of sensors becomes a major constraint in the design and implementation of a WSN in order to ensure better network operations. In wireless networking, clustering techniques add scalability, reduce the computation complexity of routing protocols, allow data aggregation and then enhance the network performance. The well-known MaxMin clustering algorithm was previously generalized, corrected and validated. Then, in a previous work we have improved MaxMin by proposing a Single- node Cluster Reduction (SNCR) mechanism which eliminates single-node clusters and then improve energy efficiency. In this paper, we show that MaxMin, because of its original pathological case, does not support the grid deployment topology, which is frequently used in WSN architectures. The unreliability feature of the wireless links could have negative impacts on Link Quality Indicator (LQI) based clustering protocols. So, in the second part of this paper we show how our distributed Link Quality based d- Clustering Protocol (LQI-DCP) has good performance in both stable and high unreliable link environments. Finally, performance evaluation results also show that LQI-DCP fully supports the grid deployment topology and is more energy efficient than MaxMin.


Keywords: Wireless sensor network, Deployment strategy, Multihop Clustering, LQI, MaxMin, LQI-DCP.


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