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11.06.2018 | S.I. : Emerging Intelligent Algorithms for Edge-of-Things Computing | Ausgabe 5/2019

Neural Computing and Applications 5/2019

Pivot variable location-based clustering algorithm for reducing dead nodes in wireless sensor networks

Zeitschrift:
Neural Computing and Applications > Ausgabe 5/2019
Autoren:
S. Jancy, C. Jayakumar

Abstract

The information technology has grown so rapidly that it has led to the development of compact size and inexpensive sensor nodes. Several sensor nodes together form a WSN. Though the WSN is compact in size, they can be equipped with radio transceivers, sensors, microprocessors which are embedded and sensors. One of the major critical issues with WSN is energy efficiency. With WSN, various energy-efficient techniques are being employed. Among clustering techniques, LEACH, HEED, EAMMH, TEEN, SEP, DEEC, K-means clustering algorithm are some of the most popular energy-efficient techniques which are employed. These are hierarchical based protocol which saves energy by balancing the energy expense. Detailed review and analysis of these protocols are presented, and midpoint location algorithm is proposed in this paper. The methodology used for reduction in dead nodes while transmitting the data is also discussed. In the proposed work, path construction phase (PCP) and alternative path construction phase (APCP) are created in order to reduce dead nodes. During the processes of data transmission if a node is found out that it will fail and APCP is applied, the cluster head is changed while applying the APCP. The cluster head is chosen based on midpoint location and highest node energy. The cluster head becomes permanent if the node has midpoint location and the highest energy. If the node does not have midpoint location and highest energy, it becomes a temporary cluster head. The proposed techniques are compared with EAMMH protocol and LEACH protocol using MATLAB. When compared with EAMMH, the dead nodes were reduced with subsequent rounds.

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