Energy source saving approach using multi-tier network design technique

• Published in: Proceedings - 2015 6th IEEE Control and System Graduate Research Colloquium, ICSGRC 2015
• Main Author: Din W.I.S.W.; Yahya S.; Razali R.; Taib M.N.; Yassin A.I.M.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2016
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964553513&doi=10.1109%2fICSGRC.2015.7412463&partnerID=40&md5=4d1e3ae14ed065bc594534f82fd23437

A wireless sensor network (WSN) organizes collected data at a central location using a set of specialized transducers with a communications infrastructure for monitoring and recording conditions at various locations. A sensor network consists of multiple detection stations called sensor nodes, each of which is small, lightweight and portable. A WSN node contains several technical components which include the radio, microcontroller, analog circuit, sensor interface and an energy source, usually a battery. Sensor nodes have the limitation of its battery where the battery is impossible to be replaced once it has been deployed. This paper presents an improvement of clustering method by implementing two-tiers of network design for efficiency of data transmission and fuzzy logic approach for cluster head selection which minimizes the energy usage of sensor nodes hence can maximize the network lifetime. The two-tiers clustering approach used in this paper covers the average of 100M×100M network and involves three parameters that worked together in order to select the cluster head which are residual energy, communication cost and centrality. The parameters have shown that the selection of cluster head can minimize the energy usage for the whole network lifetime. It is concluded that, the implementation of Fuzzy Logic used all node evenly and the nodes died sequentially as the data keep increasing. This causes the sensor nodes to use their energy effectively hence prolonging the network's lifetime. For the future work, the stability of this algorithm can be tested using random energy. © 2015 IEEE.