Handling of Indeterminacy for Trust Aware Energy Consumption Using Adaptive Intuitionistic Fuzzy Environment in Wireless Sensor Networks
N. Geetha Lakshmi1, D. Shanmuga Priyaa2
1N. Geetha Lakshmi, Research Scholar, Department of Computer Science, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu), India.
2Dr. D. Shanmuga Priyaa, Department of CS, CA & IT, Associate Professor, Karpagam Academy of Higher Education, Coimbatore (Tamil Nadu), India.
Manuscript received on 14 December 2018 | Revised Manuscript received on 26 December 2018 | Manuscript Published on 24 January 2019 | PP: 239-247 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: Es2063017519/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In Wireless Sensor Network Environment (WSN), the most critical parameter of sensor nodes is the optimal usage of life time. An efficient WSN protocol needs to conserve energy as the main objective of maximizing the network lifetime. Further, secure topology construction is also included in this work, because trust value is considered as a vital factor which affects the behavior of nodes. The incompletion or inconsistency in gathering information of sensor nodes is not well-handled in most existing techniques for the selection of cluster head, taking into account trust Value, Residual Energy, Shortest Path (distance), and Number of Neighbor Nodes. This paper has devised a two-stage optimized energy consumption scheme termed AIFMDMCS. This work elects cluster heads under the condition of indeterminacy in selection criteria with the aid of Intuitionistic fuzzy Logic based decision making. These cluster heads are responsible for collecting and integrating the data received from cluster nodes. The integrated data packets are transferred to the base station using Intuitionistic fuzzy inference engine for improved load balancing, in case of high traffic and presence of collision detection. The simulation results demonstrate that this approach is more effective in protracting network lifespan, because in WSN, it finds the optimal shortest route, and, during vagueness while electing both cluster heads, the degree of indeterminacy is considered.
Keywords: Wireless Sensor Networks, Energy Consumption, Trust Aware, Cluster Head Selection, Intuitionistic Fuzzy Logic, Uncertainty, Indeterminacy.
Scope of the Article: Wireless ad hoc & Sensor Networks