Research Area: Wireless Sensor Networks
Wireless Sensors Network (WSN) is used for monitoring and recording the physical environment and to transfer the sensed data to a central location by means of widely distributed sensor nodes. One of the major issues with WSNs is limited energy of sensor nodes and high energy consumption during data relay. An energy efficient routing protocol that consumes less energy in data transmission can enhance the network lifetime to a great extent. Considering it, this paper presents, a hierarchical routing protocol Fuzzy Multi-criteria Clustering and Bio-inspired Energy-efficient Routing (FMCB-ER) to enhance network lifetime thus improving upon the operational time of WSN based applications. Here in this approach a grid-based clustering technique is used to form the robust clusters. An adaptive Fuzzy Multi-Criteria Decision-Making (AF-MCDM) that combines Fuzzy-AHP and TOPSIS is then applied for optimum cluster head (CH) selection. For the purpose, the approach considers three broad parameters namely, energy, QoS and node position along with their six sub-criteria. After CH selection, the Emperor Penguin Optimization (EPO) is used to find optimal route for data transmission from CH to sink. The proposed method is evaluated and compared with other existing routing approaches on parameters of energy consumption, lifetime, throughput, end to end delay, jitter, packet delivery ratio, latency, number of dead, alive nodes. Simulation results confirm that the proposed approach outperforms the compared approaches on above discussed parameters. Especially, the proposed approach reduces the energy consumption up to 13% and increases the network lifetime up to 8% in comparison to compared approaches.
Keywords:
Hierarchical routing protocol
Grid cluster formation
Emperor penguin optimization
Multi criteria decision making
Author(s) Name: Deepak Mehta & Sharad Saxena
Journal name: Multimedia Tools and Applications
Conferrence name:
Publisher name: Springer
DOI: 10.1007/s11042-020-09633-8
Volume Information: volume 81, pages 35083–35116 (2022)
