Multi-Level Parameter Processed Model to Optimise Clustered Distributed WBAN

Abstract

Numerous individuals can be monitored continuously for their physical or health updates such as the comma patient ward in a hospital or the autistic patients. A distributed Wireless Body Area Network (WBAN) forms a wide network with multiple WBANs situated in the same geographical location. Each WBAN has the individual handheld or controller device, and the region has single region control base station. The symmetric featured WBANs update the information to the base station. The small coverage and heavy parallel communication cannot ensure the direct access of the base station to each WBAN. The clustered WBAN architecture is applied in this paper to resolve these primary issues. The proposed improved architecture includes a multi-level and multi-featured evaluation for cluster generation and hierarchical routing over the network. The coverage, energy, load, density and degree parameters are applied selectively at different levels to optimise the cluster controller selection, cluster member identification and communication. The ACO (Ant Colony Optimization) integrated parametric method is applied to generate the multihop hierarchical route between nodes to the base station. The proposed architectural framework is simulated on multiple scenarios under WBAN level scalability. The comparative results are generated against the energy adaptive clustering method, LEACH (Low-Energy Adaptive Clustering Hierarchy) and gateway based energyefficient routing protocol (M-GEAR). The evaluation results verified that the proposed architecture has reduced the energy consumption and improved the network life, energy utilisation, and packet communication effectively.