Runtime optimisation in WSNs for load balancing using pheromone signalling

Abstract

Wireless Sensor Networks (WSNs) consist of multiple, distributed nodes each with limited resources. With their strict resource constraints and application-specific characteristics, WSNs contain many challenging trade-offs. This paper proposes a bio-inspired load balancing approach, based on pheromone signalling mechanisms, to solve the trade-off between service availability and energy consumption. We explore the performance consequences of the pheromone-based load balancing approach using: 1) a system-level simulator; 2) deployment of real sensor testbeds to provide a competitive analysis of these evaluation methodologies. The effectiveness of the proposed algorithm is evaluated with different scenario parameters and the required performance evaluation techniques are investigated on case studies based on sound sensors.