A Bio-inspired Load Balancing Using PheromoneWireless Sensor NetworksSignalling Technique for

Wireless Sensor Networks (WSNs) consist of multiple distributed nodes each withlimited resources. With their strict resource constraints and application-speci_ccharacteristics, WSNs contain many challenging trade-o_s. This thesis is concernedwith the load balancing of Wireless Sensor Networks (WSNs). We present an approach,inspired by bees pheromone propagation mechanism, that allows individualnodes to decide on the execution process locally to solve the trade-o_ between serviceavailability and energy consumption. We explore the performance consequencesof the pheromone-based load balancing approach using a system-level simulator.The e_ectiveness of the algorithm is evaluated on case studies based on sound sensorswith di_erent scenarios of existing approaches on variety of di_erent networktopologies. The performance of our approach is dependant on the values chosenfor its parameters. As such, we utilise the Simulated Annealing to discover optimal parameter con_gurations for pheromone-based load balancing technique forany given network schema. Once the parameter values are optimised for the givennetwork topology automatically, we inspect improving the pheromone-based loadbalancing approach using robotic agents. As cyber-physical systems bene_t fromthe heterogeneity of the hardware components, we introduce the use of pheromonesignalling-based robotic guidance that integrates the robotic agents to the existingload balancing approach by guiding the robots into the uncovered area of the sensor_eld. As such, we maximise the service availability using the robotic agents as wellas the sensor nodes.