A Genetic Algorithm Approach to Multi-Agent Itinerary Planning in Wireless Sensor Networks
It has been shown recently that using Mobile Agents (MAs) in Wireless Sensor Networks (WSNs) can help to achieve the flexibility of over-the-air software deployment on demand. In MA-based WSNs, it is crucial to find out an optimal itinerary for an MA to perform data collection from multiple distributed sensors. However, using a single MA brings up the shortcomings such as large latency, inefficient route, and unbalanced resource (e.g. energy) consumption. Then a novel Genetic Algorithm based Multi-agent Itinerary Planning (GA-MIP) scheme is proposed to address these drawbacks. The extensive simulation experiments show that GA-MIP performs better than the prior single agent algorithms in terms of the product of delay and energy consumption.