A distributed sensor network (DSN) consists of intelligent sensors that are geographically dispersed in a region of interest and interconnected via a communication network. The sensed data of different types (such as acoustic, seismic, and infrared, etc.) are preprocessed by sensor nodes and then transmitted over the network to participate in the data integration at processing elements, based on which appropriate inferences can be derived about the environment for certain purposes. The study of information fusion methods has been the research focus since the early stage of DSN development [3-5]. Recent advances in sensor technologies make it possible to deploy a large number of inexpensive and small sensors to “achieve quality through quantity” in very complex scenarios, which necessitates applying new computing techniques such as genetic algorithms (GAs) to meet some theoretical and methodological challenges. This chapter provides a general introduction to GAs and their application to the mobile agent routing problem in a DSN with a special networking paradigm.
