Social insect communities are formed from simple, autonomous, and cooperative organisms that are interdependent for their survival. These communities are able to effectively coordinate themselves to achieve global objectives despite a lack of centralized planning. This chapter presents a study of artificial insect algorithms for routing in wireless sensor networks, with a specific focus on simulating termites and their behaviours in their colony. The simulating behaviour demonstrates how the termites make use of an autocatalytic behaviour in order to collectively find a solution for a posed problem in reasonable time. The derived algorithm termed Termite-Hill demonstrates the principle of the termite behavior for solving the routing problem in wireless sensor networks. The performance of the algorithm was tested on static and dynamic sink scenarios. The results were compared with other routing algorithms with varying network density and showed that the proposed algorithm is scalable and improved on network energy consumption with a control over best-effort service.
|Title of host publication||Emerging research on Swarm intelligence and algorithm optimization|
|Editors||Yuhui Shi, Xi'an Jioatong|
|Place of Publication||Hershey, Pennsylvania, USA|
|Number of pages||23|
|Publication status||Published - 2015|
|Name||Advances in Computational Intelligence and Robotics (ACIR) Book Series|