Amoeba-Like Exploring for Grouped Mobile Wireless Sensor Networks

Mobile wireless sensor networks may be applied to diverse areas, and have been receiving increasingly attentions. However, these studies do not seem to address the issue regarding how group of mobile sensor nodes move autonomously, explore and monitor area of interest without exploiting geographic information. Accordingly, this paper develops two amoeba-like algorithms, folding and elastic algorithms, to cope with the above mentioned problem. Folding algorithm operates by assigning some mobile sensor node stay in each intersection, so that it can guide and coordinate the movement of the whole group. Elastic algorithm selects a cluster head for commanding movement directions of the remaining nodes to collect necessary geographic information and determine the subsequent movements. Simulations are conducted to evaluate the two proposed algorithms.