A New Self-Management Model for Large-Scale Event-Driven Wireless Sensor Networks

Event-driven wireless sensor networks (WSNs) are equipped with the sensor nodes which are able to capture the vital changes in the measurements and report them to the base station. Due to the nature of harsh and unattended environments, it is impossible to install sensor nodes manually. Therefore, a random deployment fashion such as by aircraft is required. However, with high probability, sensor nodes will not have uniform distribution in the environment which will cause “hole” in the network. In another issue, sensor nodes are limited in energy supply and transmission range, and thus an appropriate technique is essential to calculate energy efficient routes to relay data from the sensor nodes to the base station. In hierarchical routing category, clustering techniques attempt to partition the sensor nodes in the network to appropriate groups and select the cluster heads to contact with the base station directly. However, in large scale WSNs, most of the sensor nodes are far from the base station and cannot contact directly. Most of the clustering techniques do not consider how cluster heads can reach to the base station. In our research, A Delaunay triangulation approach is employed to detect holes in the network. Then, due to the overhead of clustering methods to define cluster areas, a virtual gridding scheme is applied to define cluster areas. To overcome uncertainties in the environment, a fuzzy logic-based approach is designed to select appropriate cluster heads and hop-nodes in a distributed manner. The experimental results prove the effectiveness and accuracy of our proposed model and applicability to large scale WSNs.