Description

The emerging technology of wireless sensor network (WSN) is expected to provide a broad range of applications, such as battlefield surveillance, environmental monitoring, and smart spaces and so on. Sensing coverage and network connectivity are two of the most fundamental problems in wireless sensor networks. Sensor networks are used in numerous application environmental monitoring, power grids, etc. Large-scale sensor networks are deployed in numerous application domains, and the data they collect are used in decision making for critical infrastructures. Data are streamed from multiple sources through intermediate processing nodes that aggregate information. Data are produced at a large number of sensor node sources and processed in-network at intermediate hops on their way to a base station (BS) that performs decision-making. The diversity of data sources creates the need to assure the trustworthiness of data, such that only trustworthy information is considered in the decision process. Finding an optimal node deployment strategy that would minimize cost, reduce computation and communication overhead, be resilient to node failures, and provide a high degree of coverage with network connectivity is extremely challenging. This project proposed two heuristic algorithms to reduce the total movement distance of sensors.