Description

With the explosive development of microelectronics and wireless communication in recent decades, wire-less sensor networks (WSNs) have been one of the most active fields in research community. Wireless micro sensor networks have been identified as one of the most important technologies. Most of the wireless sensor networks consist of static sensors, which can be deployed in a wide environment for monitoring applications. While performing data transmission through multiple hops become less reliable. The data collection technique is used to collect the aggregate data from the sensor node to the sink node. The main objective of the data collection process is to reduce the delay and improves the network’s lifetime. Data collection by multiple sinks is a fundamental problem in wireless sensor networks. Existing works focused on designing the optimal offline methods provided that the number and positions of sensors and sinks (or trajectories of mobile sinks) are predetermined. This may not be practical as, though sensors are cheap, sinks are quite expensive in reality. A more practical scenario is that sinks are deployed step by step during the network operation due to the budget constraint, and we do not know the number, positions and capacities of sinks in prior. To achieve high efficiency than the target tracking, the proposed system design a suboptimal online algorithm by investigate the problem of data collection by multiple sinks. This framework evaluate the network loss probability performance which requires only local information for collecting data. Simulation show better performance than the existing methods in terms of its metrics.