Data sharing for data collection among multiple applications is an efficient way to reduce communication cost for Wireless Sensor Networks (WSNs). This paper is the first work to introduce the interval data sharing problem which is to investigate how to transmit as less data as possible over the network, and meanwhile the transmitted data satisfies the requirements of all the applications. Different from current studies where each application requires a single data sampling during each task, we study the problem where each application requires a continuous interval of data sampling in each task. The proposed problem is a nonlinear nonconvex optimization problem. Get more projects ideas from the industry experts In order to lower the high complexity for solving a nonlinear nonconvex optimization problem in resource restricted WSNs, a 2-factor approximation algorithm whose time complexity is Oðn2Þ and memory complexity is OðnÞ is provided. A special instance of this problem is also analyzed. This special instance can be solved with a dynamic programming algorithm in polynomial time, which gives an optimal result in Oðn2Þ time complexity and OðnÞ memory complexity.
Three online algorithms are provided to process the continually coming tasks. Both the theoretical analysis and simulation results demonstrate the effectiveness of the proposed algorithms