Abstract
Shared wireless sensor network is a popular solution nowadays for reducing deployment cost. Sensors in it are shared to multiple applications. Meanwhile, they suffer more workload to satisfy more tasks from these applications. Fortunately, sharing data to multiple tasks is useful to decrease workload, as long as a shared sensor can collect data efficiently. Our study focuses on interval sampling problem, each task in which need a continuous interval of data sampling during its tasks duration. It is different from the data collect problem in the past studies, which only need single data sampling for each task. We design a light weight algorithm to collect data efficiently for a sensor. The time complexity and memory complexity of it are O(n^2) and O(n), respectively, and it has a theoretic bound, which is 4logn+1. The effectiveness of our algorithm is proved in theoretical analysis. The experimental results also show that our algorithm outperforms the greedy algorithm proposed by [11] on different types of instances.