Efficient Data Collection with Sampling in WSNs: Making Use of Matrix Completion Techniques

Data collection is of paramount importance in many applications of wireless sensor networks (WSNs). Especially, to accommodate ever increasing demands of signal source coding applications, the capacity of processing multi-user data query is crucial in WSNs where the efficiency is one key consideration. To that end, this paper presents EDCA: an Efficient Data Collection Approach for data query in WSNs, which exploits recent matrix completion techniques. Specifically, for the efficiency of energy consumption, we randomly select a part of nodes from the sensor network to sample at each time instance and directly forward the data to the sink. Then, to recover the data precisely, we shift the rank minimization problem, which is NP-hard, to a convex optimization one. Compared with the centralized scheme, energy consumption using EDCA is significantly reduced due to lower sampling rate and fewer packets to transmit. The experimental results demonstrate that EDCA significantly outperforms the existing naive method in terms of energy consumption and the introduced errors are quite trivial.