On-line adaptive compression in delay sensitive wireless sensor networks

Compression, as a popular technique to reduce data size by exploiting data redundancy, can be used in delay sensitive wireless sensor networks (WSNs) to reduce end-to-end packet delay as it can reduce packet transmission time and contention on the wireless channel. However, the limited computing resources at sensor nodes make the processing time of compression a nontrivial factor in the total delay a packet experiences and must be carefully examined when adopting compression. In this paper, we first study the effect of compression on data gathering in WSNs under a practical compression algorithm. We observe that that compression does not always reduce the packet delay in a WSN as commonly perceived, whereas its effect is jointly determined by the network configuration and hardware configuration. Based on this observation, we design an adaptive algorithm to make on-line decisions such that compression is only performed when it can benefit the overall performance. We implement the algorithm in a completely distributed manner that utilizes only local information of individual sensor nodes. Our extensive experimental results show that the algorithm demonstrates good adaptiveness to network dynamics and maximizes compression benefit.