Efficient Resource Preservation through Data Compression in Wireless Sensor Networks

One possible way to achieve maximum utilization of resources in Wireless sensor networks (WSN) is to apply data compression on sensed data. However, classical compression algorithms are not applicable for sensor nodes because of their limited resources. The proposed compression framework shifts the data compression of sensed data into a dedicated layer and compresses the payload as well as the packet header. The framework splits sensed data from application into two halves, header and payload. HC1 (Header compression 1) encoding is performed to compress the header and simple stream based encoding is applied on the payload to achieve potential resource saving. The simplicity of proposed payload encoding scheme also potentially overcomes the frequent memory access that exists in the former encoding scheme and ensures maximum resource utilization of WSNs. IP is utilized in the compression framework through 6LowPAN adaptation layer so that sensing services can be provided at global scale.