Vertical and Horizontal Compression Scheme Assessment in Cluster-Based WSNs

Energy consumption is the major constraint in wireless sensor networks deployment. Since the radio communication is the main motif of energy expenditure, data compression is an appealing tool to reduce the energy dissipated in the transmission of collected information by discarding the data redundancy. Furthermore, clustering is one of the crucial energy efficient routing architectures, employed to manage the communication burden. In this paper, the energy performance of cluster-based network is investigated using compression approaches in two compression dimensions distinctly: a horizontal compression is implemented in sensor nodes level using lightweight compression algorithms. However, a vertical compression is used in the Cluster-Head level, based on a similarity function. Combining these two compression techniques leads to an efficient energy saving in cluster-based routing networks using real-world sensor datasets.