A lightweight classification algorithm for energy conservation in wireless sensor networks

Abstract

Classification of sensor nodes can be used as a technique for conserving energy and prolonging the lifetime of a wireless sensor network (WSN). In this paper, we present a new algorithm of lightweight and dynamic classification. By this algorithm, energy consumption is reduced while providing a full coverage, which is an important network parameter in WSNs. Moreover, node classification is adaptive to topology changes and has no constraint on routing protocols and hardware. Based on sensors residual energy, they are classified as essential and non-essential and rotated dynamically. Essential nodes send their measurements to the sink, whereas, non-essential ones do not send new data and receive queries from the sink. This reduces transmitting and receiving energy of non-essential nodes and regulates data traffic. Further, our mechanism may provide location-based tunable redundancy, e.g., if redundant data is needed from a specific region, the sink may query the corresponding essential nodes to activate non-essential ones in that region. We analyze the complexity and energy consumption for the scenario where nodes are randomly deployed in a given region. Analysis, supported by extensive simulation in ns2, shows that energy consumption due to communications can be reduced in proportional to the ratio of essential nodes and fairly distributed among sensors by rotation.