An Energy-Consumption Based Connected K-Neighborhood Algorithm For Duty-cycled Wireless Sensor Networks

To prolong the lifetime of a wireless sensor network, one common approach is to dynamically schedule sensors’active/sleep cycles (i.e., duty cycles) using sleep scheduling algorithms. The connected K-neighborhood (CKN) algorithm is an efficient decentralized sleep scheduling algorithm for reducing the number of awake nodes while maintaining both network connectivity and an on-demand routing latency.In this paper, we investigate the unexplored energy consumption of the CKN algorithm by building a probabilistic node sleep model, which computes the probability that a random node goes to sleep. Based on this probabilistic model, we obtain a lower epoch bound that keeps the network more energy efficient with longer lifetime when it runs the CKN algorithm than it does not. Furthermore, we propose a new sleep scheduling algorithm, namely, Energy-consumption-based CKN (EC-CKN), to prolong the network lifetime. The algorithm EC-CKN, which takes the nodes’residual energy information as the parameter to decide whether a node to be active or sleep, not only can achieve the k-connected neighborhoods problem, but also can assure the k-awake neighbor nodes have more residual energy than other neighbor nodes in current epoch.In the simulation, we use NetTopo simulator to measure the performance of the CKN algorithm and the EC-CKN algorithm. It reveals the fact that waking up more sensor nodes cannot always help to improve the exploration results of TPGF in a duty-cycle based WSN. Furthermore, the EC-CKN algorithm could consume the energy more balancedly, and achieve longer network lifetime.