Distributed scheduling for K-level probabilistic coverage and connectivity in WSNs

Coverage and connectivity are both attractive issues in wireless sensor networks. They are important measurements of quality of service (Qos). Among the existing researches, probabilistic detection model used in coverage configuration meets the actual signal decay sensing characteristic of the sensor node well. Based on this model, our previous work has presented a simplified coverage checking eligible rule and proposed a simple scheduling scheme about the network coverage and connectivity. However there are some drawbacks in the previous scheme, such as high computing time complexity, uneven distribution of active nodes and poor robustness to communication range. In this paper, a K-level probabilistic coverage and connectivity scheduling protocol (KPCCP) is proposed. The distributed parallel computing method is used by KPCCP, which can effectively shorten the scheduling time. The restricted coverage level parameter K is adopted in order to control the density and distribution of active nodes. The network connectivity configuration is also implemented by a distribution judgment method. Simulations and analysis show us that KPCCP outperforms than the previous work in aspects of computing time complexity, nodes distribution in network and robustness to the communication range.