A redundant sensing device schedule method under event monitoring coverage constraints for edge computing

Abstract Billions of sensing devices are deployed in the smart city to generate a large amount of sensing data for various applications. However, duplicated data caused by redundant deployed sensing devices makes it a great challenge to gather data with low cost and high efficiency. In this paper, a redundant sensing device schedule method is proposed through redundant sensing device identification scheme based on device redundancy and similarity (RSDI-DRS) under event monitoring coverage constraints. The key idea of the RSDI-DRS is to reduce the number of unnecessary working sensing device to decrease energy consumption and data load. Comparing to the previous researches, the innovation of RSDI-DRS is as follows: First, a novel sensing device redundancy and similarity calculation method is proposed. Second, the network connectivity is realized by the network connectivity discrimination scheme. In the proposed scheme, the redundant device set is established by calculating the sensing device redundancy score. Then, the device similarity score is calculated for the devices in the redundant device set, and the scheduling priority of the redundant device is obtained based on the similarity score and the remaining energy of the sensing device. The device with the maximum scheduling priority is scheduled to sleep. The process loops under the satisfaction of event coverage constraint. Meanwhile, the network connectivity is realized in the process. If an isolated sensing device occurs, the neighbor device with the minimum scheduling priority will not be scheduled to sleep. Simulation results show that the proposed scheme could prolong the network life by 16.30% ~ 31.18% and realized the connectivity of working sensing devices under the event monitoring coverage at the cost of the execution time growth compared with the scheme of Relocating Redundant Sensors-Redundant Node Identification (RRS-RNI).