Protocol for reliable energy data collection based on mobile fog computing

Abstract

Fog computing can quickly calculate and store user needs, and cooperate with remote cloud computing to provide more powerful computing capabilities. In this paper, the passive cache is optimized, and the Dynamic Cooperate Proactive Cache (DCPC) algorithm based on user mobility is proposed, which uses user movement information and request records collected by the fog server node to cache the content on the fog server node in advance. The algorithm combines the autoregressive differential moving average model to actively predict the requested content, which greatly improves the utilization of cache space. This paper proposes a wireless sensor network based on Lo Ra WAN to collect energy impact factors. In order to greatly extend the survival time of sensor networks, this paper proposes a data collection method based on the division of similar attribute regions. By selecting representative nodes and turning off redundant nodes, the sensor can be greatly improved while ensuring high accuracy of collected data. After system testing and simulation experiments, it is verified that the wireless sensor network developed in this paper can meet the collection requirements of energy impact factors, and the data collection method proposed can greatly extend the survival time of the sensor network.