Periodic Query Optimization Leveraging Popularity-Based Caching in Wireless Sensor Networks for Industrial IoT Applications

摘要: With the rapid development of Internet Things (IoT), billions smart devices should be available for sensing environment variables and reporting events periodically that may happen in certain regions, supporting industrial applications. It is usual contiguous queries on point-of-interests have some region overlapping. In this setting, sensory data retrieved by recent beneficial answering forthcoming, when these are fresh enough. To address challenge, we propose a popularity-based caching strategy optimizing periodic query processing. Specifically, network divided using cell-based manner, where each grid cell abstracted as an elementary unit purpose. Fresh cached memory sink node. The popularity cells calculated leveraging conducted time slots, which reflects possibility covered forthcoming. Prefetching performed with higher degree missed cache. These used facilitating afterwards. simulation results show our approach can reduce communication cost significantly increase capability.