Towards Scalability of the IoT Search Engine

With the rapid development of the Internet of Things (IoT), the need for a search engine in IoT systems is critical to reducing redundancy in IoT deployments and enabling collected data to be shared and leveraged across IoT systems and applications. Despite recent research efforts that have been conducted on IoT search engines, the scalability of such a system remains an unresolved issue. In this paper, we propose a cluster-based search system to improve the scalability of IoT search systems, enabling them to cope with increasingly large search workloads. To efficiently use cluster resources, we design a Lowest Utilization First (LUF) algorithm for sharing search loads among cluster nodes. Moreover, we have conducted a series of emulation-based studies, and the results demonstrate the efficiency of our proposed system in terms of the amounts of successfully processed search queries in different scenarios. In addition, we discuss some remaining issues for future study.