Towards efficient and dynamic allocations of mist nodes for IoST devices

In today’s information age, the Internet of Spatial Things (IoST) is rapidly gaining prominence. Massive amounts of geospatial data are generated by IoST and cloud environment. Mist Computing is a leveraging technology that processes geospatial big data and delivers it to the cloud storage system via fog nodes. Installing mist-assisted cloud architecture reduces latency and throughput. In this mist-assisted cloud environment, mist nodes are primarily in charge of localized collection, storage, and monitoring of IoST workload, resulting in considerable efficiency and availability. SLA and QoS compliance are two of the open topics and challenges in the realm of mist computing. To solve this issue, it provides a mathematical and analytical methodology for studying and analyzing mist computing performance. Our mathematical approach calculates the number of mist nodes required to meet QoS requirements for each given IoST demand. The model yielded formulas for system response time, loss rate, throughput, CPU utilization, and mean number of messages requested.