A New Task Offloading Scheme for Geospatial Fog Computing Environment Using M/M/C Queueing Approach

Geospatial fog computing became an interesting paradigm to support delay-sensitive jobs in Internet of Spatial Things (IoST) for geospatial applications by offering scalable, shared, and computational resources in addition to geospatial cloud services. The delay-sensitive jobs are offloaded in geospatial fog computing environment for reducing overall communication time. Contrarily, a good offloading technique selects a suitable computing device in terms of a fog node according to the task’s resource needs while meeting the deadline. This article proposes a new offloading technique for scheduling and processing activities generated by IoST devices to appropriate computing devices. M/M/c queueing model is used to model the system and find the optimized number of virtual machines to be activated in the fog layer for active processing of the offloaded tasks. This schema decreases the delay-sensitive tasks queue waiting time and optimizes the required number of VMs in the fog layer. The efficacy of the proposed technique is validated with the help of simulation results.