Work-in-Progress: Pricing Mechanism and Workload Scheduling to Optimize Social Welfare and Cost for Fog Computing Systems

Abstract

Fog computing is a non-trivial extension of cloud computing to overcome many inherent limitations, such as huge network bandwidth and high latency. Fog computing involves a significantly large number of fog instances, unlike few centralized cloud servers. This work is an attempt to address two crucial challenges in fog computing systems in an integrated manner, namely the pricing of the resources and offloading of real-time tasks to appropriate fog instances. We propose an integrated framework to devise the pricing of the resources to maximize the social welfare and an offloading mechanism to minimize the cost of execution of the workloads with the timing constraint.