Priced Timed Petri Nets Based Resource Allocation Strategy for Fog Computing

This paper proposes a resource allocation strategy for fog computing based on Priced Timed Petri nets (PTPN), by which the user can choose the satisfied resources autonomously from a group of pre-allocated resources according to the price cost and time cost of task. We construct the PTPN models of tasks in fog computing in accordance with the features of fog resources. The algorithm of predicting task completion time and price is presented. In particular, we give the fog resources dynamic allocation algorithm. Simulation results demonstrate that our proposed algorithms can achieve the higher efficiency.