Priority-Queue based Dynamic Scaling for Efficient Resource Allocation in Fog Computing

Abstract

In this emerging world of connected devices, the need for more computing devices with a focus on the delay-sensitive application is critical. In this paper, we propose a priority-queue based Fog computing architecture that dynamically allocates fog nodes based on system load. Also, task allocation is performed based on priority. This not only reduces the delay experienced by delay-sensitive tasks by categorizing the delay-sensitive and delay-insensitive tasks but also dynamically allocates the fog devices within the network depending upon the computation load for reducing the power consumption. The results show that the proposed algorithm is able to achieve significantly lower delay for delay-sensitive tasks for larger rates of tasks arrival when compared with other related schemes along with a 12.7% lower power consumption for a given range of rate of tasks arrival.