Memoization based priority-aware task management for QoS provisioning in IoT gateways

Abstract

Fog computing is a paradigm that works in tandem with cloud computing. The emergence of fog computing has boosted cloud-based computation, especially in the case of delay-sensitive tasks, as the fog is situated closer to end devices such as sensors that generate data. While scheduling tasks, the fundamental issue is allocating resources to the fog nodes. With the ever-growing demands of the industry, there is a constant need for gateways for efficient task offloading and resource allocation, for improving the Quality of Service (QoS) parameters. This paper focuses on the smart gateways to enhance QoS and proposes a smart gateway framework for delay-sensitive and computation-intensive tasks. The proposed framework has been divided into two phases: task scheduling and task offloading. For the task scheduling phase, a dynamic priority-aware task scheduling algorithm (DP-TSA) is proposed to schedule the incoming task based on their priorities. A Memoization based Best-Fit approach (MBFA) algorithm is proposed to offload the task to the selected computational node for the task offloading phase. The proposed framework has been simulated and compared with the traditional baseline algorithms in different test case scenarios. The results show that the proposed framework not only optimized latency and throughput but also reduced energy consumption and was scalable as against the traditional algorithms.