Entropy‐based complex proportional assessment for efficient task scheduling in fog computing

Abstract

AbstractThe tasks are offloaded to fog computing instead of cloud computing to enhance the quality of service (QoS) of internet of things (IoT) applications. Though it provides improved QoS the accessibility of unremitting computation properties of fog servers is one among the limitations of IoT applications as transmitting a huge quantity of data may induce more energy consumption, cost, and increased makespan. Much research has been made to build up an efficient technique to address the multi–objective task scheduling in fog computing. One such method used to solve multiple objective problems in different domains is multi–criteria decision–making methods (MCDM). The MCDM Method named complex proportional assessment (COPRAS) has risen in popularity due to simple and fast computation. In this paper, a task scheduling algorithm (ECOPRAS) based on the integration of the entropy weight method and COPRAS method is proposed. The proposed technique consists of two phases that is, Task prioritization, and Task assignment. In the first phase, the task is ordered based on the heuristic method, B‐level and in the second phase, the task will be assigned based on the ranking provided by the ECOPRAS method. The proposed method aims at minimizing energy consumption, price, and makespan and maximizing the reliability and utilization rate. The simulation results are compared with similar algorithms through various workflows and the proposed method outperforms well.