Research Area:  Fog Computing

Abstract:

In recent years, large computational problems have beensolved by the distributed environment in which applications are executed in parallel. Also, lately, fog computing or edge computing as a new environment is applied to collect data from the devices and preprocessing is done before sending for main processing in cloud computing. Since one of the crucial issues in such systems is task scheduling, this issue is addressed by considering reducing energy consumption. In this study, an energy-aware method is introduced by using the Dynamic Voltage and Frequency Scaling (DVFS) technique to reduce energy consumption. In addition, in order to construct valid task sequences, a hybrid Invasive Weed Optimization and Culture (IWO-CA) evolutionary algorithm is applied. The experimental results revealed that the proposed algorithm improves some current algorithms in terms of energy consumption.

Keywords:  

Author(s) Name:  Pejman Hosseinioun,Maryam Kheirabadi,Seyed Reza Kamel Tabbakh,Reza Ghaemi

Publisher name:  Elsevier

DOI:  10.1016/j.jpdc.2020.04.008

Volume Information:  Volume 143, September 2020, Pages 88-96

Paper Link:   https://www.sciencedirect.com/science/article/abs/pii/S074373152030023X