A Novel Bio-Inspired Hybrid Algorithm (NBIHA) for Efficient Resource Management in Fog Computing

Rafique, Hina, Shah, Munam Ali, Islam, Saif Ul, Maqsood, Tahir, Khan, Suleman and Maple, Carsten (2019) A Novel Bio-Inspired Hybrid Algorithm (NBIHA) for Efficient Resource Management in Fog Computing. IEEE Access, 7. pp. 115760-115773. ISSN 2169-3536

[img]
Preview
Text
08746271.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (2MB) | Preview
[img]
Preview
Text
08746271.pdf - Accepted Version
Available under License Creative Commons Attribution.

Download (4MB) | Preview
Official URL: https://doi.org/10.1109/ACCESS.2019.2924958

Abstract

Fog computing has emerged as a revolutionary paradigm to serve massive data in the Internet of Things (IoT) environment. It is a derivative of cloud computing that provides cloud-like services at the edge of the network. Subsequently, it resolves the significant issue of higher delay faced in cloud-IoT paradigm. According to the literature, the inefficient scheduling of users tasks in fog computing may result in higher delays in comparison to cloud computing. Hence, the real benefits of fog computing can only be obtained by applying effective job scheduling strategies. In fact, task scheduling is an NP-hard problem that cannot be solved by any specific algorithm to reach an ideal solution. Hence, it requires the optimal and efficient techniques to cater to the issues of latency, response time and efficient resource utilization of the available fog resources at the edge of the network. Given this, we proposed a novel bioinspired hybrid algorithm (NBIHA) which is a hybrid of modified particle swarm optimization (MPSO) and modified cat swarm optimization (MCSO). In the proposed scheme, MPSO is used to schedule the tasks among fog devices and the hybrid of MPSO and MCSO is used to manage resources at the fog device level. In the proposed approach, the resources are assigned and managed on the basis of the demand of incoming requests. The main objective of the proposed work is to reduce the average response time and to optimize resource utilization by efficiently scheduling the tasks and managing available fog resources. The simulations are carried out using iFogSim. The evaluation results show that the proposed approach (NBIHA) shows promising results in terms of energy consumption, execution time and average response time in comparison to the state-of-the-art scheduling techniques.

Item Type: Article
Uncontrolled Keywords: Cloud Computing, Edge Computing, Fog Computing, Bio-Inspired Algorithms, Task Scheduling, Resource Management
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Paul Burns
Date Deposited: 25 Jul 2019 12:13
Last Modified: 11 Oct 2019 13:02
URI: http://nrl.northumbria.ac.uk/id/eprint/40159

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics


Policies: NRL Policies | NRL University Deposit Policy | NRL Deposit Licence