Open Access

ARTICLE

Survey of Resources Allocation Techniques with a Quality of Service (QoS) Aware in a Fog Computing Environment

Wan Norsyafizan W. Muhamad¹, Kaharudin Dimyati², Muhammad Awais Javed³, Suzi Seroja Sarnin^1,*, Divine Senanu Ametefe¹

1 School of Electrical Engineering, College of Engineering, University Teknologi Mara, 40450, Shah Alam, Selangor, Malaysia
2 Department of Electrical Engineering, Faculty of Engineering, University Malaya, 50603, Kuala, Lumpur, Malaysia
3 Department of Electrical and Computer Engineering, COMSATS University Islamabad, 45550, Pakistan

* Corresponding Author: Suzi Seroja Sarnin. Email:

(This article belongs to the Special Issue: Innovations in Pervasive Computing and Communication Technologies)

Computers, Materials & Continua 2023, 76(1), 1291-1308. https://doi.org/10.32604/cmc.2023.037214

Received 27 October 2022; Accepted 08 February 2023; Issue published 08 June 2023

Abstract

The tremendous advancement in distributed computing and Internet of Things (IoT) applications has resulted in the adoption of fog computing as today’s widely used framework complementing cloud computing. Thus, suitable and effective applications could be performed to satisfy the applications’ latency requirement. Resource allocation techniques are essential aspects of fog networks which prevent unbalanced load distribution. Effective resource management techniques can improve the quality of service metrics. Due to the limited and heterogeneous resources available within the fog infrastructure, the fog layer’s resources need to be optimised to efficiently manage and distribute them to different applications within the IoT network. There has been limited research on resource management strategies in fog networks in recent years, and a limited systematic review has been done to compile these studies. This article focuses on current developments in resource allocation strategies for fog-IoT networks. A systematic review of resource allocation techniques with the key objective of enhancing QoS is provided. Steps involved in conducting this systematic literature review include developing research goals, accessing studies, categorizing and critically analysing the studies. The resource management approaches engaged in this article are load balancing and task offloading techniques. For the load balancing approach, a brief survey of recent work done according to their sub-categories, including stochastic, probabilistic/statistic, graph theory and hybrid techniques is provided whereas for task offloading, the survey is performed according to the destination of task offloading. Efficient load balancing and task-offloading approaches contribute significantly to resource management, and tremendous effort has been put into this critical topic. Thus, this survey presents an overview of these extents and a comparative analysis. Finally, the study discusses ongoing research issues and potential future directions for developing effective management resource allocation techniques.

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Keywords

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