Design of load-aware resource allocation for heterogeneous fog computing systems

Syed Rizwan Hassan; Ateeq Ur Rehman; Naif Alsharabi; Salman Arain; Asim Quddus; Habib Hamam

doi:10.7717/peerj-cs.1986

Design of load-aware resource allocation for heterogeneous fog computing systems

PeerJ Comput Sci. 2024 Apr 18:10:e1986. doi: 10.7717/peerj-cs.1986. eCollection 2024.

Authors

Syed Rizwan Hassan^#¹, Ateeq Ur Rehman^#², Naif Alsharabi^{3

4}, Salman Arain¹, Asim Quddus⁵, Habib Hamam^{6

7

8

9}

Affiliations

¹ Department of Electrical Engineering, Institute of Engineering and Fertilizer Research, Faisalabad, Pakistan.
² School of Computing, Gachon University, Seongnam, Republic of Korea.
³ College of Computer Science and Engineering, University of Ha'il, Ha'il, Saudi Arabia.
⁴ College of Engineering and Information Technology, Amran University, Amran, Yemen.
⁵ Department of Electronics Engineering, University of Chakwal, Chakwal, Pakistan.
⁶ International Institute of Technology and Management, Commune d'Akanda, Libreville, Gabon.
⁷ School of Electrical Engineering, Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg, South Africa.
⁸ Centre Ville, Bridges for Academic Excellence, Tunis, Tunisia.
⁹ Faculty of Engineering, Université de Moncton, Moncton, Canada.

^# Contributed equally.

Abstract

The execution of delay-aware applications can be effectively handled by various computing paradigms, including the fog computing, edge computing, and cloudlets. Cloud computing offers services in a centralized way through a cloud server. On the contrary, the fog computing paradigm offers services in a dispersed manner providing services and computational facilities near the end devices. Due to the distributed provision of resources by the fog paradigm, this architecture is suitable for large-scale implementation of applications. Furthermore, fog computing offers a reduction in delay and network load as compared to cloud architecture. Resource distribution and load balancing are always important tasks in deploying efficient systems. In this research, we have proposed heuristic-based approach that achieves a reduction in network consumption and delays by efficiently utilizing fog resources according to the load generated by the clusters of edge nodes. The proposed algorithm considers the magnitude of data produced at the edge clusters while allocating the fog resources. The results of the evaluations performed on different scales confirm the efficacy of the proposed approach in achieving optimal performance.

Keywords: Cloud computing; Fog computing; Load aware; Resource allocation.

Grants and funding

The Natural Sciences and Engineering Research Council of Canada (NSERC) and New Brunswick Innovation Foundation (NBIF) financially supported this global project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.