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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Oyediran, Mayowa O.
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Computer Science & IT Electrical & Electronics Engineering

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Comprehensive review of load balancing in cloud computing system Oyediran, Mayowa O.; Ojo, Olufemi S.; Ajagbe, Sunday Adeola; Aiyeniko, Olukayode; Chima Obuzor, Princewill; Adigun, Matthew Olusegun
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3244-3255

Abstract

Load balancing plays a critical role in optimizing resource utilization and enhancing performance in cloud computing systems. As cloud environments grow in scale and complexity, efficient load balancing mechanisms become increasingly vital. This paper presents a comprehensive review of load balancing techniques in cloud computing systems, with a focus on their applicability, advantages, and limitations. The review encompasses both static and dynamic load balancing approaches, evaluating their effectiveness in addressing the challenges posed by cloud infrastructure, such as heterogeneity, scalability, and variability in workload demands. Furthermore, the review examines load balancing algorithms considering factors such as resource utilization, response time, fault tolerance, and energy efficiency. Additionally, the impact of load balancing on cloud performance metrics, including throughput, latency, and scalability, is analyzed. This review aims to provide insights into the state-of-the-art load balancing strategies and serve as a valuable resource for researchers, practitioners, and system designers involved in the development and optimization of cloud computing systems.
Comparative analysis of selected optimization algorithms for mobile agents’ migration pattern Oyediran, Mayowa O.; Ajagbe, Sunday Adeola; Ojo, Olufemi S.; Elegbede, Adedayo Wasiat; Adio, Michael Olumuyiwa; Adeniyi, Abidemi Emmanuel; Adebayo, Isaiah O.; Obuzor, Princewill Chima; Adigun, Matthew Olusegun
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 1: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i1.pp685-693

Abstract

Mobile agents are agents that can migrate from host-to-host to work in a heterogeneous network environment. A mobile agent can migrate from host-to-host in its plan with the statistics generated on each host through a route known as migration pattern. Migration pattern therefore is the route the agents use to travel within the plan from the first host to the last host. However, there is a need for a comparison between the commonly used optimization algorithms in developing migration patterns for mobile agents with respect to some evaluation metrics. In this paper, the three techniques firefly algorithm (FFA), honeybee optimization (HBO) and particle swarm optimization (PSO) were used for developing migration patterns for mobile agents and their comparison was done based on migration time, time complexity and network load as metrics. PSO is discovered to perform better in terms of network load with an average of 242.3905 bits per second (bps), time complexity with an average of 41.2688 number of nodes (n), and migration/transmission time with an average of 4.203462 seconds (s).
Co-Authors Adebayo, Isaiah O. Adeniyi, Abidemi Emmanuel Adigun, Matthew Olusegun Adio, Michael Olumuyiwa Aiyeniko, Olukayode Ajagbe, Sunday Adeola Chima Obuzor, Princewill Elegbede, Adedayo Wasiat Obuzor, Princewill Chima Ojo, Olufemi S.