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Title: A Fair, Dynamic Load Balanced Task Distribution Strategy for Heterogeneous Cloud Platforms Based on Markov Process Modeling
Authors: Souravlas, Stavros
Anastasiadou, Sofia
Tantalaki, Nikoleta
Katsavounis, Stefanos
Type: Article
Subjects: FRASCATI::Engineering and technology
Keywords: Load balancing
cloud computing
Markov modeling
distributed environment
expected utilization
expected processing capacity
Issue Date: 2022
Publisher: IEEE
Source: IEEE Access
Volume: 10
First Page: 26149
Last Page: 26162
Abstract: Load balancing techniques in cloud computing can be applied at three different levels: Virtual machine load balancing, task load balancing, and resource load balancing. At all levels, load balancing should also be implemented in an efficient manner, to increase system performance. In this paper, we propose a fair, in terms of added workload per VM, task load balancing strategy, that aims to improve the average response time and the makespan of the system in the cloud environment. The problem is formulated as an irreducible finite state Markov process, which is known to have a balance equation for each state. From the balance state probabilities we derive the expected utilizations for the virtual machines (VM), which play a vital role in our task allocation approach. In our model, the Load Balancer (LBer) acts as a central server, which uses our proposed fair task allocation scheme to distribute the incoming tasks in a fair, balanced manner among the virtual machines, taking into account their current state as well as their processing capabilities. Our scheme has been compared to recent algorithms that use the particle swarm optimization and the Honey bee foraging scheme to achieve load balancing. Our experimental results show that our proposed scheme outperforms other state of the art schemes in terms of makespan, average response time, and resource utilization and provides lower degree of imbalance.
ISSN: 2169-3536
Other Identifiers: 10.1109/ACCESS.2022.3157435
Appears in Collections:Department of Applied Informatics

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