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Multi-Agent with Multi Objective-Based Optimized Resource Allocation on Inter-Cloud

J. Arravinth*, D. Manjula

Department of Computer Science and Engineering, College of Engineering, Guindy, Anna University, Chennai, 600025, Tamilnadu, India

* Corresponding Author: J. Arravinth. Email: email

Intelligent Automation & Soft Computing 2022, 34(1), 133-147. https://doi.org/10.32604/iasc.2022.025292

Abstract

Cloud computing is the ability to provide new technologies and standard cloud services. One of the essential features of cloud computing is the provision of “unlimited” computer resources to users on demand. However, single cloud resources are generally limited and may not be able to cope with the sudden rise in user needs. Therefore, the inter-cloud concept is introduced to support resource sharing between clouds. In this system, each cloud can tap the resources of other clouds when there are not enough resources to meet the demands of the consumer. In cloud computing, allocating the available resources of service nodes to on-demand tasks is an important concern. To achieve this, in this paper, multi-agent with multi-objective optimized resource allocation on inter-cloud is proposed. The proposed algorithm is a combination of adaptive tree seed optimization (ATSO) and multi-agent. The proposed approach consists of four agents namely, user interface agent, monitoring agent, scheduler agent, and Executer agent. Initially, the user agent collects the task from the users, and the monitoring agent reports the resource list to the scheduler agent. Based on the resource list, the scheduler agent schedules the task with the help of ATSO. Finally, the executer agent, allocate the task to the resources. The performance of the proposed approach is evaluated using makespan, cost, and resource utilization.

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Cite This Article

J. Arravinth and D. Manjula, "Multi-agent with multi objective-based optimized resource allocation on inter-cloud," Intelligent Automation & Soft Computing, vol. 34, no.1, pp. 133–147, 2022.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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