A Novel Multi-Objective Cat Swarm Technique for an Efficient Cloud Manager for Data Handling in Cloud Environment.

Autor: Gupta, Megha, Ahuja, Laxmi, Seth, Ashish
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Zdroj: International Journal of Performability Engineering; Mar2023, Vol. 19 Issue 3, p216-222, 7p
Abstrakt: The three key advantages of cloud computing are adaptability, scale, and availability. These features were produced by combining virtualization techniques with internet services. The conventional management techniques and tools, unfortunately, appear inadequate in comparison to the scalability and flexibility of cloud services since they often require local software installation with ongoing upgrades and modifications. System administrators still do a major portion of the manual work involved in deploying and managing cloud configurations. Working with cloud services from multiple providers is also challenging since the solutions are sometimes private and only adhere to the cloud service capabilities of certain service providers. Incorporating autonomy into cloud management would mean giving the cloud manager the capacity to autonomously upgrade or decrease the variety of deployed images and virtual machines to fulfill Customer service contracts for efficiency, etc. In this paper, we introduce Multi-objective Cat Swarm - Aurora (MCS-Aurora), a highly scalable infrastructure as a service (IaaS) cloud manager that enables access to cloud services even in the scenario that the manager itself fails. By providing network automation, MCS-Aurora and the role-based access control mechanism provide flexible and effective resource management. Enhancing user authentication, data access mechanisms, and data security are the main goals of the suggested manager. The manager is in charge of achieving the cloud's service level agreement for handling and storing data. To demonstrate the effectiveness of the system, the suggested technique is contrasted with current methods. [ABSTRACT FROM AUTHOR]
Databáze: Supplemental Index