Interoperable Resource Management for Establishing Federated Clouds

Author:

Kecskemeti Gabor1,Kertesz Attila1,Marosi Attila1,Kacsuk Peter1

Affiliation:

1. Laboratory of Parallel and Distributed Systems of the MTA-SZTAKI, Hungary

Abstract

Cloud Computing builds on the latest achievements of diverse research areas, such as Grid Computing, Service-oriented computing, business process modeling and virtualization. As this new computing paradigm was mostly lead by companies, several proprietary systems arose. Recently, alongside these commercial systems, several smaller-scale privately owned systems are maintained and developed. This chapter focuses on issues faced by users with interests in Multi-Cloud use and by Cloud providers with highly dynamic workloads. The authors propose a Federated Cloud Management architecture that provides unified access to a federated Cloud that aggregates multiple heterogeneous IaaS Cloud providers in a transparent manner. The architecture incorporates the concepts of meta-brokering, Cloud brokering, and on-demand service deployment. The meta-brokering component provides transparent service execution for the users by allowing the interconnection of various Cloud brokering solutions. Cloud-Brokers manage the number and the location of the Virtual Machines performing the user requests. In order to decrease Virtual Machine instantiation time and increase dynamism in the system, the service deployment component optimizes service delivery by encapsulating services as virtual appliances allowing their decomposition and replication among IaaS Cloud infrastructures. The architecture achieves service provider level transparency through automatic virtual appliance replication and Virtual Machine management of Cloud-Brokers.

Publisher

IGI Global

Reference26 articles.

1. Amazon CloudWatch. (2011). Website, retrieved July 20, 2011 from http://aws.amazon.com/cloudwatch/

2. Amazon Web Services LLC. (2011). Amazon elastic compute cloud. Website, retrieved July 20, 2011 from http://aws.amazon.com/ec2/

3. Bellur, U., Rao C. S. & S.D, M. K. (2010). Optimal Placement Algorithms for Virtual Machines. Arxiv preprint arXiv10115064, (Vm), pp 1-16. Retrieved from http://arxiv.org/abs/1011.5064

4. Bernstein, D., Ludvigson, E., Sankar, K., Diamond, S., & Morrow, M. (2009). Blueprint for the Intercloud – Protocols and Formats for Cloud Computing Interoperability. In Proceedings of The Fourth International Conference on Internet and Web Applications and Services. 328-336.

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Network federation: Challenges and opportunities;Internet Technology Letters;2023-10-03

2. CloudFinder: A System for Processing Big Data Workloads on Volunteered Federated Clouds;IEEE Transactions on Big Data;2020-06-01

3. Enhancing the Cloud Inter-operation Toolkit (CIT) to Support Multiple Cloud Service Models;Journal of Grid Computing;2020-04-18

4. Multiple-Clouds Computing Security Approaches;Proceedings of the International Conference on Internet of things and Cloud Computing;2016-03-22

5. Cloud Federations;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2016

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3