An Efficient Resource Provisioning Technique in Inter-Cloud using Peer-to-Peer Approach
Manbir Kaur1, Kiranbir Kaur1 & Lohit Kapoor2 Show affiliations
- Guru Nanak Dev University, India
- Sreenidhi Institute of Science and Technology, India
American Journal of Engineering and Applied Sciences, Volume 10, Issue 2, pp. 529–539 · doi.org/10.3844/ajeassp.2017.529.539
Abstract
Resource discovery is the process of computing systems; it supports resource management and scheduling of applications. It searches for the apposite variety of resource that satisfies the user's requirements. Resource discovery in computing system is perplexing because of conventional centralized approaches and resilient availability of resources. This scenario becomes more complex in inter-clouds owing to the dynamism and heterogeneity of clouds involved. The inspiration driving this paper is to utilize peer-to-peer approach to circumvent the problem of resource provisioning and resource discovery that are predominantly associated with centralized approach. This paper introduces a system model of Resource discovery in Inter-Cloud and mechanism to joining Remote Resource Manager using reputation based algorithm. We attempt to minimize the data traffic and balance the load partly by using the reputation based algorithm.
Licence and reuse
Open access. This article is licensed under a Creative Commons Attribution 3.0 Licence (CC BY 3.0), as printed on the article, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original authors and the source. No permission is needed.
How to reuse this articleResponses (0)
About this article
Kaur, M., Kaur, K. & Kapoor, L. (2017). An Efficient Resource Provisioning Technique in Inter-Cloud using Peer-to-Peer Approach. American Journal of Engineering and Applied Sciences, 10(2), 529–539. https://doi.org/10.3844/ajeassp.2017.529.539
- Licence
- CC BY 3.0
- Issue
- Volume 10, Issue 2
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
