The week's pick
Reseach Article
Given a Static Workload Cloud Computing Patterns does it have an Elastic Scaling?
| Communications on Applied Electronics |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 4 - Number 2 |
| Year of Publication: 2016 |
| Authors: Ravi (Ravinder) Prakash. G, Kiran M |
10.5120/cae2016652041
|
Ravi (Ravinder) Prakash. G, Kiran M . Given a Static Workload Cloud Computing Patterns does it have an Elastic Scaling?. Communications on Applied Electronics. 4, 2 ( January 2016), 17-26. DOI=10.5120/cae2016652041
Abstract
Measurability is a concept in elastic scaling based on the following two conditions: (a) a cloud service provider should be cautious, that is, should not exclude any cloud consumer’s resource pooling pattern strategy from consideration; and (b) a cloud service provider should consider the cloud consumers’ resource pooling pattern preferences, that is, should deem a cloud consumer’s resource pooling pattern strategy ki infinitely more likely than k'i if it premises the cloud consumer to prefer ki to k'i. A resource pooling pattern strategy is measurable if it can optimally be chosen under common resource pooling pattern conjecture in the events (a) and (b). In this paper we present an algorithm that for every finite elastic scaling operation computes the set of all measurable resource pooling pattern strategies. The algorithm is based on the new idea of a Static Workload preference limitation, which is a pair (ki, Vi) consisting of a resource pooling pattern strategy ki, and a subset of resource pooling pattern strategies Vi, for cloud service provider i. The interpretation is that cloud service provider i prefers some resource pooling pattern strategy in Vi to ki. The algorithm proceeds by successively adding Static Workload preference limitations to the elastic scaling.
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- Ravi (Ravinder) Prakash G. and Kiran M. Is It True for Static Scaling Cloud Model there Exists a Centrally Asymmetric Static Workload Pattern?. Communications on Applied Electronics 3(4):39-48, November 2015.
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