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On Characterized Once-in-a-Lifetime Workload patterns for Periodic Static Scaling
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 10 - Number 6 |
| Year of Publication: 2016 |
| Authors: Ravi (Ravinder) Prakash G., Kiran M. |
10.5120/ijais2016451521
|
Ravi (Ravinder) Prakash G., Kiran M. . On Characterized Once-in-a-Lifetime Workload patterns for Periodic Static Scaling. International Journal of Applied Information Systems. 10, 6 ( March 2016), 33-43. DOI=10.5120/ijais2016451521
Abstract
Measurability is a concept in periodic static 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 periodic static scaling operation computes the set of all measurable resource pooling pattern strategies. The algorithm is based on the new idea of an Once-in-a-Lifetime 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 Once-in-a-Lifetime Workload preference limitations to the periodic static scaling.
References
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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.
- Ravi (Ravinder) Prakash. G and Kiran M., Given a Static Workload Cloud Computing Patterns does it have an Elastic Scaling? Communications on Applied Electronics 4(2): 17-26, January 2016.
- Ravi (Ravinder) Prakash G. and Kiran M., How can Periodic Workload Cloud Pattern benefit from Periodically Peaking Utilization?. International Journal of Applied Information Systems 10(5):27-36, February 2016.
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