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Algorithms to Improve Resource Utilization and Request Acceptance Rate in IaaS Cloud Scheduling


Affiliations
1 International Institute of Professional Studies, Devi Ahilya University, Indore-17, India
2 Computer Centre, Devi Ahilya University, Indore-17, India
 

Computing infrastructure provisioning in Infrastructure as a Service (IaaS) cloud is done in the form of virtual machines. Haizea, a resource lease manager, provides four types of leases: Immediate, Best Effort (BE), Advance Reservation (AR) and Dead Line Sensitive (DLS). AR leases are most privileged leases with “AR preempts other leases” policy, since they can preempt & suspend other BE leases when demanded by consumers. This leads to two problems: 1) a set of BEs can go suspended infinite number of time & 2) ARs, at the actual time of their resource allocation, can be rejected due to presence of other ARs in schedule. This work proposes two algorithms 1) Starvation-Removal and 2) AR-to-BE Conversion to solve these problems. Experimental results of the proposed algorithms successfully demonstrate that we can stop starvation of BE leases for resources and effectively improve request acceptance rate.

Keywords

AR-to-BE Conversion, IaaS Cloud, Haizea, Scheduling, Starvation-Removal.
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  • Algorithms to Improve Resource Utilization and Request Acceptance Rate in IaaS Cloud Scheduling

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Authors

Vivek Shrivastava
International Institute of Professional Studies, Devi Ahilya University, Indore-17, India
D. S. Bhilare
Computer Centre, Devi Ahilya University, Indore-17, India

Abstract


Computing infrastructure provisioning in Infrastructure as a Service (IaaS) cloud is done in the form of virtual machines. Haizea, a resource lease manager, provides four types of leases: Immediate, Best Effort (BE), Advance Reservation (AR) and Dead Line Sensitive (DLS). AR leases are most privileged leases with “AR preempts other leases” policy, since they can preempt & suspend other BE leases when demanded by consumers. This leads to two problems: 1) a set of BEs can go suspended infinite number of time & 2) ARs, at the actual time of their resource allocation, can be rejected due to presence of other ARs in schedule. This work proposes two algorithms 1) Starvation-Removal and 2) AR-to-BE Conversion to solve these problems. Experimental results of the proposed algorithms successfully demonstrate that we can stop starvation of BE leases for resources and effectively improve request acceptance rate.

Keywords


AR-to-BE Conversion, IaaS Cloud, Haizea, Scheduling, Starvation-Removal.