SLA - driven dynamic resource allocation on clouds

Authors:
G. M. Siddesh;K. G. Srinivasa
Affiliations:
Dept. of Information Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India and JNTU, Hyderabad, India;Dept. of Computer Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India
Venue:
ADCONS'11 Proceedings of the 2011 international conference on Advanced Computing, Networking and Security
Year:
2011

Citing 5
Cited 0

Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility

Future Generation Computer Systems
Exploiting semantics and virtualization for SLA-driven resource allocation in service providers

Concurrency and Computation: Practice & Experience
Profit-Driven Service Request Scheduling in Clouds

CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Resource-level QoS metric for CPU-based guarantees in cloud providers

GECON'10 Proceedings of the 7th international conference on Economics of grids, clouds, systems, and services
InterCloud: utility-oriented federation of cloud computing environments for scaling of application services

ICA3PP'10 Proceedings of the 10th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

With advent of gaining popularity in cloud computing, there is an increase in demand of resources among the heterogeneous workload types on cloud. Resource management is a key challenging problem that is faced by the cloud service providers, by achieving business goals and agreed level of service with the subscribers. This paper focuses on dynamic resource allocation with risk analysis by meeting Service Level Agreements. Further, proposed framework handles heterogeneous workload types by dynamic capacity planning with risk assessment to maximize the profit and resource utilization on clouds. In addition advanced resource reservation, SLA based scheduling/rescheduling with risks involved in resource allocation is considered in the proposed model. The experimental results demonstrates that proposed framework maximizes the resource utilization and profit gain of the cloud service provider when evaluated against widely used static configuration strategy.