Failure aware resource provisioning for hybrid cloud infrastructure
- 1. Failure-aware resource provisioning for hybrid Cloud infrastructure NISL 张雪军&July
- 2. contributions This Paper main contributions in this paper are threefold: • We provide a flexible and scalable hybrid Cloud architecture to solve the problem of resource provisioning for users’ requests. • In the hybrid Cloud architecture, we propose various provisioning policies based on the workload model and failure correlations to fulfill a common QoS requirement of users, request deadline. • We evaluate the proposed policies under realistic workload and failure traces and consider different performance metrics such as deadline violation rate, job slowdown, and performance–cost efficiency
- 3. Cloud computing Hybrid Cloud provide local users with a flexible and agile private infrastructure to run workloads within their own administrative domain security privacy Failure-aware resource provisioning approach sell IT capacity based on open market offerings Private Cloud Public Cloud Cloud computing
- 4. Background System model IaaS Homogeneous System workload Computational Fluid Dynamic(CFD) applications -- a broad range of high-performance applications tightly-coupled jobs, be allocated resources from a single provider. Gateway(broker) control the user requests
- 5. Background Failure model concentrate on resource failures in the private Cloud.
- 6. Problem Statement The resource provisioning problem can be formulated as follows: Given a set of requests (e.g., parallel jobs) and a hybrid Cloud system with a failure-prone private Cloud, the problem is how to decide if a request should be executed in a public Cloud or in a private Cloud such that the end-user QoS requirements are satisfied
- 7. Problem Statement Public Cloud Private Cloud User Request Redirection QoS
- 8. Related work The related work can be classified in two groups: load sharing in the distributed systems solutions utilizing Cloud computing resources to extend the capacity of existing infrastructure.
- 9. Related work Iosup et al. proposed a matchmaking mechanism for enabling resource sharing across computational Grids. In contrast, we utilize the workload model in provisioning policies to borrow resources from a public Cloud provider to improve the users’ QoS of an organization in the presence of resource failures.
- 10. Related work Moschakis and Karatza have evaluated the performance of applying Gang scheduling algorithms on Cloud. Their study is restricted to a single public Cloud which consists of a cluster of VMs on which parallel jobs are dispatched. In contrast, we develop our scheduling strategies on a hybrid Cloud computing environment.
- 11. The hybrid Cloud system architecture 1.Request for VMs 2.Enactment of leases 3.Application deployment
- 13. to be continued……. Thank you!