pCloud: an adaptive i/o resource allocation algorithm with revenue consideration over public clouds

Authors:
Jianzong Wang;Yanjun Chen;Daniel Gmach;Changsheng Xie;Jiguang Wan;Rui Hua
Affiliations:
School of Computer Science, Huazhong University of Science and Technology, Wuhan, China,Wuhan National Laboratory for Optoelectronics, Wuhan, China;School of Computer Science, Huazhong University of Science and Technology, Wuhan, China;HP Labs, Palo Alto, CA;School of Computer Science, Huazhong University of Science and Technology, Wuhan, China,Wuhan National Laboratory for Optoelectronics, Wuhan, China;School of Computer Science, Huazhong University of Science and Technology, Wuhan, China,Wuhan National Laboratory for Optoelectronics, Wuhan, China;School of Computer Science, Huazhong University of Science and Technology, Wuhan, China
Venue:
GPC'12 Proceedings of the 7th international conference on Advances in Grid and Pervasive Computing
Year:
2012

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Abstract

Cloud-based services are emerging as an economical and convenient alternative for clients who don't want to acquire, maintain and operate their own IT equipment. Instead, customers purchase virtual machines (VMs) with certain Service Level Objectives (SLOs) to obtain computational resources. Existing algorithms for memory and CPU allocation are inadequate for I/O allocation, especially in clustered storage infrastructures where storage is distributed across multiple storage nodes. This paper focuses on: (1) dynamic SLO decomposition so VMs receive proper I/O service in each distributed storage node, and (2) efficient and robust local I/O scheduling strategy. To address these issues, we present pCloud, an adaptive I/O resource allocation algorithm that at runtime adjusts local SLOs. The local SLOs are generated for each VM at each storage node based on access patterns. We also adopt dual clocks in pCloud to allow automatic switching between two scheduling strategies. When system capacity is sufficient, pCloud interweaves requests in an earliest deadline first (EDF) manner. Otherwise resources are allocated proportionate to their normalized revenues. The results of our experiments suggest that pCloud is adaptive to various access patterns without significant manual pre-settings while maximizing profits.