Pack Up Cloud: Recursive Datacenter Resource Management and Experimental Studies
Ye Xia, Shigang Chen, Maurício Tsugawa, J.A.B. Fortes
Abstract
Ye Xia, Shigang Chen, Maurício Tsugawa, J.A.B. Fortes
Abstract
Today's virtualized resource management in datacenters is typically VM-centric, which has serious problems in scalability. We propose a shift from the traditional flat, fine-grained model towards a hierarchical, abstract model that facilitates decomposition of the complex resource allocation problem in a divide-and-conquer approach. In particular, this paper elaborates a pack-centric framework in datacenter resource management, provides a case study with a recursive algorithm, and presents detailed results from experimental studies on VM-PM mapping through recursive resource allocation, which demonstrates the performance and scalability of the pack-centric framework.
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Today's virtualized resource management in datacenters is typically VM-centric, which has serious problems in scalability. We propose a shift from the traditional flat, fine-grained model towards a hierarchical, abstract model that facilitates decomposition of the complex resource allocation problem in a divide-and-conquer approach. In particular, this paper elaborates a pack-centric framework in datacenter resource management, provides a case study with a recursive algorithm, and presents detailed results from experimental studies on VM-PM mapping through recursive resource allocation, which demonstrates the performance and scalability of the pack-centric framework.
Key concepts: Scalability, Computer science, Cloud computing, Distributed computing, Resource management (computing), Resource allocation, Resource (disambiguation), Decomposition