Document Type

Dissertation

Degree

Doctor of Philosophy (PhD)

Department

Computer Science

First Advisor's Name

Seyed Masoud Sadjadi

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Ming Zhao

Third Advisor's Name

Jason Liu

Fourth Advisor's Name

Jorge Rodríguez

Keywords

meta-scheduling, cloud computing, brokering, provisioning, allocation, policies

Date of Defense

10-17-2012

Abstract

The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers.

However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.

Identifier

FI12120515

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