Fuzzy Allocation of Fine-Grained Compute Resources for Grid Data Streaming Applications

Fuzzy Allocation of Fine-Grained Compute Resources for Grid Data Streaming Applications

Wen Zhang (Tsinghua University, China), Junwei Cao (Tsinghua University and Tsinghua National Laboratory for Information Science and Technology, China), Yisheng Zhong (Tsinghua University and Tsinghua National Laboratory for Information Science and Technology, China), Lianchen Liu (Tsinghua University and Tsinghua National Laboratory for Information Science and Technology, China) and Cheng Wu (Tsinghua University and Tsinghua National Laboratory for Information Science and Technology, China)
DOI: 10.4018/978-1-4666-0056-0.ch020
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Abstract

Fine-grained allocation of compute resources, in terms of configurable clock speed of virtual machines, is essential for processing efficiency and resource utilization of data streaming applications. For a data streaming application, its processing speed is expected to approach the allocated bandwidth as much as possible. Automatic control technology is a feasible solution, but the plant model is hard to be derived. In relation to the model free characteristic, a fuzzy logic controller is designed with several simple yet robust rules. Performance of this controller is verified to out-perform classic controllers in response rapidness and less oscillation. An empirical formula on tuning an essential parameter is obtained to achieve better performance.
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2. Problem Formulation

In a data streaming scenario, data in remote sources will be transferred to local storage, read by processing program one tuple by another and deleted. From a macroscopic viewpoint, data is just processed in a form of tuple streams.

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