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  1. Proceedings of the 6th international workshop on Middleware for grid computing (MGC '08)
  2. Heuristic for resources allocation on utility computing infrastructures
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Heuristic for resources allocation on utility computing infrastructures

Content Provider ACM Digital Library
Author Silva, João Nuno Veiga, Luís Ferreira, Paulo
Abstract The use of utility on-demand computing infrastructures, such as Amazon's Elastic Clouds [1], is a viable solution to speed lengthy parallel computing problems to those without access to other cluster or grid infrastructures. With a suitable middleware, bag-of-tasks problems could be easily deployed over a pool of virtual computers created on such infrastructures. In bag-of-tasks problems, as there is no communication between tasks, the number of concurrent tasks is allowed to vary over time. In a utility computing infrastructure, if too many virtual computers are created, the speedups are high but may not be cost effective; if too few computers are created, the cost is low but speedups fall below expectations. Without previous knowledge of the processing time of each task, it is difficult to determine how many machines should be created. In this paper, we present an heuristic to optimize the number of machines that should be allocated to process tasks so that for a given budget the speedups are maximal. We have simulated the proposed heuristics against real and theoretical workloads and evaluated the ratios between number of allocated hosts, charged times, speedups and processing times. With the proposed heuristics, it is possible to obtain speedups in line with the number of allocated computers, while being charged approximately the same predefined budget.
Starting Page 1
Ending Page 6
Page Count 6
File Format PDF
ISBN 9781605583655
DOI 10.1145/1462704.1462713
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2008-12-01
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Resource allocation Resource allocation on utility computing Bag-of-tasks Scheduling heuristics
Content Type Text
Resource Type Article
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