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Adapting Market-Oriented Policies for Scheduling Divisible Loads on Clouds

Adapting Market-Oriented Policies for Scheduling Divisible Loads on Clouds

Mimi Liza Abdul Majid, Suriayati Chuprat
Copyright: © 2020 |Volume: 11 |Issue: 2 |Pages: 11
ISSN: 1947-3532|EISSN: 1947-3540|EISBN13: 9781799807087|DOI: 10.4018/IJDST.2020040104
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MLA

Majid, Mimi Liza Abdul, and Suriayati Chuprat. "Adapting Market-Oriented Policies for Scheduling Divisible Loads on Clouds." IJDST vol.11, no.2 2020: pp.45-55. http://doi.org/10.4018/IJDST.2020040104

APA

Majid, M. L. & Chuprat, S. (2020). Adapting Market-Oriented Policies for Scheduling Divisible Loads on Clouds. International Journal of Distributed Systems and Technologies (IJDST), 11(2), 45-55. http://doi.org/10.4018/IJDST.2020040104

Chicago

Majid, Mimi Liza Abdul, and Suriayati Chuprat. "Adapting Market-Oriented Policies for Scheduling Divisible Loads on Clouds," International Journal of Distributed Systems and Technologies (IJDST) 11, no.2: 45-55. http://doi.org/10.4018/IJDST.2020040104

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Abstract

Cloud computing has become an important alternative for solving big data processing. Nowadays, cloud service providers usually offer users a virtual machine with various combinations of prices. As each user has different circumstances, the problem of choosing the cost-minimized combination under a deadline constraint as well as user's preference is becoming more complex. This article is concerned with the investigation of adapting a user's preference policies for scheduling real-time divisible loads in a cloud computing environment. The workload allocation approach used in this research is using Divisible Load Theory. The proposed algorithm aggregates resources into groups and optimally distributes the fractions of load to the available resources according to user's preference. The proposed algorithm was evaluated by simulation experiments and compared with the baseline approach. The result obtained from the proposed algorithm reveals that a significant reduction in computation cost can be attained when the user's preferences are low priority.

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