Scheduling in compute cloud with multiple data banks using divisible load paradigm

S. Suresh, Hao Huang, Hyong Joong Kim

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

The main challenge in a compute cloud system is to design a scheduling strategy for heterogeneous computing resources with shared data banks. The cloud user's job arrives at the Web role, which distributes the load to the worker rules for concurrent processing. The worker role retrieves the respective data from the shared data banks. According to divisible load theory, the scheduling problem is formulated as relevant recursive equations and constraints that are derived from the continuity of processing time due to retrieval from multiple data banks. The scheduling problem in a compute cloud is formulated as a linear programming problem. Finally, we present a satellite image classification problem in a compute cloud as an example to show the adequacy of the proposed solution.

Original languageEnglish
Article number7126183
Pages (from-to)1288-1297
Number of pages10
JournalIEEE Transactions on Aerospace and Electronic Systems
Volume51
Issue number2
DOIs
Publication statusPublished - 2015 Apr 1

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Scheduling
Image classification
Processing
Linear programming
Satellites

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Aerospace Engineering

Cite this

Scheduling in compute cloud with multiple data banks using divisible load paradigm. / Suresh, S.; Huang, Hao; Kim, Hyong Joong.

In: IEEE Transactions on Aerospace and Electronic Systems, Vol. 51, No. 2, 7126183, 01.04.2015, p. 1288-1297.

Research output: Contribution to journalArticle

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