ThinkMind // CLOUD COMPUTING 2010, The First International Conference on Cloud Computing, GRIDs, and Virtualization // View article cloud_computing_2010_4_40_50059

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Semantic Resource Allocation with Historical Data Based Predictions

Authors:
Jorge Ejarque
Andras Micsik
Raül Sirvent
Peter Pallinger
Laszlo Kovacs
Rosa Badia

Keywords: multi-agent, semantics, scheduling, resource allocation, historical data, predictions, grid computing, cloud computing, distributed systems

Abstract:
One of the most important issues for Service Providers in Cloud Computing is delivering a good quality of service. This is achieved by means of the adaptation to a changing environment where different failures can occur during the execution of different services and tasks. Some of these failures can be predicted taking into account the information obtained from previous executions. The results of these predictions will help the schedulers to improve the allocation of resources to the different tasks. In this paper, we present a framework which uses semantically enhanced historical data for predicting the behavior of tasks and resources in the system, and allocating the resources according to these predictions.

Pages: 104 to 109

Copyright: Copyright (c) IARIA, 2010

Publication date: November 21, 2010

Published in: conference

ISBN: 978-1-61208-106-9

Location: Lisbon, Portugal

Dates: from November 21, 2010 to November 26, 2010