Web Information Systems and Mining
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About: This article is published in Lecture Notes in Computer Science. The article was published on 01 Jan 2011. The article focuses on the topics: Web mining & Web intelligence.
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Citations
The analytic hierarchy process: task scheduling and resource allocation in cloud computing environment
TL;DR: A model for task-oriented resource allocation in a cloud computing environment where an induced bias matrix is used to identify the inconsistent elements and improve the consistency ratio when conflicting weights in various tasks are assigned is proposed.
282
Load balancing mechanisms and techniques in the cloud environments
TL;DR: A systematic literature review of the existing load balancing techniques proposed so far and the advantages and disadvantages associated with several load balancing algorithms have been discussed and the important challenges of these algorithms are addressed so that more efficientload balancing techniques can be developed in future.
245
A PSO-Based algorithm for load balancing in virtual machines of cloud computing environment
Zhanghui Liu,Xiaoli Wang +1 more
- 17 Jun 2012
TL;DR: A new task scheduling model is proposed, and a Particle Swarm Optimization (PSO) based algorithm is proposed that improves the standard PSO, and introduces a simple mutation mechanism and a self-adapting inertia weight method by classifying the fitness values.
107
An Overview of E-Learning in Cloud Computing
Alberto Fernández,Daniel Peralta,Francisco Herrera,José Manuel Benítez +3 more
- 01 Jan 2012
TL;DR: The Cloud Computing environment rises as a natural platform to provide support to e-Learning systems and also for the implementation of data mining techniques that allow to explore the enormous data bases generated from the former process to extract the inherent knowledge.
Scheduling in distributed systems: A cloud computing perspective
Luiz F. Bittencourt,Alfredo Goldman,Edmundo R. M. Madeira,Nelson L. S. da Fonseca,Rizos Sakellariou +4 more
TL;DR: This paper introduces a classification of the scheduling problem in distributed systems by presenting a taxonomy that incorporates recent developments, especially those in cloud computing, and identifies relevant future directions in scheduling for distributed systems.
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