Dynamic Multi-objective task scheduling in Cloud Computing based on Modified particle swarm optimization
Journal: Advances in Computer Science : an International Journal(ACSIJ) (Vol.4, No. 5)Publication Date: 2015-09-30
Authors : A.I.Awad; N.A.El-Hefnawy; H.M.Abdel kader;
Page : 110-117
Keywords : Cloud computing; partial swarm; load balancing; task scheduling; Particle swarm optimization;
Abstract
Task scheduling is one of the most important research topics in Cloud Computing environment. Dynamic Multi-objective task scheduling in Cloud Computing are proposed by using modified particle swarm optimization. This paper presents efficient allocation of
Other Latest Articles
- On end-to-end safety for mobile COTS devices
- Persian Word Sense Disambiguation Corpus Extraction Based on Web Crawler Method
- MLENN-KELM: a Prototype Selection Based Kernel Extreme Learning Machine Approach for Large-Scale Automatic Image Annotation
- Linear time constant factor approximation algorithm for the Euclidean ``Freeze-Tag`` robot awakening problem
- Finding the highest performance for one-to-many content distribution in peer-to-peer networks based on the clustering and loading bandwidth of peer Nodes
Last modified: 2015-10-08 21:45:18