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Dynamic Load Balancing in Cloud Computing using Swarm Intelligence Algorithms
Author(s) -
Abhijit Patil,
Harshal Gala,
Jai Kapoor
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2015907172
Subject(s) - computer science , cloud computing , swarm intelligence , swarm behaviour , load balancing (electrical power) , distributed computing , algorithm , artificial intelligence , particle swarm optimization , operating system , geometry , mathematics , grid
In today’s world, smart-phones and tablets have allowed cloud computing to realize it’s true potential. It allows the users to use software, services and data on the go. This has resulted in increased study on cloud computing. With increased research in cloud computing, emphasis has been made in load balancing that allocates resources to multiple devices. Load balancing has played an important role in cloud computing by ensuring optimal use of resources with highest efficiency. The use of load balancing in the form of software and hardware has led many to discover new algorithms to achieve the same with better efficiency and minimum response time. This article discusses about the load balancing algorithms especially, swarm intelligence algorithms that can be used to balance load across devices. The algorithms taken into account are-PSO, Ant Colony Optimization, GSO and IWD.A study on advantages and limitations of the algorithm is made in order to realize the advantages of use of each algorithm in load balancing in it’s own way. General Terms Dynamic Load Balancing, Virtual Machines. Optimization.

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