Proceedings ArticleDOI
Bat algorithm for scheduling workflow applications in cloud
S Raghavan,P. Sarwesh,C. Marimuthu,K. Chandrasekaran +3 more
- pp 139-144
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TLDR
Bat algorithm with the help of binary bat algorithm is used for scheduling workflow in a cloud using a metaheuristic approach called bat algorithm for optimizing hard problems.Abstract:
Workflow is one of the important aspects of cloud computing today. Cloud computing is one of the fastest growing technologies in the world. Workflows can be used in cloud as we use them in grid. Many operations in the cloud are based on workflow execution. Workflow systems are now becoming more complex and for such kind of systems efficient workflow management is important. Workflow scheduling is an important part of workflow management. Scheduling in general is NP-hard problem. To solve such kind of problems exhaustive methods cannot be used. Only non-exhaustive techniques can be used. In this paper we have used a metaheuristic approach called bat algorithm. Bat algorithm is specifically designed for optimizing hard problems. Here, bat algorithm with the help of binary bat algorithm is used for scheduling workflow in a cloud. Specifically the mapping of tasks and resources is done using this method. The optimal resources are selected such that the overall cost of the workflow is minimal.read more
Citations
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Journal ArticleDOI
A review of metaheuristic scheduling techniques in cloud computing
Mala Kalra,Sarbjeet Singh +1 more
TL;DR: An extensive survey and comparative analysis of various scheduling algorithms for cloud and grid environments based on three popular metaheuristic techniques: Ant Colony Optimization, Genetic Algorithm and Particle Swarm Optimization and two novel techniques: League Championship Algorithm (LCA) and BAT algorithm.
Journal ArticleDOI
Multiobjective Cloud Workflow Scheduling: A Multiple Populations Ant Colony System Approach
Zong-Gan Chen,Zhi-Hui Zhan,Ying Lin,Yue-Jiao Gong,Tianlong Gu,Feng Zhao,Huaqiang Yuan,Xiaofeng Chen,Qing Li,Jun Zhang +9 more
TL;DR: A novel multiobjective ant colony system based on a co-evolutionary multiple populations for multiple objectives framework is proposed, which adopts two colonies to deal with these two objectives, respectively.
Journal ArticleDOI
Nature Inspired Methods and Their Industry Applications—Swarm Intelligence Algorithms
Adam Slowik,Halina Kwasnicka +1 more
TL;DR: This paper presents the particle swarm optimization (PSO) algorithm and the ant colony optimization (ACO) method as the representatives of the SI approach and mentions some metaheuristics belonging to the SI.
Journal ArticleDOI
Improved bat algorithm with optimal forage strategy and random disturbance strategy
Xingjuan Cai,Xiao-Zhi Gao,Yu Xue +2 more
TL;DR: In this paper, optimal forage strategy is designed to guide the search direction for each bat and a random disturbance strategy is also employed to extend the global search pattern.
Journal ArticleDOI
Resource scheduling for infrastructure as a service (IaaS) in cloud computing
Syed Hamid Hussain Madni,Muhammad Shafie Abd Latiff,Yahaya Coulibaly,Shafi’i Muhammad Abdulhamid +3 more
TL;DR: It is perceived that different schemes and algorithms did not consider some essential parameters and enhancement is requisite to improve the performance of the existing schemes to trigger new and innovative methods of handling the problems of resource scheduling in the cloud.
References
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