Workflow scheduling in cloud computing environment using Cat Swarm Optimization

Bilgaiyan, Saurabh; Sagnika, Santwana; Das, Madhabananda

doi:10.1109/iadcc.2014.6779406

Cited by 64 publications

(42 citation statements)

References 12 publications

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“…This indirectly ensures that the tasks are not mapped to a single resource and there will be a distribution of cost among the resources. In Bilgaiyan et al [22] solved the same problem as [121]. Instead of PSO-based optimization, they used cat swarm optimization (CSO) method to obtain schedule in less number of iterations [41].…”

Section: Best-effort Schedulingmentioning

confidence: 99%

Workflow scheduling in cloud: a survey

2015

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To program in distributed computing environments such as grids and clouds, workflow is adopted as an attractive paradigm for its powerful ability in expressing a wide range of applications, including scientific computing, multi-tier Web, and big data processing applications. With the development of cloud technology and extensive deployment of cloud platform, the problem of workflow scheduling in cloud becomes an important research topic. The challenges of the problem lie in: NP-hard nature of task-resource mapping; diverse QoS requirements; on-demand resource provisioning; performance fluctuation and failure handling; hybrid resource scheduling; data storage and transmission optimization. Consequently, a number of studies, focusing on different aspects, emerged in the literature. In this paper, we firstly conduct taxonomy and comparative review on workflow scheduling algorithms. Then, we make a comprehensive survey of workflow scheduling in cloud environment in a problem-solution manner. Based on the analysis, we also highlight some research directions for future investigation.

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Section: Best-effort Schedulingmentioning

confidence: 99%

Workflow scheduling in cloud: a survey

2015

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“…These steps are repeated until all the tasks in the workflow are scheduled. Several improvements of this algorithm are proposed like CSO [5], RDPSO [24] and PSO HOM [21].…”

Section: Percentage Of Deleting Tasksmentioning

confidence: 99%

A Provisioning Approach of Cloud Resources for Dynamic Workflows

Fakhfakh

Kacem

2015

2015 IEEE 8th International Conference on Cloud Computing

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Workflow technologies have become an efficient mean for the development of different applications. One wellknown challenge for executing workflows on cloud computing is the resources provisioning. The latter consists in making an appropriate decision when mapping tasks to resources considering multiple objectives that are often contradictory. The problem of resources provisioning for workflow applications in the cloud has been widely studied in the literature. However, the existing works didn't consider the change in workflow instances at runtime. This functionality has become a major requirement to deal with unusual situations and evolutions. In this paper, we present a first step towards the resources provisioning for a dynamic workflow in the cloud. In fact, we propose a provisioning algorithm which takes into account some constraints. After that, we extend it in order to support the dynamic changes of workflow. Our algorithm is evaluated using CloudSim simulator. The different experiments that we present show the efficiency of our approach in terms of financial execution cost and overhead.

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“…Several improvements of this algorithm are proposed. For example, Bilgaiyan et al [6] propose a newly optimization heuristic algorithm CSO (Cat swarm optimization) based on social behaviour of cats. Each cat represents a task-resource mapping.…”

Section: ) Scheduling a Single Workflowmentioning

confidence: 99%

Workflow Scheduling in Cloud Computing: A Survey

Fakhfakh

Kacem

2014

2014 IEEE 18th International Enterprise Distributed Object Computing Conference Workshops and Demonstrations

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Workflow systems have become a major vehicle for easy and efficient development of scientific applications. This type of systems can benefit from the resource provisioning technology offered by the cloud computing. In fact, the latter offers on-demand virtualized resources to its users. These virtual resources can be added and released dynamically. Also, users are charged on a pay-per-use basis. How to make appropriate decisions when allocating resources to the tasks and dispatching the computing tasks to resource pool has become the main issue in cloud computing. The amount of allocated resources affects the execution time of the applications and the cost incurred by the user. In fact, resource under-provisioning will necessarily affect the performance. In contrast, over-provisioning can result in idle instances and cause additional costs. Then, efficient scheduling algorithms are required for selection of best suitable resources for task execution. This paper focuses on some of the important workflow scheduling strategies. It brings out an exhaustive survey of such strategies in cloud computing and includes a detailed classification of them. Then, it presents a comparative analysis of the studied approaches. Finally, it stands out a critical challenge for further research.

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Workflow scheduling in cloud computing environment using Cat Swarm Optimization

Cited by 64 publications

References 12 publications

Workflow scheduling in cloud: a survey

Workflow scheduling in cloud: a survey

A Provisioning Approach of Cloud Resources for Dynamic Workflows

Workflow Scheduling in Cloud Computing: A Survey

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