• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3096-3117
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• 2013

To execute the performance driven Grid applications, an effective and scalable workflow scheduling is seen as an essential. To optimize cost & makespan, in this paper, we propose a Scalable Cost-Time Trade-off (SCTT) model for scheduling workflow tasks. We have developed a heuristic algorithm known as Scalable Cost-Time Trade-off Scheduling (SCTTS) with a lower runtime complexity based on the proposed SCTT model. We have compared the performance of our proposed approach with other heuristic and meta-heuristic based scheduling strategies using simulations. The results show that the proposed approach improves performance and scalability with different workflow sizes, task parallelism and heterogeneous resources. This method, therefore, outperforms other methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4311-4330
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• 2015

Cloud computing has become a new paradigm by enabling on-demand provisioning of applications, platforms or computing resources for clients. Workflow scheduling has always been treated as one of the most challenging problems in clouds. Commercial clouds have been widely used in scientific research, such as biology, astronomy and weather forecasting. Certainly, it is very important for a cloud service provider to pursue the profits for the commercial essence of clouds. This is also significantly important for the case of providing services to workflow tasks. In this paper, we address the issues of workflow scheduling in commercial clouds. This work takes the communication into account, which has always been ignored. And then, a topology-based workflow-scheduling algorithm named Resource Auction Algorithm (REAL) is proposed in the objective of getting more profits. The algorithm gives a good performance on searching for the optimum schedule for a sample workflow. Also, we find that there exists a certain resource amount, which gets the most profits to help us get more enthusiasm for further developing the research. Experimental results demonstrate that the analysis of the strategies for most profits is reasonable, and REAL gives a good performance on efficiently getting an optimized scheme with low computing complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.976-995
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• 2016

Workflow scheduling is one of the challenging problems in cloud computing, especially when service reliability is considered. To improve cloud service reliability, fault tolerance techniques such as fault recovery can be employed. Practically, fault recovery has impact on the performance of workflow scheduling. Such impact deserves detailed research. Only few research works on workflow scheduling consider fault recovery and its impact. In this paper, we investigate the problem of workflow scheduling in clouds, considering the probability that cloud resources may fail during execution. We formulate this problem as a multi-objective optimization model. The first optimization objective is to minimize the overall completion time and the second one is to minimize the overall execution cost. Based on the proposed optimization model, we develop a heuristic-based algorithm called Min-min based time and cost tradeoff (MTCT). We perform extensive simulations with four different real world scientific workflows to verify the validity of the proposed model and evaluate the performance of our algorithm. The results show that, as expected, fault recovery has significant impact on the two performance criteria, and the proposed MTCT algorithm is useful for real life workflow scheduling when both of the two optimization objectives are considered.

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.191-198
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• 2006

Many enterprises have introduced workflow to enhance work efficiency and support effective work processes in their various work environments. Recently, Business Process Management(BPM), an extension of workflow, is spotlighted in enterprise software markets Although woklflow plays an important role in Business Process Managements, researches in workflow are mostly concentrated on temporal constraints which finds exact execution sequences for complicated jobs. On that reason, majority of workflow scheduling has concentrated on modeling of various resources which should be handled and the interest for workflow scheduling under constraints related to resources is rather unsatisfactory In this paper we presents the Transformation Template based on Concurrent Transaction Logic(CTR) which is suitable for scheduling workflows with resource allocation constraints, and the logical framework. The Transformation Template consists of a Workflow Transformation Template and a Constraint Transaction Template. Especially the Transformation Template can be conveniently used to logically represent new workflows under the existing resource allocation constraints.

• The KIPS Transactions:PartA
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• v.18A no.1
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• pp.11-18
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• 2011

Cloud computing is a new computing paradigm for sharing resources. Various applications used for cloud services are represented as workflows. These workflow applications must be appropriately allocated to resources or services in cloud. In this paper, a new scheduling algorithm is proposed for multiple workflow applications considering cloud computing environment. The cost-based rank scheduling algorithm considers not only multiple workflow applications, but various QoS metrics for evaluating services. Simulation results show that the proposed algorithm can improve the mean makespan and the availability significantly over two well-known algorithms.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.29-36
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• 2012

Cloud computing has gained great popularity because users don't need to install any softwares as well as maintain hardwares and service providers also can utilize its resources through virtualization of servers. As workflows feature variableness and servers are heterogenous, efficient scheduling of workflows in cloud computing is important factor in view of responsibility and resource utilization. In this paper, we propose a new workflow scheduling named 2-step scheduling which prioritizes each workflow through its significance degree and allocates resources to workflows through decision table. The goal of this 2-step scheduling is to improve responsibility as well as availability versus cost. Simulation results show that the proposed scheme in contrast of counterparts can improve the responsibility as well as availability of resource.

• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.264-270
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• 2018

In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.5
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• pp.375-384
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• 2004

The Grid is new infrastructure to provide computing environment for grand challenge research by sharing large-scale resources. Currently the Globus becomes a de facto standard middleware to construct Grid and supports core services such as resource management, security, data transfer, information services, and so on. However, it still needs more works and researches to satisfy requirements from various grid applications. A workflow management is becoming a main service as one of the important grid services for complex grid applications. We propose a Meta Scheduling Framework (MSF) in this paper. The MSF provides a XML-based Job Control Markup Language (JCML) for describing information and procedures of grid applications, and a workflow management service for scheduling the job using the JCML and for processing the job effectively.

• The Journal of Korean Association of Computer Education
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• v.9 no.6
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• pp.89-98
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• 2006

Recently, grid computing environment has being changed to the service-oriented grid integrated with Web Services. In this architecture, there is the service-oriented grid application in which Grid Services are executed according to the workflow of the grid application. This implies that the grid scheduling method needs to consider grid service characteristics. Therefore, we propose the grid service performance model based on factors such as service availability, accessibility, reliability, throughput, and slowdown, and develop service scheduling method to increase performance of the service-oriented grid application.

• Journal of the Korea Society of Computer and Information
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• v.17 no.9
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• pp.1-8
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• 2012

Cloud computing has got great popularity in recent times because users can easily access its resources as well as service providers can use efficiently use its resources. By the way, cloud computing are composed of heterogeneous resources and workflows of user application have various characteristics. So, the main goal of this paper is to design new efficient workflow scheduling algorithm, which classifies workflows through their importance degree and allocates resources to each workflow based on QoS metrics such as responsibility, cost and load balancing. Simulation results show that the proposed scheme can improve the responsibility as well as availability of resource.