The Experts below are selected from a list of 17661 Experts worldwide ranked by ideXlab platform
Yun Yang - One of the best experts on this subject based on the ideXlab platform.
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A probabilistic strategy for temporal constraint management in scientific Workflow systems
Concurrency and Computation: Practice and Experience, 2011Co-Authors: Jinjun Chen, Yun YangAbstract:In scientific Workflow systems, it is critical to ensure the timely completion of scientific Workflows. Therefore, temporal constraints as a type of QoS (Quality of Service) specification are usually required to be managed in scientific Workflow systems. Specifically, temporal constraint management includes two basic tasks: setting temporal constraints at Workflow build-time and updating temporal constraints at Workflow run-time. For constraint setting, the current work mainly adopts user-specified temporal constraints without considering the system performance. Hence, it may result in frequent temporal violations which deteriorate the overall Workflow Execution effectiveness. As regards constraint updating, although not well investigated, so far is in fact of great importance to Workflow management tasks such as Workflow scheduling and exception handling. In this paper, with a systematic analysis of the above issues, we propose a probabilistic strategy for temporal constraint management which utilizes a novel probability-based temporal consistency model. Specifically for constraint setting, a negotiation process between the client and the service provider is designed to support the setting of coarse-grained temporal constraints and then automatically derive the fine-grained temporal constraints; for constraint updating, the probability time deficit/redundancy propagation process is proposed to update run-time fine-grained temporal constraints when Workflow Execution is either ahead of or behind the schedule. The effectiveness of our strategy is demonstrated through a case study on an example scientific Workflow process in our scientific Workflow system. Copyright © 2011 John Wiley & Sons, Ltd. (The initial work was published in the Proceedings of 6th International Conference on Business Process Management (BPM2008), Lecture Notes in Computer Science, vol. 5240, pp. 180–195, September 2008 Milan, Italy.)
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a compromised time cost scheduling algorithm in swindew c for instance intensive cost constrained Workflows on a cloud computing platform
IEEE International Conference on High Performance Computing Data and Analytics, 2010Co-Authors: Ke Liu, Dong Yuan, Jinjun Chen, Xiao Liu, Hai Jin, Yun YangAbstract:The concept of cloud computing continues to spread widely, as it has been accepted recently. Cloud computing has many unique advantages which can be utilized to facilitate Workflow Execution. Instance-intensive cost-constrained cloud Workflows are Workflows with a large number of Workflow instances (i.e. instance intensive) bounded by a certain budget for Execution (i.e. cost constrained) on a cloud computing platform (i.e. cloud Workflows). However, there are, so far, no dedicated scheduling algorithms for instance-intensive cost-constrained cloud Workflows. This paper presents a novel compromised-time-cost scheduling algorithm which considers the characteristics of cloud computing to accommodate instance-intensive cost-constrained Workflows by compromising Execution time and cost with user input enabled on the fly. The simulation performed demonstrates that the algorithm can cut down the mean Execution cost by over 15% whilst meeting the user-designated deadline or shorten the mean Execution time by over 20% within the user-designated Execution cost.
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an algorithm in swindew c for scheduling transaction intensive cost constrained cloud Workflows
IEEE International Conference on eScience, 2008Co-Authors: Yun Yang, Dong Yuan, Jinjun Chen, Ke Liu, Xiao Liu, Hai JinAbstract:The concept of cloud computing has been wide spreading very recently. Cloud computing has many unique advantages which can be utilised to facilitate (cloud) Workflow Execution. Transaction-intensive cost-constrained cloud Workflows are Workflows with a large number of Workflow instances (i.e. transaction intensive) bounded by a certain budget for Execution (i.e. cost constrained) in a cloud computing environment (i.e. cloud Workflows). However, there are not any specific scheduling algorithms so far for transaction-intensive cost-constrained cloud Workflows. This paper presents a novel scheduling algorithm which considers the characteristics of cloud computing to accommodate transaction-intensive cost-constrained Workflows by compromising Execution time and cost with user input enabled on the fly. The simulation performed demonstrates that the algorithm can reduce the mean Execution cost while meeting the user-requested deadline.
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temporal dependency based checkpoint selection for dynamic verification of fixed time constraints in grid Workflow systems
International Conference on Software Engineering, 2008Co-Authors: Jinjun Chen, Yun YangAbstract:In grid Workflow systems, temporal correctness is critical to assure the timely completion of grid Workflow Execution. To monitor and control the temporal correctness, fixed-time constraints are often assigned to a grid Workflow and then verified. A checkpoint selection strategy is used to select checkpoints along grid Workflow Execution for verifying fixed-time constraints. The problem of existing representative strategies is that they do not differentiate fixed-time constraints as once a checkpoint is selected, they verify all fixed-time constraints. However, these checkpoints do not need to be taken for those constraints whose consistency can be deduced from others. The corresponding verification of such constraints is consequently unnecessary and can severely impact the efficiency of overall temporal verification. To address the problem, in this paper, we develop a new temporal dependency based checkpoint selection strategy which can select checkpoints according to different fixed-time constraints. With our strategy, the corresponding unnecessary verification can be avoided. The comparison and experimental simulation further demonstrate that our new strategy can improve the efficiency of overall temporal verification significantly over the existing representative strategies.
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selecting necessary and sufficient checkpoints for dynamic verification of fixed time constraints in grid Workflow systems
Business Process Management, 2006Co-Authors: Jinjun Chen, Yun YangAbstract:In grid Workflow systems, existing representative checkpoint selection strategies, which are used to select checkpoints for verifying fixed-time constraints at run-time Execution stage, often select some unnecessary checkpoints and ignore some necessary ones. Consequently, overall temporal verification efficiency and effectiveness can be severely impacted. In this paper, we propose a new strategy that selects only necessary and sufficient checkpoints dynamically along grid Workflow Execution. Specifically, we introduce a new concept of minimum time redundancy as a key reference value for checkpoint selection. We also investigate its relationships with fixed-time constraint consistency. Based on these relationships, we present our strategy which can improve overall temporal verification efficiency and effectiveness significantly.
Jinjun Chen - One of the best experts on this subject based on the ideXlab platform.
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a clustering based coscheduling strategy for efficient scientific Workflow Execution in cloud computing
Concurrency and Computation: Practice and Experience, 2013Co-Authors: Kefeng Deng, Kaijun Ren, Junqiang Song, Dong Yuan, Yang Xiang, Jinjun ChenAbstract:SUMMARY Due to its advantages of cost-effectiveness, on-demand provisioning and easy for sharing, cloud computing has grown in popularity with the research community for deploying scientific applications such as Workflows. Although such interests continue growing and scientific Workflows are widely deployed in collaborative cloud environments that consist of a number of data centers, there is an urgent need for exploiting strategies which can place application datasets across globally distributed data centers and schedule tasks according to the data layout to reduce both latency and makespan for Workflow Execution. In this paper, by utilizing dependencies among datasets and tasks, we propose an efficient data and task coscheduling strategy that can place input datasets in a load balance way and meanwhile, group the mostly related datasets and tasks together. Moreover, data staging is used to overlap task Execution with data transmission in order to shorten the start time of tasks. We build a simulation environment on Tianhe supercomputer for evaluating the proposed strategy and run simulations by random and realistic Workflows. The results demonstrate that the proposed strategy can effectively improve scheduling performance while reducing the total volume of data transfer across data centers. Concurrency and Computation: Practice and Experience, 2013.© 2013 Wiley Periodicals, Inc.
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A probabilistic strategy for temporal constraint management in scientific Workflow systems
Concurrency and Computation: Practice and Experience, 2011Co-Authors: Jinjun Chen, Yun YangAbstract:In scientific Workflow systems, it is critical to ensure the timely completion of scientific Workflows. Therefore, temporal constraints as a type of QoS (Quality of Service) specification are usually required to be managed in scientific Workflow systems. Specifically, temporal constraint management includes two basic tasks: setting temporal constraints at Workflow build-time and updating temporal constraints at Workflow run-time. For constraint setting, the current work mainly adopts user-specified temporal constraints without considering the system performance. Hence, it may result in frequent temporal violations which deteriorate the overall Workflow Execution effectiveness. As regards constraint updating, although not well investigated, so far is in fact of great importance to Workflow management tasks such as Workflow scheduling and exception handling. In this paper, with a systematic analysis of the above issues, we propose a probabilistic strategy for temporal constraint management which utilizes a novel probability-based temporal consistency model. Specifically for constraint setting, a negotiation process between the client and the service provider is designed to support the setting of coarse-grained temporal constraints and then automatically derive the fine-grained temporal constraints; for constraint updating, the probability time deficit/redundancy propagation process is proposed to update run-time fine-grained temporal constraints when Workflow Execution is either ahead of or behind the schedule. The effectiveness of our strategy is demonstrated through a case study on an example scientific Workflow process in our scientific Workflow system. Copyright © 2011 John Wiley & Sons, Ltd. (The initial work was published in the Proceedings of 6th International Conference on Business Process Management (BPM2008), Lecture Notes in Computer Science, vol. 5240, pp. 180–195, September 2008 Milan, Italy.)
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a compromised time cost scheduling algorithm in swindew c for instance intensive cost constrained Workflows on a cloud computing platform
IEEE International Conference on High Performance Computing Data and Analytics, 2010Co-Authors: Ke Liu, Dong Yuan, Jinjun Chen, Xiao Liu, Hai Jin, Yun YangAbstract:The concept of cloud computing continues to spread widely, as it has been accepted recently. Cloud computing has many unique advantages which can be utilized to facilitate Workflow Execution. Instance-intensive cost-constrained cloud Workflows are Workflows with a large number of Workflow instances (i.e. instance intensive) bounded by a certain budget for Execution (i.e. cost constrained) on a cloud computing platform (i.e. cloud Workflows). However, there are, so far, no dedicated scheduling algorithms for instance-intensive cost-constrained cloud Workflows. This paper presents a novel compromised-time-cost scheduling algorithm which considers the characteristics of cloud computing to accommodate instance-intensive cost-constrained Workflows by compromising Execution time and cost with user input enabled on the fly. The simulation performed demonstrates that the algorithm can cut down the mean Execution cost by over 15% whilst meeting the user-designated deadline or shorten the mean Execution time by over 20% within the user-designated Execution cost.
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an algorithm in swindew c for scheduling transaction intensive cost constrained cloud Workflows
IEEE International Conference on eScience, 2008Co-Authors: Yun Yang, Dong Yuan, Jinjun Chen, Ke Liu, Xiao Liu, Hai JinAbstract:The concept of cloud computing has been wide spreading very recently. Cloud computing has many unique advantages which can be utilised to facilitate (cloud) Workflow Execution. Transaction-intensive cost-constrained cloud Workflows are Workflows with a large number of Workflow instances (i.e. transaction intensive) bounded by a certain budget for Execution (i.e. cost constrained) in a cloud computing environment (i.e. cloud Workflows). However, there are not any specific scheduling algorithms so far for transaction-intensive cost-constrained cloud Workflows. This paper presents a novel scheduling algorithm which considers the characteristics of cloud computing to accommodate transaction-intensive cost-constrained Workflows by compromising Execution time and cost with user input enabled on the fly. The simulation performed demonstrates that the algorithm can reduce the mean Execution cost while meeting the user-requested deadline.
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temporal dependency based checkpoint selection for dynamic verification of fixed time constraints in grid Workflow systems
International Conference on Software Engineering, 2008Co-Authors: Jinjun Chen, Yun YangAbstract:In grid Workflow systems, temporal correctness is critical to assure the timely completion of grid Workflow Execution. To monitor and control the temporal correctness, fixed-time constraints are often assigned to a grid Workflow and then verified. A checkpoint selection strategy is used to select checkpoints along grid Workflow Execution for verifying fixed-time constraints. The problem of existing representative strategies is that they do not differentiate fixed-time constraints as once a checkpoint is selected, they verify all fixed-time constraints. However, these checkpoints do not need to be taken for those constraints whose consistency can be deduced from others. The corresponding verification of such constraints is consequently unnecessary and can severely impact the efficiency of overall temporal verification. To address the problem, in this paper, we develop a new temporal dependency based checkpoint selection strategy which can select checkpoints according to different fixed-time constraints. With our strategy, the corresponding unnecessary verification can be avoided. The comparison and experimental simulation further demonstrate that our new strategy can improve the efficiency of overall temporal verification significantly over the existing representative strategies.
Kamalakar Karlapalem - One of the best experts on this subject based on the ideXlab platform.
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context aware Workflow Execution engine for e contract enactment
International Conference on Conceptual Modeling, 2016Co-Authors: Himanshu Jain, Radha P Krishna, Kamalakar KarlapalemAbstract:An e-contract is a contract that is specified, modeled and executed by a software system. E-contract business processes are modeled using Workflows and their enactment is mostly dependent on the Execution context. Existing e-contract systems lack context-awareness, and thus often face difficulties in enacting when context and requirements of e-contracts change at run-time. In this paper, we (a) present an approach for context pattern discovery and build a context-aware Workflow Execution engine, (b) develop an approach for context-aware Execution-Workflow to instantiate and execute context-based Workflow instances and (c) provide a framework for context-aware e-contract enactment system. We also demonstrate the viability of our approach using a government contract.
Dick Epema - One of the best experts on this subject based on the ideXlab platform.
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deadline constrained Workflow scheduling algorithms for infrastructure as a service clouds
Future Generation Computer Systems, 2013Co-Authors: Saeid Abrishami, Mahmoud Naghibzadeh, Dick EpemaAbstract:The advent of Cloud computing as a new model of service provisioning in distributed systems encourages researchers to investigate its benefits and drawbacks on executing scientific applications such as Workflows. One of the most challenging problems in Clouds is Workflow scheduling, i.e., the problem of satisfying the QoS requirements of the user as well as minimizing the cost of Workflow Execution. We have previously designed and analyzed a two-phase scheduling algorithm for utility Grids, called Partial Critical Paths (PCP), which aims to minimize the cost of Workflow Execution while meeting a user-defined deadline. However, we believe Clouds are different from utility Grids in three ways: on-demand resource provisioning, homogeneous networks, and the pay-as-you-go pricing model. In this paper, we adapt the PCP algorithm for the Cloud environment and propose two Workflow scheduling algorithms: a one-phase algorithm which is called IaaS Cloud Partial Critical Paths (IC-PCP), and a two-phase algorithm which is called IaaS Cloud Partial Critical Paths with Deadline Distribution (IC-PCPD2). Both algorithms have a polynomial time complexity which make them suitable options for scheduling large Workflows. The simulation results show that both algorithms have a promising performance, with IC-PCP performing better than IC-PCPD2 in most cases. Highlights? We propose two Workflow scheduling algorithms for IaaS Clouds. ? The algorithms aim to minimize the Workflow Execution cost while meeting a deadline. ? The pricing model of the Clouds is considered which is based on a time interval. ? The algorithms are compared with a list heuristic through simulation. ? The experiments show the promising performance of both algorithms.
Thierry Priol - One of the best experts on this subject based on the ideXlab platform.
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A Chemistry-Inspired Workflow Management System for Decentralizing Workflow Execution
IEEE Transactions on Services Computing, 2016Co-Authors: Héctor Fernandez, Cédric Tedeschi, Thierry PriolAbstract:With the recent widespread adoption of service-oriented architecture, the dynamic composition of services is now a crucial issue in the area of distributed computing. The coordination and Execution of composite Web services are today typically conducted by heavyweight centralized Workflow engines, leading to an increasing probability of processing and communication bottlenecks and failures. In addition, centralization induces higher deployment costs, such as the computing infrastructure to support the Workflow engine, which is not affordable for a large number of small businesses and end-users. In a world where platforms are more and more dynamic and elastic as promised by cloud computing, decentralized and dynamic interaction schemes are required. Addressing the characteristics of such platforms, nature-inspired analogies recently regained attention to provide autonomous service coordination on top of dynamic large scale platforms. In this paper, we propose an approach for the decentralized Execution of composite Web services based on an unconventional programming paradigm that relies on the chemical metaphor. It provides a high-level Execution model that allows executing composite services in a decentralized manner. Composed of services communicating through a persistent shared space containing control and data flows between services, our architecture allows to distribute the composition coordination among nodes. A proof of concept is given, through the deployment of a software prototype implementing these concepts, showing the viability of an autonomic vision of service composition.
