The Experts below are selected from a list of 4341 Experts worldwide ranked by ideXlab platform
Xing Jian - One of the best experts on this subject based on the ideXlab platform.
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qos aware multi Granularity Service composition based on generalized component Services
International Conference on Service Oriented Computing, 2013Co-Authors: Qingsheng Zhu, Xing JianAbstract:QoS-aware Service composition aims to maximize overall QoS values of the resulting composite Service. Traditional methods only consider Service instances that implement one abstract Service in the composite Service as candidates, and neglect those that fulfill multiple abstract Services. To overcome this shortcoming, we present the concept of generalized component Services to expand the selection scope to achieve a better solution. The problem of QoS-aware multi-Granularity Service composition is then formulated and how to discover candidates for each generalized component Service is elaborated. A genetic algorithm based approach is proposed to optimize the resulting composite Service instance. Empirical studies are performed at last.
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ICSOC - QoS-Aware Multi-Granularity Service Composition Based on Generalized Component Services
Service-Oriented Computing, 2013Co-Authors: Qingsheng Zhu, Xing JianAbstract:QoS-aware Service composition aims to maximize overall QoS values of the resulting composite Service. Traditional methods only consider Service instances that implement one abstract Service in the composite Service as candidates, and neglect those that fulfill multiple abstract Services. To overcome this shortcoming, we present the concept of generalized component Services to expand the selection scope to achieve a better solution. The problem of QoS-aware multi-Granularity Service composition is then formulated and how to discover candidates for each generalized component Service is elaborated. A genetic algorithm based approach is proposed to optimize the resulting composite Service instance. Empirical studies are performed at last.
Michael Luck - One of the best experts on this subject based on the ideXlab platform.
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Efficient multi-Granularity Service composition
Proceedings - 2011 IEEE 9th International Conference on Web Services ICWS 2011, 2011Co-Authors: Lina Barakat, Iman Poernomo, Simon Miles, Michael LuckAbstract:Dynamic composition of Services provides the ability to build complex distributed applications at run time by combining existing Services, thus coping with a large variety of complex requirements that cannot be met by individual Services alone. However, with the increasing amount of available Services that differ in Granularity (amount of functionality provided) and qualities, selecting the best combination of Services becomes very complex. In response, this paper addresses the challenges of Service selection, and makes a twofold contribution. First, a rich representation of compositional planning knowledge is provided, allowing the expression of multiple decompositions of tasks at arbitrary levels of Granularity. Second, two distinct search space reduction techniques are introduced, the application of which, prior to performing Service selection, results in significant improvement in selection performance in terms of execution time, which is demonstrated via experimental results.
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ICWS - Efficient Multi-Granularity Service Composition
2011 IEEE International Conference on Web Services, 2011Co-Authors: Lina Barakat, Iman Poernomo, Simon Miles, Michael LuckAbstract:Dynamic composition of Services provides the ability to build complex distributed applications at run time by combining existing Services, thus coping with a large variety of complex requirements that cannot be met by individual Services alone. However, with the increasing amount of available Services that differ in Granularity (amount of functionality provided) and qualities, selecting the best combination of Services becomes very complex. In response, this paper addresses the challenges of Service selection, and makes a twofold contribution. First, a rich representation of compositional planning knowledge is provided, allowing the expression of multiple decompositions of tasks at arbitrary levels of Granularity. Second, two distinct search space reduction techniques are introduced, the application of which, prior to performing Service selection, results in significant improvement in selection performance in terms of execution time, which is demonstrated via experimental results.
Qingsheng Zhu - One of the best experts on this subject based on the ideXlab platform.
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qos aware multi Granularity Service composition based on generalized component Services
International Conference on Service Oriented Computing, 2013Co-Authors: Qingsheng Zhu, Xing JianAbstract:QoS-aware Service composition aims to maximize overall QoS values of the resulting composite Service. Traditional methods only consider Service instances that implement one abstract Service in the composite Service as candidates, and neglect those that fulfill multiple abstract Services. To overcome this shortcoming, we present the concept of generalized component Services to expand the selection scope to achieve a better solution. The problem of QoS-aware multi-Granularity Service composition is then formulated and how to discover candidates for each generalized component Service is elaborated. A genetic algorithm based approach is proposed to optimize the resulting composite Service instance. Empirical studies are performed at last.
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ICSOC - QoS-Aware Multi-Granularity Service Composition Based on Generalized Component Services
Service-Oriented Computing, 2013Co-Authors: Qingsheng Zhu, Xing JianAbstract:QoS-aware Service composition aims to maximize overall QoS values of the resulting composite Service. Traditional methods only consider Service instances that implement one abstract Service in the composite Service as candidates, and neglect those that fulfill multiple abstract Services. To overcome this shortcoming, we present the concept of generalized component Services to expand the selection scope to achieve a better solution. The problem of QoS-aware multi-Granularity Service composition is then formulated and how to discover candidates for each generalized component Service is elaborated. A genetic algorithm based approach is proposed to optimize the resulting composite Service instance. Empirical studies are performed at last.
Xiao Geng - One of the best experts on this subject based on the ideXlab platform.
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a novel multi Granularity Service composition model
Asia-Pacific Services Computing Conference, 2016Co-Authors: Yanmei Zhang, Yu Qiao, Xiao Geng, Zhao Liu, Hengyue JiaAbstract:The number of Services is proliferating dramatically and the rate of Services’ evolution has also been increasingly fluctuating in recent years. The demands of Service composition also show the characteristics of individuation and diversification at the same time. The traditional methods of Service composition are difficult to meet the multiple Granularity demands of users. This paper proposes a novel multiple granular Service composition model based on Services granular space. The model firstly constructs Service Granularity by Service clustering. And then constructs the Service Granularity space according to the relationships between Service granularities. So the process of getting appropriate Service compositions can be transformed into getting Service compositions from different Granularity layers. Through experimental analysis, we can demonstrate that this model can provide users with different Granularity Service compositions which meet the multiple Granularity demands of users. And can also decrease the response time of Service composition at the same time.
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APSCC - A Novel Multi-Granularity Service Composition Model
Lecture Notes in Computer Science, 2016Co-Authors: Yanmei Zhang, Yu Qiao, Xiao GengAbstract:The number of Services is proliferating dramatically and the rate of Services’ evolution has also been increasingly fluctuating in recent years. The demands of Service composition also show the characteristics of individuation and diversification at the same time. The traditional methods of Service composition are difficult to meet the multiple Granularity demands of users. This paper proposes a novel multiple granular Service composition model based on Services granular space. The model firstly constructs Service Granularity by Service clustering. And then constructs the Service Granularity space according to the relationships between Service granularities. So the process of getting appropriate Service compositions can be transformed into getting Service compositions from different Granularity layers. Through experimental analysis, we can demonstrate that this model can provide users with different Granularity Service compositions which meet the multiple Granularity demands of users. And can also decrease the response time of Service composition at the same time.
Lina Barakat - One of the best experts on this subject based on the ideXlab platform.
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Efficient multi-Granularity Service composition
Proceedings - 2011 IEEE 9th International Conference on Web Services ICWS 2011, 2011Co-Authors: Lina Barakat, Iman Poernomo, Simon Miles, Michael LuckAbstract:Dynamic composition of Services provides the ability to build complex distributed applications at run time by combining existing Services, thus coping with a large variety of complex requirements that cannot be met by individual Services alone. However, with the increasing amount of available Services that differ in Granularity (amount of functionality provided) and qualities, selecting the best combination of Services becomes very complex. In response, this paper addresses the challenges of Service selection, and makes a twofold contribution. First, a rich representation of compositional planning knowledge is provided, allowing the expression of multiple decompositions of tasks at arbitrary levels of Granularity. Second, two distinct search space reduction techniques are introduced, the application of which, prior to performing Service selection, results in significant improvement in selection performance in terms of execution time, which is demonstrated via experimental results.
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ICWS - Efficient Multi-Granularity Service Composition
2011 IEEE International Conference on Web Services, 2011Co-Authors: Lina Barakat, Iman Poernomo, Simon Miles, Michael LuckAbstract:Dynamic composition of Services provides the ability to build complex distributed applications at run time by combining existing Services, thus coping with a large variety of complex requirements that cannot be met by individual Services alone. However, with the increasing amount of available Services that differ in Granularity (amount of functionality provided) and qualities, selecting the best combination of Services becomes very complex. In response, this paper addresses the challenges of Service selection, and makes a twofold contribution. First, a rich representation of compositional planning knowledge is provided, allowing the expression of multiple decompositions of tasks at arbitrary levels of Granularity. Second, two distinct search space reduction techniques are introduced, the application of which, prior to performing Service selection, results in significant improvement in selection performance in terms of execution time, which is demonstrated via experimental results.
