Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing
IEEE Transactions on Parallel and Distributed Systems
Distributed and Parallel Databases
Quality driven web services composition
WWW '03 Proceedings of the 12th international conference on World Wide Web
QoS Aggregation for Web Service Composition using Workflow Patterns
EDOC '04 Proceedings of the Enterprise Distributed Object Computing Conference, Eighth IEEE International
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Efficient algorithms for Web services selection with end-to-end QoS constraints
ACM Transactions on the Web (TWEB)
Combining global optimization with local selection for efficient QoS-aware service composition
Proceedings of the 18th international conference on World wide web
Frontiers in Information and Software as Services
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Towards Scalability of Quality Driven Semantic Web Service Composition
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
SERVICES '09 Proceedings of the 2009 Congress on Services - I
A Probabilistic Approach to Service Selection with Conditional Contracts and Usage Patterns
ICSOC-ServiceWave '09 Proceedings of the 7th International Joint Conference on Service-Oriented Computing
Selecting skyline services for QoS-based web service composition
Proceedings of the 19th international conference on World wide web
On optimal service selection in Service Oriented Architectures
Performance Evaluation
Distributed QoS Evaluation for Real-World Web Services
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Metaheuristic Optimization of Large-Scale QoS-aware Service Compositions
SCC '10 Proceedings of the 2010 IEEE International Conference on Services Computing
Genetic algorithm based QoS-aware service compositions in cloud computing
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications: Part II
QoS-Aware Automatic Service Composition by Applying Functional Clustering
ICWS '11 Proceedings of the 2011 IEEE International Conference on Web Services
Efficient Heuristic Approach with Improved Time Complexity for Qos-Aware Service Composition
ICWS '11 Proceedings of the 2011 IEEE International Conference on Web Services
Algorithms for Web service selection with static and dynamic requirements
Service Oriented Computing and Applications
A flexible approach for considering interdependent security objectives in service composition
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Review: Cloud computing service composition: A systematic literature review
Expert Systems with Applications: An International Journal
QoS-aware web services composition using GRASP with Path Relinking
Expert Systems with Applications: An International Journal
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Service-Oriented Computing (SOC) enables the composition of loosely coupled services provided with varying Quality of Service (QoS) levels. Selecting a (near-)optimal set of services for a composition in terms of QoS is crucial when many functionally equivalent services are available. With the advent of Cloud Computing, both the number of such services and their distribution across the network are rising rapidly, increasing the impact of the network on the QoS of such compositions. Despite this, current approaches do not differentiate between the QoS of services themselves and the QoS of the network. Therefore, the computed latency differs substantially from the actual latency, resulting in suboptimal QoS for service compositions in the cloud. Thus, we propose a network-aware approach that handles the QoS of services and the QoS of the network independently. First, we build a network model in order to estimate the network latency between arbitrary services and potential users. Our selection algorithm then leverages this model to find compositions that will result in a low latency given an employed execution policy. In our evaluation, we show that our approach efficiently computes compositions with much lower latency than current approaches.