Introduction: Service-oriented computing
Communications of the ACM - Service-oriented computing
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Web services on demand: WSLA-driven automated management
IBM Systems Journal
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
QoS-aware Composite Service Selection in Grids
GCC '06 Proceedings of the Fifth International Conference on Grid and Cooperative Computing
Heuristics for QoS-aware Web Service Composition
ICWS '06 Proceedings of the IEEE International Conference on Web Services
Efficient algorithms for Web services selection with end-to-end QoS constraints
ACM Transactions on the Web (TWEB)
Global and local qos guarantee in web service selection
BPM'05 Proceedings of the Third international conference on Business Process Management
QoS-aware web services composition using GRASP with Path Relinking
Expert Systems with Applications: An International Journal
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In this paper, we consider a provider that offers an application implemented as a composite service to several users with (possibly) different Quality of Service (QoS) requirements. To this end, the provider negotiates with both the clients and the service providers Service Level Agreements (SLAs), which define the respective QoS-related obligations along with the interval of time over which such obligations are to be met. We present an efficient SLA provisioning scheme which allows to determine for each client the constituent services that best meet its QoS goal as well as the services effective usage. Differently from most of the current approaches, which consider independently each single request and often require the solution of an NP-hard problem, we take into account the simultaneous and concurrent client accesses to the application and optimize the aggregated QoS of all incoming client requests by means of a simple linear programming problem. As a result, the proposed approach is scalable and lends itself to an efficient implementation.