2015 · 19 citations · 14 references
Service ClusteringEngineeringScheduling ProblemEdge ComputingCloud SchedulingCloud ComputingQuality-of-serviceSystems EngineeringService Oriented ComputingComputer ScienceInternet Of ThingsService DiscoveryCombinatorial OptimizationIntelligent Service SystemQos-based Service SelectionService OrchestrationService-oriented ComputingOperations Research
QoS-based service selection is one of the important requirements in Service Oriented Computing (SOC). A challenging task towards this purpose is the selection of the best combination of services that fulfils user's requirements while meeting quality of service (QoS) constraints. This challenge becomes more complex when dealing with time-dependent QoS values and temporal properties. Indeed, during the selection, mutual dependencies between the different temporal constraints may arise so that the selection of each service may influence or be influenced by the selection of other services. On other side, to find the best solution, all potential combinations must be compared. However, the number of these combinations may be very high, which can present a barrier for enabling effective service selection. In this paper, we present a heuristic based time-aware service selection approach to efficiently select a close-to-optimal combination of services. First, pruning techniques are adopted to reduce the search space. Second, a novel heuristic approach is proposed based on service clustering, constraints decomposition and local selection while considering both QoS and temporal constraints. Finally, experiments which confirm the feasibility and effectiveness of the proposed approach in terms of its timeliness and optimality, are conducted.
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Least squares quantization in PCM
Sheelagh Lloyd · IEEE Transactions on Information Theory · 1982 · 15.1K citations · Full text
An approach for QoS-aware service composition based on genetic algorithms
Gerardo Canfora, Massimiliano Di Penta, Raffaele Esposito et al. · 2005 · 905 citations