Uncertain QoS Research Articles

Efficient web service selection with uncertain QoS

The QoS-based service selection in a highly dynamical environment is becoming a challenging issue. In practice, the QoS fluctuations of a service composition entail major difficulties in measuring the degree to which the user requirements are satisfied. In addition, the search space of feasible compositions (i.e., the solutions that preserve the requirements) is generally large and cannot be explored in a limited time; therefore, we need an approach that not only copes with the presence of uncertainty but also ensures a pertinent search with a reduced computational cost. To tackle this problem, we propose a constraint programming framework and a set of ranking heuristics that both reduce the search space and ensure a set of reliable compositions. The conducted experiments show that the ranking heuristics, termed 'fuzzy dominance' and 'probabilistic skyline', outperform almost all existing state-of-the-art methods.

Efficient web service selection with uncertain QoS

Efficient web service selection with uncertain QoS

Research on Robust Model for Web Service Selection

Abstract Most existing service quality models use defined Quality of Service parameters for service selection.Since a large number of uncertainties exist, the QoS performance indicators in the runtime of the composite services obtained through the model and method based on the determined QoS will be worse even beyond the range acceptable to the users. Web services can solve this problem and become the most reasonable solution in the current application environment. Web services can solve this problem and become the most reasonable solution in the current application environment. In the process of actual service delivery, the key to the failure of the service composition to meet the requirements is caused by uncertain factors. In order to solve the above problems, this paper first proposes a local optimal selection model based on uncertain QoS. The Web service selection method based on uncertain QoS has been progressing in recent years. Second, in order to reduce the time spent on selection, a redundant service selection result is given. The experimental results on the data set show that the proposed model and method can effectively select more robust services for users.

Clustering-based uncertain QoS prediction of web services via collaborative filtering

Although collaborative filtering (CF) has been widely applied for QoS-aware web service recommendation, most of these approaches mainly focus on certain QoS prediction. However, they failed to take the natural characteristic of web services with QoS uncertainty into account in service-oriented web applications. To solve the problem, this paper proposes a novel approach for uncertain QoS prediction via collaborative filtering and service clustering. We first establish uncertain QoS model for a service user, where each service is formalised as a QoS matrix. To mine the similar neighbourhood users for an active user, we then extend the Euclidean distance to calculate the similarity between two uncertain QoS models. Finally, we present two kinds of QoS prediction strategies based on collaborative filtering and clustering, called U-Rec and UC-Rec. Extensive experiments have been carried on 1.5 million real-world uncertain QoS transaction logs of web services. The experimental results validate the effectiveness of our proposed approach.

Clustering-based uncertain QoS prediction of web services via collaborative filtering

Clustering-based uncertain QoS prediction of web services via collaborative filtering

Policy control framework-based algorithm for uncertain QoS harmonization in IP-based live video surveillance communications

There are around 15 million surveillance camera installed in US and about 10 % of it is IP based. This number of IP-based surveillance is constantly growing as it gives an opportunity for smart real time surveillance. When the number of camera increases, it create a challenge to smart surveillance both in terms of cost and efficiency. Cost—as to monitor so many views, there is a need to have enough people. Efficiency—due to overload of monitoring, there are chances that important tracking is missed. Intelligent surveillance helps in avoiding many such issues, however, there is a constant threat that due to lack of appropriate policy control framework, tracking may be affected due to inherent network issues or human glitches. The paper presents a novel way, where a policy control framework is deployed for IP-based surveillance which will help in efficient monitoring. The paper studies the QoS pattern where such a system is deployed and shows that the utility function used for such tracking follows a linear uncertainty distribution pattern. The paper also concentrates on illustrating the algorithm for finding the cameras where the QoS needs to be harmonized. It shows how to make the algorithm opportunistic, so that the number of messages in the network can be reduced while tweaking the QoS.

Transaction history-based web service composition for uncertain QoS

The QoS-aware web service composition WSC problem constructs a composite web service with the optimal accumulated QoS value. In the real world, this problem encounters some challenges. First, while most QoS-aware WSC techniques make their decisions based on the QoS information published by each service provider, the actual QoS performance at run-time may be inconsistent with the QoS specification due to the dynamic execution environment and intentional/unintentional error in the QoS declaration. Another obstacle is that the QoS-aware WSC problem for large scale instances is intractable to solve since the problem corresponds to a global optimisation problem. Toward these challenges, we propose a novel QoS-aware WSC method based on the real service transaction history of web services, which employs the anytime algorithm technique. In the experiment, our proposal can deal with the uncertain QoS efficiently and identify composite web services with high quality much earlier than the optimal algorithm.

ABC supporting QoS unicast routing scheme with particle swarm optimization

A QoS unicast routing scheme with ABC supported was proposed.The interval was used to describe the uncertain users' QoS requirement and inaccurate edge(link) parameter.With the user satisfaction degree,edge evaluation and elitist solution set introduced,a QoS unicast path was searched by particle swarm optimization algorithm and gaming analysis,achieving or approaching Pareto optimal solution under Nash equilibrium on both the network provider utility and the user utility along the found path.Simulation results show that the proposed scheme is both feasible and effective.