In this paper we extend our previous work on soft probabilistic contracts for QoS management, from the particular case of "response time", to general QoS parameters. Our study covers composite QoS parameters dealing not only with time aspects but also with quality of data. We also study contract composition (how to derive QoS contracts for an orchestration from the QoS contracts with its called services), and contract monitoring. Our approach supports comprehensive and flexible QoS management within a probabilistic framework.

Web services are software applications that are published over the Web, and can be searched and invoked by other programs. New Web services can be formed by composing elementary services, such composite services are called Web service orchestrations. Quality of service (QoS) issues for Web service orchestrations deeply differ from corresponding QoS issues in network management. In an open world of Web services, service level agreements (SLAs) play an important role. They are contracts defining the obligations and rights between the provider of a Web service and a client with respect to the services' function and quality. In a previous work we have advocated using soft contracts of probabilistic nature, for the QoS part of contracts. Soft contracts have no hard bounds on QoS parameters, but rather probability distributions for them. An essential component of SLA management is the continuous monitoring of the performance of called Web services, to check for violation of the agreed SLA. In this paper we propose a statistical technique for QoS contract run time monitoring. Our technique is compatible with the use of soft probabilistic contracts.

Service level agreements (SLAs), or contracts, have an important role in web services. They define the obligations and rights between the provider of a web service and its client, about the function and the Quality of the service (QoS). For composite services like orchestrations, contracts are deduced by a process called QoS contract composition, based on contracts established between the orchestration and the called web services. Contracts are typically stated as hard guarantees (e.g., response time always less than 5 msec). Using hard bounds is not realistic, however, and more statistical approaches are needed. In this paper we propose using soft probabilistic contracts instead, which consist of a probability distribution for the considered QoS parameter—in this paper, we focus on timing. We show how to compose such contracts, to yield a global probabilistic contract for the orchestration. Our approach is implemented by the TOrQuE tool. Experiments on TOrQuE show that overly pessimistic contracts can be avoided and significant room for safe overbooking exists. An essential component of SLA management is then the continuous monitoring of the performance of called web services, to check for violations of the SLA. We propose a statistical technique for run-time monitoring of soft contracts.

Web services orchestrations and choreographies require establishing quality of service (QoS) contracts with the user. This is achieved by performing QoS composition, based on contracts established between the orchestration and the called Web services. These contracts are typically stated in the form of hard guarantees (e.g., response time always less than 5 msec). In this paper we propose using soft contracts instead. Soft contracts are characterized by means of probability distributions for QoS parameters. We show how to compose such contracts, to yield a global contract (probabilistic) for the orchestration. Our approach is implemented by the TOrQuE tool. Experiments on TOrQuE show that overly pessimistic contracts can be avoided and significant room for safe overbooking exists.

Web services orchestrations require a firm mathematical basis for their development, regarding both their functional and QoS characteristics. We provide such a basis in the form of a model based on colored Petri net systems. Our approach allows evaluating end-to-end QoS of the orchestration with the help of the QoS of the called sites.