A Combination Of Research And Consultation Services Based On SLA

The service Level Agreement (SLA) is a contractual obligation between the service provider and the service consumer by specifying mutually-agreed understandings and expectations of the provision of a service. The core of a SLA is specification of the service guarantees, which define both functional and non-functional guarantees of a service provision. A SLA often contains general information such as the parties involved in service provision and their respective roles, and the validity period of the SLA. Business rules in terms of the service provision restrictions, payment, and penalties can also be specified in a SLA. With the large numbers of service composition, the SLA agreement reached by the service requester with the composite services is a formal agreement through negotiation between the service requester and the atomic services of composite services. The SLA contains a series of composite service quality objectives. Because the most of method to achieve the optimal QoS performance of service composition is multi-objective optimal method and services to the dynamic nature of support is not enough, the resulting service composition may not meet the SLA agreement. Therefore, how to do combination which meet the QoS requirements and based on SLA is a problem currently. Service level agreement has a very important role in the quality of service composition, and the negotiation of the service level agreement is becoming hot spot in recent years, as well as the dynamic changes of the outside surroundings, which make the support of service level agreement automatic establishment and maintenance very important. Around these problems, this article has carried on the following work mainly:1. For the instability of the network environment and the dynamic nature of the web service itself, and in order to set up automatically and maintain the service level agreement, this paper proposes a service composition and negotiation framework based on SLA. The negotiation is conducted through negotiation agent between service requester and service providers automatically in the framework. The service providers are all candidate services in the dependency graph of the combination. In this paper, the SLA is to describe with WSLA (Web service Level Agreement) language. The service composition which meets SLA agreement may also be obtained in the support of the framework and service level objectives in the SLA can also be converted to the factors which influence the performance of service composition. Then the service selection and combination can be carried out and SLA monitoring is doing at the same time. Once the service has a violation of the SLA, the service requester and the service providers will negotiate.2. In order to get the optimal combination of services meets the SLA agreement, this paper presents a heuristic dynamic service composition based on SLA. Heuristic method we choose the ant colony algorithm here. The method converts the QoS requirements in the service level objectives to the factors affecting the pheromone of ant colony algorithm, and then ant colony algorithm to improve to reach the optimal composite service QoS. Experiments prove that this method is effective to solve the service composition to meet the SLA agreement.3. In order to adapt to the dynamic changes of the environment, this paper presents automatic negotiation of the service composition based on SLA. The composite service QoS requirements need to be converted to the QoS requirement of each service provider formed the composite service firstly, and then we define the negotiation model and parameter mapping model. The parameter mapping model will map the high level of QoS requirements described by negotiation partners to the low level parameters of decision function based on time, which reduces the complexity of the system. We also propose a strategy selection algorithm according to the other proposal in the negotiation process in order to determine their own adaptive decision-making function. According to the comparison of the two negotiating sides total utility value, simulation results show the effectiveness of our proposed method.