The Study And Implementation Of Grid System QoS Degradation Key Technologies Based On Organic Computing

With the continuous development of Grid, all grid applications are abstracted and encapsulated into "Services", and these services should provide customers with reliable and guaranteed quantity of service (QoS). In this case, a good grid resource mapping strategy is able to allocate resources effectively, endowing the grid application with a better performance. With the grid system become more and more complexing, the QoS is gradually becoming the focus. So how to guarantee the QoS requirement of customers has become a hotspot in the field of grid resource mapping research.In order to solve the problems mentioned-above,constantly to address the growing complexity of system,to further guarantee the quality of service.This paper introduces the idea of organic computing,constructing a organic computing QoS degradation model based on self-healing function.The model by giving some of the characteristics of organisms reduce system's complexity while increasing flexibility and robustness of mapping.In this paper,we study the main technology and mechanisms of guaranteeing QoS, the status of QoS monitoring is detailed analysis.The QoS degradation self-healing model added QoS monitoring,analysis,self-healing components in the Observer.By monitoring the corresponding QoS parameters, diagnosing service degradation source and replacing it, in order to guarantee the QoS requirements of users of Grid resource mapping.The model deploys the monitoring components:edgeQMon,reqsideQMon and provideQMon.The QMon\QServer architecture is explained in detail to illustrate the architecture of the system design goals,specifications,communication protocols,parameters of the formula,process and structure.Based on the QoS parameters to analyze the service degradation source, and proposed a discrimination algorithm of QoS degradation. Adopting QoS degradation propagation principle to replace the service in order to meet users'QoS requirements.Also, this paper adopts GridSim to simulate the algorithm, tests and verifies its reasonableness and feasibility.