Research On Service-oriented Autonomic Recovery System Architecture And Technologies

As business logic becomes more and more complicated, requirement of IT supports of enterprises becomes more and more sophisticated. Most IT systems adopt distributed structure because of enterprises'cross-boundary nature and requirement of fast response. In order to separate IT and business and shield increasingly complex internal implementation of IT systems, researchers put forword the concept of service. Because of complexity and Heterogeneity of service-oriented distributed system, artificial management and maintainment become more difficult, but traditional dependability theory and techniche can't meet actual needs well. So how to avoid service failure or minimize the impact of failure becomes the key issue of improving dependability of sevice. But it's impossible to totally avoid service failure, however fast recovery from failure can deduce impact of service failure. So autonomic recovery techiche came into being with people's expect for solving the problems.Because of distributed environment and high availability demand, construction of framework, real-time monitoring of random events and fast recovery from failure are to be deep studied and discussed. So this paper takes improvement of service recovery ability as target and deep studies autonomic recovery model, monitoring model and recovery technology.First, an autonomic recovery framework model which has a hierarchy structure is constructed based on features of service and autonomic recovery technology. Central layer is responsible for monitoring and analizing and recovery layer is responsible for implementing recovery while service layer is taken as target system. Then detailed design, fuction module and workflow of each layer is determined, and some key issues like communications between components and dependability definition and quantification are researched, which provides theory support for autonomic recovery implementation. At last, the model is formally descript and analyzed with PEPA.Second, as information collection part is basis of the whole autonomic recovery system, all analysis and recovery actions are based on the information from it. So the paper puts forward a comprehensive monitor model and relative algorithms based on files'multi- attributes. In this model all events are classified as three file attributes:static attribute, dynamic inner attribute and dynamic outside attribute, and each kind of events are monitored based on relative algorithm. Experimental results show that the proposed monitor model has better monitoring performance than existing monitoring mechanisms.Third, to meet needs of autonomic recovery, we propose a recursive microreboot method which is insensitive to language and doesn't rely on specific server. Performance of existing microreboot methods is limited because of their dependence on environment and requirement of modularization. Acturally response time of each service depends on response time of each microrebootable element inner the service. So In order to improve recovery performance, recovery granularity needs to be refined to reboot more accurately. Regarding microreboot as microscopical re-execution, the paper proposes a microreboot method which can improve performance by controlling microrebootable elements. And experimental results show that the proposed microreboot method has better recovery performance and less limits than existing ones.Fourth, the paper proposes a novel software hot-swapping method and its structure and algorithm are also descript. Unlike existing ones, this method maintains an intermediate interface table which has a simple structure. Experimental results show that the method can be used to tolerate attack, unexpected modification and meet upgrade needs at the same time; it just contains one global agent so that system cost is deduced.The last, taking a web service as experimental case, the paper introduces implementation of the proposed autonomic recovery model and technology. With consideration of MVC structure of the case, recovery structure and workflow are deployed on practical application, which provides demonstration and guide for autonomic recovery system's application for other services.