SRS: A Decentralized and Rule-Based Approach to Data Dependency Analysis and Failure Recovery in Service-Oriented Environments

NSF Proposal 0820152A面向服务环境中数据依赖分析和故障恢复的分散式和基于规则的方法[id: Susan D. Urban]本研究的目的是在一个松散耦合的面向服务环境中，开发一种分散的方法来进行数据依赖分析和并发执行进程的故障恢复。该方法包括监视单个服务执行的外部化数据更改。然后使用流程执行代理之间的点对点、分散通信来发现并发执行流程之间的数据依赖关系，这些依赖关系可能在恢复失败流程期间导致数据不一致。依赖进程的进程干扰规则用于测试用户定义的语义条件，以确定1)关键数据条件是否受到失败进程恢复的影响，以及2)依赖进程是否应该调用恢复过程。该研究包括开发一种使用过程干扰规则的方法。在支持补偿、偶然性、回滚和重试技术的服务组合模型的上下文中，还演示了分散数据依赖分析和基于规则的恢复过程的正确性和效率。这项研究提供了一种思考传统事务可恢复性概念的新方法，提供了一种动态方法来发现数据依赖关系，并以一种保证用户定义的正确性条件的方式响应故障，以保证在没有隔离保证的情况下执行并发进程。

NSF Proposal 0820152A Decentralized and Rule-Based Approach to Data Dependency Analysis and Failure Recovery in a Service-Oriented EnvironmentPI: Susan D. Urban The objective of this research is to develop a decentralized approach to data dependency analysis and failure recovery among concurrently executing processes in a loosely-coupled service-oriented environment. The approach involves monitoring externalized data changes of individual service executions. Peer-to-peer, decentralized communication among process execution agents is then used to discover data dependencies among concurrently executing processes that may lead to data inconsistencies during the recovery of a failed process. Process interference rules of dependent processes are used to test user-defined semantic conditions to determine if 1) critical data conditions have been affected by the recovery of a failed process and 2) recovery procedures should be invoked for dependent processes. The research includes the development of a methodology for using process interference rules. The correctness and efficiency of decentralized data dependency analysis and rule-based recovery procedures are also demonstrated for concurrent processes in the context of a service composition model that supports compensation, contingency, rollback, and retry techniques. This research provides a new way of thinking about traditional transaction recoverability concepts, providing a dynamic approach to discovering data dependencies and responding to failures in a manner that guarantees user-defined correctness conditions for concurrent processes that execute without isolation guarantees.