In communicating resource systems (CRS), a set of independent, hierarchically composed resources communicate to realize a business process. Examples of CRSs include RESTful Web services, cloud computing platforms and hierarchical distributed systems. Unfortunately, their complexity, distributed nature, and usually long lifespan can lead to problems like livelocks, deadlock occurrences and invocation loops. This makes CRSs hard to maintain and manage; it also leads to a loss of QoS or system failures. Moreover, it is important to take into account, in system management, the exact way how the system gets to some desired or undesired state. Therefore, it is crucial to analyze processes, executed in a system to find and fix the above problems. Unfortunately, CRS process models are hardly ever available. Therefore, we present a new distributed algorithm, dRMA, discovering process models from CRS event logs. In order to reduce the representational bias between the discovered process model and the real process, we have defined a Communication Net, which can express features of CRSs: directed communication channels, hierarchy, and a resource perspective. Finally, we have evaluated dRMA on a cluster, and have showed that distributing jobs can significantly reduce the time of process model discovery.

Composition of Web Services (WS) into business processes (BP) often results in occurrence of defects in a process: implicit dependencies, incorrect contexts, non-optimal or bottlenecked workflow, and deadlocks. To deal with these problems, WS Mining (process mining in SOA) research provides methods and tools to discover, evaluate and enhance real world processes basing on a process model discovered from a log. Unfortunately, current research in this field only concerns SOAP-WS which are not as well-suited as RESTful-WS in the context of current research trends like Internet of Things or Web 2.0. WS Mining methods and tools should consider RESTful-WS where functionality of the system is expressed in the form of resources and relationships among them. In this paper we show the idea of discovering process models for interacting RESTful-WS with respect to both workflow and resources perspectives. We introduce extended version of the α algorithm (AA), RESTful-WS mining algorithm (RMA), which discovers hierarchical process models and resource-oriented perspective of a process including local and global behavior. Finally, we present a brief discussion on how RMA decomposes a problem into smaller ones, significantly reducing the execution time in real time scenarios.