Data mining: concepts and techniques
Data mining: concepts and techniques
Filtering algorithms and implementation for very fast publish/subscribe systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Design and evaluation of a wide-area event notification service
ACM Transactions on Computer Systems (TOCS)
E Role-based Decomposition of Business Processes using BPEL
ICWS '06 Proceedings of the IEEE International Conference on Web Services
Towards a framework for the agile mining of business processes
BPM'05 Proceedings of the Third international conference on Business Process Management
On web services workflow mining
BPM'05 Proceedings of the Third international conference on Business Process Management
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Service Oriented Architecture (SOA) is by far the most pervasive architecture which includes several building blocks among which orchestration engine is under special focus. Although, there are a number of centralized orchestration engines to execute business processes described by BPEL language in SOA, you may find several decentralized orchestration engines and their purpose is decomposing a BPEL process to several software agents to improve quality factors such as adaptability, performance and so forth. As these process distribution methods break a BPEL process to its building activities and encapsulate each activity in one agent, it results in producing a lot of agents whose interactions and resource usage would degrade the run-time environment. This paper proposes an intelligent process distribution (IPD) based on a process mining approach in which the selection of activities that should be encapsulated in agents, depends on the previous behavior of process instances. The recommended IPD approach will improve three aspects of system quality. First; is the amelioration of business process adaptability with run-time environment, second; choosing the best agent granularity based on detecting most relevant activities and encapsulating them in agents and third; is decreasing of resource usage due to reduced and improved number of produced agents and messages. Furthermore, we proved our method using a mathematical approach.