Section: New Results

Priority based events management in IoT-BPM architecture

Participants : Khalid Benali, Abir Ismaili-Alaoui.

BPM allows organizations to evolve their performance and achieve their goals, as it helps them to have a clear vision of their business. Several research works have been done in this area and aimed at improving business processes, by focusing on the optimization of business processes issues at build-time and at run-time, from different perspectives: control-flow perspective, data and event data perspective, and scheduling and event management perspective. Business process instances scheduling and event management are considered as a crucial step in the journey of business process improvement. However, this step becomes more challenging especially when the events are triggered by IoT devices. The main objective of our research consists on scheduling business process instances based on the priority of events that trigger these instances, taking into consideration historical data gathered from previous business process instances. We proposed a clustering approach based on the K-Means algorithm that we apply on a set of event sources, as to classify these sources on different clusters using a score calculated for each event source. This score is based on the frequency and the critically of previous events. The main objective of this approach was to create clusters of priorities. These clusters are used to estimate the criticality level of incoming events, and then the priority level of incoming process instances. However, there is always a degree of uncertainty regarding the criticality/priority level of events generated from sources that belong to the same cluster. This issue can be addressed by using fuzzy logic. In fact, the integration of a Fuzzy Inference System (FIS) in our IoT-BPM architecture, helps us to handle uncertainties regarding the criticality level of events, especially when these events are generated by sources that may have the same characteristics [8].