Institute of Visual Informatics

Enhanced Intelligent Facility Monitoring of Computer Network System via Fusion of IoT and Complex Event Detection

Headed by Assoc. Prof. Dr. Mohamad Hanif Bin Md Saad.

Dana Impak Perdana (DIP)

 

 

Computer Network System (CNS) forms a crucial infrastructure in the era of IR4.0. It enables information exchange between remote sites and facilitates communication between organizations. As such, it is very critical to ensure that CNS facilities such as server farms, server rooms, and communication gateways are in good shape. Organizations employ multiple subsystems (e.g.: SCADA systems) monitoring these facilities with real-time heterogeneous data processing, anomalous events detection (e.g.: power failure at a server farm). One method to build such systems is to develop intelligent CNS facilities monitoring via the Complex Event Processing approach whereby a central system acquires sensor data, identifies Simple Events (SE), and Complex Events (CEs) and automatically executes mitigation action to rectify anomalous events. UKM researchers have previously successfully developed a CNS system called SONAR, for Perbadanan Putrajaya (PPJ) to assist them in monitoring the CNS facilities in Putrajaya and has been used since 2013. In this project, the research team will improve SONAR’s CE detection capability via enhancing the CE detection algorithm and incorporating SONAR with a new low-cost Internet of Things (IoT) based sensor data collection system to enable more sensor data to be acquired at a fraction of the current cost. Enhancing SONAR’s CE detection engine capability will explicitly improve the CE detection process and ensures that no anomalous CE events go un-mitigated. The incorporation of a low-cost IoT based sensor system will lower the capital and operational cost of SONAR and make it sustainable. Furthermore, a lower-cost sensor data acquisition system will enable more sensors to be incorporated and ultimately improve the SONAR’s CE detection capability. The enhanced SONAR, as a case study of a CSN monitoring system in this project, is highly scalable and can be utilized by other organizations and not limited to Putrajaya only.