• A load balance multi-scheduling model for OpenCL kernel tasks in an integrated cluster 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam; Aleem, Muhammad (Peer reviewed; Journal article, 2020)
      Nowadays, embedded systems are comprised of heterogeneous multi-core architectures, i.e., CPUs and GPUs. If the application is mapped to an appropriate processing core, then these architectures provide many performance ...
    • Model-based software testing for distributed systems and protocols 

      Wang, Rui (Doctoral thesis, 2020)
      Society is increasingly dependent on fault-tolerant cloud-based services which rely on the correctness and reliability of advanced distributed software systems and consensus protocols. The implementations of these systems ...
    • Multilevel Modelling of Coloured Petri Nets 

      Tena, Alejandro Rodriguez; Rutle, Adrian; Duran, Francisco; Kristensen, Lars Michael; Macías, Fernando (Journal article; Peer reviewed, 2018)
      Coloured Petri Nets (CPNs) is a modelling language for distributed systems which has been applied in a multitude of industrial cases. The supporting tool of CPNs is currently lacking important features such as having the ...
    • On modelling and validation of the MQTT IoT protocol for M2M communication 

      Tena, Alejandro Rodriguez; Kristensen, Lars Michael; Rutle, Adrian (Journal article; Peer reviewed, 2018)
      Machine to Machine (M2M) communication and Internet of Things (IoT) are becoming still more pervasive with the increase of communicating devices used in cyber-physical environments. A prominent approach to communication ...
    • The density-based clustering method for privacy-preserving data mining 

      Wu, Jimmy Ming-Tai; Lin, Chun Wei; Fournier-Viger, Philippe; Djenouri, Youcef; Chen, Chun-Hao; Li, Zhongcui (Journal article; Peer reviewed, 2019)
      Privacy-preserving data mining has become an interesting and emerging issue in recent years since it can, not only hide the sensitive information but still mine the meaningful knowledge at the same time. Since privacy-preserving ...