The concept of Cyber-Physical Systems (CPSs), which combine computation, networking, and physical processes, is considered to be beneficial to smart grid applications. This study presents an integrated simulation environment to provide a unified platform for the investigation of smart grid applications involving power grid monitoring, communication, and control. In contrast to the existing approaches, this environment allows the network simulator to operate independently, importing its results to the power system simulation. This resolves conflicts between discrete event simulation and continuous simulation. In addition, several data compensation methods are proposed and investigated under different network delay conditions. A case study of wide-area monitoring and control is provided, and the efficiency of the proposed simulation framework has been evaluated based on the experimental results.

Video streaming services are trending to be deployed on cloud. Cloud computing offers better stability and lower price than traditional IT facilities. Huge storage capacity is essential for video streaming service. More and more cloud providers appear so there are increasing cloud platforms to choose. A better choice is to use more than one data center, which is called multi-cloud. In this paper a closed-loop approach is proposed for optimizing Quality of Service (QoS) and cost. Modules of monitoring and controlling data centers are required as well as the application feedback such as video streaming services. An algorithm is proposed to help choose cloud providers and data centers in a multi-cloud environment as a video service manager. Performance with different video service workloads are evaluated. Compared with using only one cloud provider, dynamically deploying services in multi-cloud is better in aspects of both cost and QoS. If cloud service costs are different among data centers, the algorithm will help make choices to lower the cost and keep a high QoS.