Leveraging Mobile Edge Computing on Smart Grids Using LTE Cellular Networks Given the advance of the Smart Grid technology, the electrical grid is now in a process of transformation never seen in history. This new grid model allows customers and providers to generate and manage electrical power efficiently. To support such transformation, a key element of the model is the communication network responsible for delivering measurement data from sensors on the grid to the applications that analyze and adapt distribution according to demands. This work proposes and evaluates a system architecture that copes with reliability and latency demands that are of much importance for a successful Smart Grid deployment, also considering the internal design of distributed applications in the context of Smart Grids. The architecture adopts a Mobile Edge Computing based infrastructure that is suitable for 4G and 5G mobile cellular networks. Experiments made on NS3 shows that the proposed system architecture is capable of handling a realistic number of smart meters while providing low latency and network reliability, supporting many use cases of a Smart Grid deployment.

A performance comparison of heuristics for scheduling jobs in hybrid mobile topologies Hardware improvements of mobile devices have allowed them to be considered as firstclass resources at the edge, which has led to the need to propose new techniques and scheduling heuristics to make efficient usage of these devices. Current scheduling heuristics available in the literature do not take into account mobile grid nodes that do not rely on batteries to work, a factor that is of great importance in the advent of mobileedge computing. In this paper we propose a simple algorithm that incorporates a more advanced awareness of a mobile deviceu0027s power supply and we show that incorporating this characteristic can enable these heuristics to manage edge resources in a more efficient way.