Software Defined Networking envisions smart centralized controllers governing the forwarding behavior of dumb low-cost switches. But are "dumb" switches an actual strategic choice, or (at least to some extent) are they a consequence of the lack of viable alternatives to OpenFlow as programmatic data plane forwarding interface? Indeed, some level of (programmable) control logic in the switches might be beneficial to offload logically centralized controllers (de facto complex distributed systems) from decisions just based on local states (versus network-wide knowledge), which could be handled at wire speed inside the device itself. Also, it would reduce the amount of flow processing tasks currently delegated to specialized middleboxes. The underlying challenge is: can we devise a stateful data plane programming abstraction (versus the stateless OpenFlow match/action table) which still entails high performance and remains consistent with the vendors' preference for closed platforms? We posit that a promising answer revolves around the usage of extended finite state machines, as an extension (super-set) of the OpenFlow match/action abstraction. We concretely turn our proposed abstraction into an actual table-based API, and, perhaps surprisingly, we show how it can be supported by (mostly) reusing core primitives already implemented in OpenFlow devices.

The residential sector is currently one of the major contributors to the global energy balance. However, the energy demand of residential users has been so far largely uncontrollable and inelastic with respect to the power grid conditions. With the massive introduction of renewable energy sources and the large variations in energy flows, also the residential sector is required to provide some flexibility in energy use so as to contribute to the stability and efficiency of the electric system. To address this issue, demand management mechanisms can be used to optimally manage the energy resources of customers and their energy demand profiles. A very promising technique is represented by demand-side management (DSM), which consists in a proactive method aimed at making users energy-efficient in the long term. In this paper, we survey the most relevant studies on optimization methods for DSM of residential consumers. Specifically, we review the related literature according to three axes defining contrasting characteristics of the schemes proposed: DSM for individual users versus DSM for cooperative consumers, deterministic DSM versus stochastic DSM and day-ahead DSM versus real-time DSM. Based on this classification, we provide a big picture of the key features of different approaches and techniques and discuss future research directions.

The Smart Meter (SM) is an essential tool for successful balancing the demand-offer energy curve. It allows the linking of the consumption and production measurements with the time information and the customer’s identity, enabling the substitution of flat-price billing with smarter solutions, such as Time-of-Use or Real-Time Pricing. In addition to sending data to the energy operators for billing and monitoring purposes, Smart Meters must be able to send the same data to customer devices in near-real-time conditions, enabling new services such as instant energy awareness and home automation. In this article, we review the ongoing situation in Europe regarding real-time services for the final customers. Then, we review the architectural and technological options that have been considered for the roll-out phase of the Italian second generation of Smart Meters. Finally, we identify a collection of use cases, along with their functional and performance requirements, and discuss what architectures and communications technologies can meet these requirements.