Koen Vanthournout

Long-term individual household forecasting is useful in various applications, e.g., to determine customers’ advance payments. However, the literature on this type of forecasting is limited; existing methods either focus on short-term predictions for individual households, or long-term prediction at an aggregated level (e.g., neighborhood). To fill this gap, we present a method that predicts the monthly consumption of individual households over the next year, given only a few months of consumption data during the current year. Utility companies can exploit this method to predict the consumption of any customer for the next year even with incomplete data. The method consists of three steps: clustering the data using ${k}$ -means, prediction using an ensemble of forecasts based on the historical median distribution among similar households, and smoothing the predictions to remove weather-dependent patterns. The method is highly accurate as it finished third in the IEEE-CIS competition (and ranks first when leveraging insights from another team), focused on forecasting long-term household consumption with incomplete data. It is also very scalable thanks to its low computational complexity and weak data requirements: the method only requires a few months of historical data and no household-specific or weather information.

Overlay networks are increasingly receiving attention as a scalable and distributed platform to realise resource discovery for file-sharing applications. However, their potential application range is much broader, as they can even serve as a communications infrastructure for distributed control and automation, e.g., underlying the electricity infrastructure. This requires the support of generic primitives such as, e.g., attribute-based semantic routing. Due to their focus on file sharing, today's systems do not or inefficiently support attribute-based semantic routing. In response, this paper proposes an innovative overlay class that supports attribute-based, semantic addressing. Agora, a set of algorithms, provides an implementation of such semantic overlay network. The simulation results confirm the claims.