Energy Demand Shifting in Residential Households: The Interdependence between Social Practices and Technology Design

Emerging energy technologies, such as smart meters and solar photovoltaic systems (solar PV), are changing our relationship to energy. There is increasing evidence that households with solar PV on their roof tend naturally to shift their energy consumption in time to match their local generation, but what do people actually do to achieve this and how ICT can support them to optimize their consumption? In this paper we present a year-long user study to understand social practices around laundry routines and local energy generation. We highlight four challenges for the next generation of home energy management systems

Adaptive Dispatching of Tasks in the Cloud

The increasingly wide application of Cloud Computing enables the consolidation of tens of thousands of applications in shared infrastructures. Thus, meeting the quality of service requirements of so many diverse applications in such shared resource environments has become a real challenge, especially since the characteristics and workload of applications differ widely and may change over time. This paper presents an experimental system that can exploit a variety of online quality of service aware adaptive task allocation schemes, and three such schemes are designed and compared. These are a measurement driven algorithm that uses reinforcement learning, secondly a "sensible" allocation algorithm that assigns jobs to sub-systems that are observed to provide a lower response time, and then an algorithm that splits the job arrival stream into sub-streams at rates computed from the hosts' processing capabilities. All of these schemes are compared via measurements among themselves and with a simple round-robin scheduler, on two experimental test-beds with homogeneous and heterogeneous hosts having different processing capacities.Comment: 10 pages, 9 figure