Smart metering is an essential feature of smart grids, allowing residential customers to monitor and reduce electricity costs. Devices called smart meters allows residential customers to monitor and reduce electricity costs, promoting energy saving, demand management, and energy efficiency. However, monitoring a households' energy consumption through smart meters poses serious privacy threats, and have thus become a major privacy issue. Hence, a significant amount of research has appeared recently with the purpose of providing methods and mechanisms to reconcile smart metering technologies and privacy requirements. However, most current approaches fall short in meeting one of several of the requirements for privacy preserving smart metering systems. In this paper we show how Intel SGX technology can be used to provide a simple and general solution for the smart metering privacy problem that meets all these requirements in a satisfactory way. Moreover, we present also an implementation of the proposed architecture as well as a series of experiments that have been carried out in order to assess how the proposed solution performs in comparison to a second implementation of the architecture that completely disregards privacy issues.
In this paper, we present our approach on solving the DEBS Grand Challenge using StreamMine3G, a distributed, highly scalable, elastic and fault tolerant ESP system. We will provide an overview about the system architecture of StreamMine3G and implementation details of an application aimed at consumption prediction and outlier detection. Using our elastic approach, we can provide an accurate prediction as we can keep a practically unbounded history able to deal with high volume, highly fluctuating workloads. Our system also provides techniques for dealing with incomplete data in the source stream, which is a common problem when processing data from a large number of sources. Finally, we provide performance measurements showing that we are able to process the dataset given as part of the 2014 DEBS Challenge (135 GB) at a throughput of up to 40 kEvents/s.
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