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Many Big Data applications in science and industry have arisen, that require large amounts of streamed or event data to be analyzed with low latency. This paper presents a reactive strategy to enforce latency guarantees in data flows running on scalable Stream Processing Engines (SPEs), while minimizing resource consumption. We introduce a model for estimating the latency of a data flow, when the...
The ability to process large numbers of continuous data streams in a near-real-time fashion has become a crucial prerequisite for many scientific and industrial use cases in recent years. While the individual data streams are usually trivial to process, their aggregated data volumes easily exceed the scalability of traditional stream processing systems. At the same time, massively-parallel data processing...
The ongoing integration of renewable energy sources is likely to increase the fluctuations in the ratio of produced and consumed power. Several types of Demand Response (DR) programs have been proposed to deal with the increasing volatility of power production and consumption. Many of these, such as Real Time Pricing (RTP), require intensive monitoring of the consumers' power consumption. This is...
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