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In the context of next generation radio telescopes, like the Square Kilometre Array, the efficient processing of large-scale datasets is extremely important. Convex optimisation tasks under the compressive sensing framework have recently emerged and provid ...
Squall is a scalable online query engine that runs complex analytics in a cluster using skew-resilient, adaptive operators. Online processing implies that results are incrementally built as the input arrives, and it is ubiquitous for many applications such ...
Cloud computing promises flexibility and high performance for users and high cost-efficiency for operators. Nevertheless, most cloud facilities operate at very low utilization, hurting both cost effectiveness and future scalability. We present Quasar, a cl ...
Software development has taken a fundamental turn. Software today has gone from simple, closed programs running on a single machine, to massively open programs, patching together user experiences byway of responses received via hundreds of network requests ...
The dramatic rise of time-series data produced in a variety of contexts, such as stock markets, mobile sensing, sensor networks, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation systems (e.g., Apach ...
GSN (Global Sensor Networks) is capable of managing configurable virtual sensors through a wide range of wrappers, and is able to manage one-shot and continuous queries, even in a distributed environment with several GSN instances. However, each GSN instan ...
Data replication, the main failure resilience strategy used for big data analytics jobs, can be unnecessarily inefficient. It can cause serious performance degradation when applied to intermediate job outputs in multi-job computations. For instance, for I/ ...
Humans navigate crowded spaces such as a university campus by following common sense rules based on social etiquette. In this paper, we argue that in order to enable the design of new target tracking or trajectory forecasting methods that can take full adv ...
The dramatic rise of streaming time-series data produced in a vari- ety of contexts, such as stock markets, mobile sensing, sensor net- works, data centre monitoring, etc., has fuelled the development of large-scale distributed real-time computation system ...
Many programs have an inherently reactive nature imposed by the functional dependencies between their data and external events. Classically, these dependencies are dealt with using callbacks. Reactive programming with first-class reactive values is a parad ...