Existing HTTP caches interact poorly with multiple Dynamic Adaptive Streaming over HTTP (DASH) streams of the same content: time and quality differences prevent a complete representation from being cached, reducing hit-ratios. We propose to consolidate near-simultaneous streams based on time or quality, where the improved cache performance makes this worthwhile. We estimate that there is a suff...

Selectivity estimation is an important task for query optimization. We propose a technique to perform range query estimation over multiple data streams using micro-clustering. The technique maintains cluster statistics in terms of micro-clusters and cosine series for all streams. These microclusters maintain data distribution information about the stream values using cosine coefficients. These ...

This paper studies the problem of mining frequent co-occurrence patterns across multiple data streams, which has not been addressed by existing works. Co-occurrence pattern in this context refers to the case that the same group of objects appear consecutively in multiple streams over a short time span, signaling tight correlations between these objects. The need for mining such patterns in real...

A video server allows to deliver multiple video streams to different clients. To provide the required amount of storage and bandwidth, a video server must contain a large number of disks. Since the retrieval rate of the disk and the consumption rate of the clients differ, the data retrieved from disk need to be temporarily stored in main memory, which is an important cost factor in a video serv...

Using multiple streams can improve the overall system performance by mitigating the data transfer overhead on heterogeneous systems. Currently, very few cases have been streamed to demonstrate the streaming performance impact and a systematic investigation of streaming necessity and how-to over a large number of test cases remains a gap. In this paper, we use a total of 56 benchmarks to build a...

Streams are infinite sequences over a given data type. A stream specification is a set of equations intended to define a stream. We propose a transformation from such a stream specification to a term rewriting system (TRS) in such a way that termination of the resulting TRS implies that the stream specification is well-defined, that is, admits a unique solution. As a consequence, proving well-d...

We propose a model, called a deliberation structure model, that represents streams of relevant messages in email communication. The deliberation structure model treats e-mail messages that include several topics and uses tree structure, called deliberation trees, that are based on Clark’s contribution trees to represent message structure. Deliberation trees are useful to visualize the message s...

This paper presents a new method to calculate the freshwater target for water using networks with single contaminant. The pinch point is determined by exploiting one of the features of water-pinch-analysis: freshwater is only necessary below the pinch. With the known pinch point, the calculation of the freshwater target becomes very simple, especially for the networks with many streams. The res...

Learning from data streams has been an important open research problem in the era of big data analytics. This paper investigates supervised machine learning techniques for mining data streams with application to online anomaly detection. Unlike conventional machine learning tasks, machine learning from data streams for online anomaly detection has several challenges: (i) data arriving sequentia...

We consider the problem of resource allocation in mining multiple data streams. Due to the large volume and the high speed of streaming data, mining algorithms must cope with the effects of system overload. How to realize maximum mining benefits under resource constraints becomes a challenging task. In this paper, we propose a load shedding scheme for classifying multiple data streams. We focus...