The emergence of mobile and ambient computing technologies brings democratization in the access to information and data; services play a crucial role, thereby opening new research challenges for data querying. A promising method to access data within ...

One of the leading challenges for pervasive computing is to ease the application development to smoothly handle the surrounding environment. We consider the case where the environment produces heterogeneous and continuous data, e. g. temperature ...

Physical design represents one of the hardest problems for database management systems. Without proper tuning, systems cannot achieve good performance. Offline indexing creates indexes a priori assuming good workload knowledge and idle time. More ...

During the last decade, data management and storage have become increasingly distributed. In consideration of the huge amount of data available in such systems, advanced query operators, such as skyline queries, are necessary to help users process the ...

General-purpose streaming systems support diverse application domains with powerful and user-defined stream operators. Most general-purpose streaming systems have their own, non-XML, internal data representation. However, streaming input is often either ...

Database engines often consume significant power during query processing activities, motivating researchers to investigate the redesign of their internals to minimize these overheads. While the prior literature has dealt exclusively with average power ...

We propose new adaptive runtime techniques for MapReduce that improve performance and simplify job tuning. We implement these techniques by breaking a key assumption of MapReduce that mappers run in isolation. Instead, our mappers communicate through a ...

Summarizability in a multidimensional (MD) database refers to the correct reusability of pre-computed aggregate queries (or views) when computing higher-level aggregations or roll-ups. A dimension instance has this property if and only if it is strict ...

The inherent flexibility of the RDF data model has led to its notable adoption in many domains, especially in the area of life-sciences. Some of these domains have an emerging need to access data integrated from various distributed sources of ...

Query optimization in RDF Stores is a challenging problem as SPARQL queries typically contain many more joins than equivalent relational plans, and hence lead to a large join order search space. In such cases, cost-based query optimization often is not ...

Given a multi-features data set, a best preference query (BPQ) computes the maximal preference score (MPS) that the tuples in the data set can achieve with respect to a preference function. BPQs are very useful in applications where users want to ...

Many stream processing applications require access to a multitude of streaming as well as stored data sources. Yet there is no clear semantics for correct continuous query execution over these data sources in the face of concurrent access and failures. ...

With the popularization of GPS-enabled devices there is an increasing interest for location-based queries. In this context, one interesting problem is processing top-k spatial keyword queries. Given a set of objects with a textual description (e.g., ...

Implementing recursive algorithms on computing clusters presents a number of new challenges. In particular, we consider the endgame problem: later rounds of a recursion often transfer only small amounts of data, causing high overhead for interprocessor ...

Self-join, which joins a relation with itself, is a prevalent operation in relational database systems. Despite its wide applicability, there has been little attention devoted to improving its performance. In this paper, we present SCALE (<u>S</u>ort ...

In data mining applications and spatial and multimedia databases, a useful tool is the kNN join, which is to produce the k nearest neighbors (NN), from a dataset S, of every point in a dataset R. Since it involves both the join and the NN search, ...