4,759 research outputs found
The Odyssey Approach for Optimizing Federated SPARQL Queries
Answering queries over a federation of SPARQL endpoints requires combining
data from more than one data source. Optimizing queries in such scenarios is
particularly challenging not only because of (i) the large variety of possible
query execution plans that correctly answer the query but also because (ii)
there is only limited access to statistics about schema and instance data of
remote sources. To overcome these challenges, most federated query engines rely
on heuristics to reduce the space of possible query execution plans or on
dynamic programming strategies to produce optimal plans. Nevertheless, these
plans may still exhibit a high number of intermediate results or high execution
times because of heuristics and inaccurate cost estimations. In this paper, we
present Odyssey, an approach that uses statistics that allow for a more
accurate cost estimation for federated queries and therefore enables Odyssey to
produce better query execution plans. Our experimental results show that
Odyssey produces query execution plans that are better in terms of data
transfer and execution time than state-of-the-art optimizers. Our experiments
using the FedBench benchmark show execution time gains of at least 25 times on
average.Comment: 16 pages, 10 figure
Context-driven progressive enhancement of mobile web applications: a multicriteria decision-making approach
Personal computing has become all about mobile and embedded devices. As a result, the adoption rate of smartphones is rapidly increasing and this trend has set a need for mobile applications to be available at anytime, anywhere and on any device. Despite the obvious advantages of such immersive mobile applications, software developers are increasingly facing the challenges related to device fragmentation. Current application development solutions are insufficiently prepared for handling the enormous variety of software platforms and hardware characteristics covering the mobile eco-system. As a result, maintaining a viable balance between development costs and market coverage has turned out to be a challenging issue when developing mobile applications. This article proposes a context-aware software platform for the development and delivery of self-adaptive mobile applications over the Web. An adaptive application composition approach is introduced, capable of autonomously bypassing context-related fragmentation issues. This goal is achieved by incorporating and validating the concept of fine-grained progressive application enhancements based on a multicriteria decision-making strategy
Abmash: Mashing Up Legacy Web Applications by Automated Imitation of Human Actions
Many business web-based applications do not offer applications programming
interfaces (APIs) to enable other applications to access their data and
functions in a programmatic manner. This makes their composition difficult (for
instance to synchronize data between two applications). To address this
challenge, this paper presents Abmash, an approach to facilitate the
integration of such legacy web applications by automatically imitating human
interactions with them. By automatically interacting with the graphical user
interface (GUI) of web applications, the system supports all forms of
integrations including bi-directional interactions and is able to interact with
AJAX-based applications. Furthermore, the integration programs are easy to
write since they deal with end-user, visual user-interface elements. The
integration code is simple enough to be called a "mashup".Comment: Software: Practice and Experience (2013)
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