SMIL State: an architecture and implementation for adaptive time-based web applications

In this paper we examine adaptive time-based web applications (or presentations). These are interactive presentations where time dictates which parts of the application are presented (providing the major structuring paradigm), and that require interactivity and other dynamic adaptation. We investigate the current technologies available to create such presentations and their shortcomings, and suggest a mechanism for addressing these shortcomings. This mechanism, SMIL State, can be used to add user-defined state to declarative time-based languages such as SMIL or SVG animation, thereby enabling the author to create control flows that are difficult to realize within the temporal containment model of the host languages. In addition, SMIL State can be used as a bridging mechanism between languages, enabling easy integration of external components into the web application. Finally, SMIL State enables richer expressions for content control. This paper defines SMIL State in terms of an introductory example, followed by a detailed specification of the State model. Next, the implementation of this model is discussed. We conclude with a set of potential use cases, including dynamic content adaptation and delayed insertion of custom content such as advertisements. © 2009 Springer Science+Business Media, LLC

Data Mining-based Fragmentation of XML Data Warehouses

With the multiplication of XML data sources, many XML data warehouse models have been proposed to handle data heterogeneity and complexity in a way relational data warehouses fail to achieve. However, XML-native database systems currently suffer from limited performances, both in terms of manageable data volume and response time. Fragmentation helps address both these issues. Derived horizontal fragmentation is typically used in relational data warehouses and can definitely be adapted to the XML context. However, the number of fragments produced by classical algorithms is difficult to control. In this paper, we propose the use of a k-means-based fragmentation approach that allows to master the number of fragments through its $k$ parameter. We experimentally compare its efficiency to classical derived horizontal fragmentation algorithms adapted to XML data warehouses and show its superiority

Data replication and update propagation in XML P2P data management systems

XML P2P data management systems are P2P systems that use XML as the underlying data format shared between peers in the network. These systems aim to bring the benefits of XML and P2P systems to the distributed data management field. However, P2P systems are known for their lack of central control and high degree of autonomy. Peers may leave the network at any time at will, increasing the risk of data loss. Despite this, most research in XML P2P systems focus on novel and efficient XML indexing and retrieval techniques. Mechanisms for ensuring data availability in XML P2P systems has received comparatively little attention. This project attempts to address this issue. We design an XML P2P data management framework to improve data availability. This framework includes mechanisms for wide-spread data replication, replica location and update propagation. It allows XML documents to be broken down into fragments. By doing so, we aim to reduce the cost of replicating data by distributing smaller XML fragments throughout the network rather than entire documents. To tackle the data replication problem, we propose a suite of selection and placement algorithms that may be interchanged to form a particular replication strategy. To support the placement of replicas anywhere in the network, we use a Fragment Location Catalogue, a global index that maintains the locations of replicas. We also propose a lazy update propagation algorithm to propagate updates to replicas. Experiments show that the data replication algorithms improve data availability in our experimental network environment. We also find that breaking XML documents into smaller pieces and replicating those instead of whole XML documents considerably reduces the replication cost, but at the price of some loss in data availability. For the update propagation tests, we find that the probability that queries return up-to-date results increases, but improvements to the algorithm are necessary to handle environments with high update rates

Distributed XML Query Processing

While centralized query processing over collections of XML data stored at a single site is a well understood problem, centralized query evaluation techniques are inherently limited in their scalability when presented with large collections (or a single, large document) and heavy query workloads. In the context of relational query processing, similar scalability challenges have been overcome by partitioning data collections, distributing them across the sites of a distributed system, and then evaluating queries in a distributed fashion, usually in a way that ensures locality between (sub-)queries and their relevant data. This thesis presents a suite of query evaluation techniques for XML data that follow a similar approach to address the scalability problems encountered by XML query evaluation. Due to the significant differences in data and query models between relational and XML query processing, it is not possible to directly apply distributed query evaluation techniques designed for relational data to the XML scenario. Instead, new distributed query evaluation techniques need to be developed. Thus, in this thesis, an end-to-end solution to the scalability problems encountered by XML query processing is proposed. Based on a data partitioning model that supports both horizontal and vertical fragmentation steps (or any combination of the two), XML collections are fragmented and distributed across the sites of a distributed system. Then, a suite of distributed query evaluation strategies is proposed. These query evaluation techniques ensure locality between each fragment of the collection and the parts of the query corresponding to the data in this fragment. Special attention is paid to scalability and query performance, which is achieved by ensuring a high degree of parallelism during distributed query evaluation and by avoiding access to irrelevant portions of the data. For maximum flexibility, the suite of distributed query evaluation techniques proposed in this thesis provides several alternative approaches for evaluating a given query over a given distributed collection. Thus, to achieve the best performance, it is necessary to predict and compare the expected performance of each of these alternatives. In this work, this is accomplished through a query optimization technique based on a distribution-aware cost model. The same cost model is also used to fine-tune the way a collection is fragmented to the demands of the query workload evaluated over this collection. To evaluate the performance impact of the distributed query evaluation techniques proposed in this thesis, the techniques were implemented within a production-quality XML database system. Based on this implementation, a thorough experimental evaluation was performed. The results of this evaluation confirm that the distributed query evaluation techniques introduced here lead to significant improvements in query performance and scalability both when compared to centralized techniques and when compared to existing distributed query evaluation techniques

Adding state to declarative languages to enable web applications

On the web, media tend to be encoded in declarative formats, which facilitate accessibility, reuse, and transformation. Web applications, on the other hand, are created with more procedural technology and do not enjoy these benefits. In this thesis we examine how this can be fixed. We examine a small part of the problem space, adaptive time based applications, and investigate how we can extend existing declarative languages to fa

MULTIHIERARCHICAL DOCUMENTS AND FINE-GRAINED ACCESS CONTROL

This work presents new models and algorithms for creating, modifying, and controlling access to complex text. The digitization of texts opens new opportunities for preservation, access, and analysis, but at the same time raises questions regarding how to represent and collaboratively edit such texts. Two issues of particular interest are modelling the relationships of markup (annotations) in complex texts, and controlling the creation and modification of those texts. This work addresses and connects these issues, with emphasis on data modelling, algorithms, and computational complexity; and contributes new results in these areas of research. Although hierarchical models of text and markup are common, complex texts often exhibit layers of overlapping structure that are best described by multihierarchical markup. We develop a new model of multihierarchical markup, the globally ordered GODDAG, that combines features of both graph- and range-based models of markup, allowing documents to be unambiguously serialized. We describe extensions to the XPath query language to support globally ordered GODDAGs, provide semantics for a set of update operations on this structure, and provide algorithms for converting between two different representations of the globally ordered GODDAG. Managing the collaborative editing of documents can require restricting the types of changes different editors may make, while not altogether restricting their access to the document. Fine-grained access control allows precisely these kinds of restrictions on the operations that a user is or is not permitted to perform on a document. We describe a rule-based model of fine-grained access control for updates of hierarchical documents, and in this context analyze the document generation problem: determining whether a document could have been created without violating a particular access control policy. We show that this problem is undecidable in the general case and provide computational complexity bounds for a number of restricted variants of the problem. Finally, we extend our fine-grained access control model from hierarchical to multihierarchical documents. We provide semantics for fine-grained access control policies that control splice-in, splice-out, and rename operations on globally ordered GODDAGs, and show that the multihierarchical version of the document generation problem remains undecidable

Revised CONNECT Architecture

Interoperability remains a fundamental challenge when connecting heterogeneous systems which encounter and spontaneously communicate with one another in pervasive computing environments. This challenge is exasperated by the highly heterogeneous technologies employed by each of the interacting parties, i.e., in terms of hardware, operating system, middleware protocols, and application protocols. The key aim of the CONNECT project is to drop this heterogeneity barrier and achieve universal interoperability. Here we report on the revised CONNECT architecture, highlighting the integration of the work carried out to integrate the CONNECT enablers developed by the different partners; in particular, we present the progress of this work towards a finalised concrete architecture. In the third year this architecture has been enhanced to: i) produce concrete CONNECTors, ii) match networked systems based upon their goals and intent, and iii) use learning technologies to find the affordance of a system. We also report on the application of the CONNECT approach to streaming based systems, further considering exploitation of CONNECT in the mobile environment