Multi-Xpath query processing in client-server environment

Master'sMASTER OF SCIENC

SIQXC: Schema Independent Queryable XML Compression for Smartphones

The explosive growth of XML use over the last decade has led to a lot of research on how to best store and access it. This growth has resulted in XML being described as a de facto standard for storage and exchange of data over the web. However, XML has high redundancy because of its self-­‐ describing nature making it verbose. The verbose nature of XML poses a storage problem. This has led to much research devoted to XML compression. It has become of more interest since the use of resource constrained devices is also on the rise. These devices are limited in storage space, processing power and also have finite energy. Therefore, these devices cannot cope with storing and processing large XML documents. XML queryable compression methods could be a solution but none of them has a query processor that runs on such devices. Currently, wireless connections are used to alleviate the problem but they have adverse effects on the battery life. They are therefore not a sustainable solution. This thesis describes an attempt to address this problem by proposing a queryable compressor (SIQXC) with a query processor that runs in a resource constrained environment thereby lowering wireless connection dependency yet alleviating the storage problem. It applies a novel simple 2 tuple integer encoding system, clustering and gzip. SIQXC achieves an average compression ratio of 70% which is higher than most queryable XML compressors and also supports a wide range of XPATH operators making it competitive approach. It was tested through a practical implementation evaluated against the real data that is usually used for XML benchmarking. The evaluation covered the compression ratio, compression time and query evaluation accuracy and response time. SIQXC allows users to some extent locally store and manipulate the otherwise verbose XML on their Smartphones

Query-driven indexing in large-scale distributed systems

Efficient and effective search in large-scale data repositories requires complex indexing solutions deployed on a large number of servers. Web search engines such as Google and Yahoo! already rely upon complex systems to be able to return relevant query results and keep processing times within the comfortable sub-second limit. Nevertheless, the exponential growth of the amount of content on the Web poses serious challenges with respect to scalability. Coping with these challenges requires novel indexing solutions that not only remain scalable but also preserve the search accuracy. In this thesis we introduce and explore the concept of query-driven indexing – an index construction strategy that uses caching techniques to adapt to the querying patterns expressed by users. We suggest to abandon the strict difference between indexing and caching, and to build a distributed indexing structure, or a distributed cache, such that it is optimized for the current query load. Our experimental and theoretical analysis shows that employing query-driven indexing is especially beneficial when the content is (geographically) distributed in a Peer-to-Peer network. In such a setting extensive bandwidth consumption has been identified as one of the major obstacles for efficient large-scale search. Our indexing mechanisms combat this problem by maintaining the query popularity statistics and by indexing (caching) intermediate query results that are requested frequently. We present several indexing strategies for processing multi-keyword and XPath queries over distributed collections of textual and XML documents respectively. Experimental evaluations show significant overall traffic reduction compared to the state-of-the-art approaches. We also study possible query-driven optimizations for Web search engine architectures. Contrary to the Peer-to-Peer setting, Web search engines use centralized caching of query results to reduce the processing load on the main index. We analyze real search engine query logs and show that the changes in query traffic that such a results cache induces fundamentally affect indexing performance. In particular, we study its impact on index pruning efficiency. We show that combination of both techniques enables efficient reduction of the query processing costs and thus is practical to use in Web search engines

Complex adaptive systems based data integration : theory and applications

Data Definition Languages (DDLs) have been created and used to represent data in programming languages and in database dictionaries. This representation includes descriptions in the form of data fields and relations in the form of a hierarchy, with the common exception of relational databases where relations are flat. Network computing created an environment that enables relatively easy and inexpensive exchange of data. What followed was the creation of new DDLs claiming better support for automatic data integration. It is uncertain from the literature if any real progress has been made toward achieving an ideal state or limit condition of automatic data integration. This research asserts that difficulties in accomplishing integration are indicative of socio-cultural systems in general and are caused by some measurable attributes common in DDLs. This research’s main contributions are: (1) a theory of data integration requirements to fully support automatic data integration from autonomous heterogeneous data sources; (2) the identification of measurable related abstract attributes (Variety, Tension, and Entropy); (3) the development of tools to measure them. The research uses a multi-theoretic lens to define and articulate these attributes and their measurements. The proposed theory is founded on the Law of Requisite Variety, Information Theory, Complex Adaptive Systems (CAS) theory, Sowa’s Meaning Preservation framework and Zipf distributions of words and meanings. Using the theory, the attributes, and their measures, this research proposes a framework for objectively evaluating the suitability of any data definition language with respect to degrees of automatic data integration. This research uses thirteen data structures constructed with various DDLs from the 1960\u27s to date. No DDL examined (and therefore no DDL similar to those examined) is designed to satisfy the law of requisite variety. No DDL examined is designed to support CAS evolutionary processes that could result in fully automated integration of heterogeneous data sources. There is no significant difference in measures of Variety, Tension, and Entropy among DDLs investigated in this research. A direction to overcome the common limitations discovered in this research is suggested and tested by proposing GlossoMote, a theoretical mathematically sound description language that satisfies the data integration theory requirements. The DDL, named GlossoMote, is not merely a new syntax, it is a drastic departure from existing DDL constructs. The feasibility of the approach is demonstrated with a small scale experiment and evaluated using the proposed assessment framework and other means. The promising results require additional research to evaluate GlossoMote’s approach commercial use potential

Techniques efficaces basées sur des vues matérialisées pour la gestion des données du Web (algorithmes et systèmes)

Le langage XML, proposé par le W3C, est aujourd hui utilisé comme un modèle de données pour le stockage et l interrogation de grands volumes de données dans les systèmes de bases de données. En dépit d importants travaux de recherche et le développement de systèmes efficace, le traitement de grands volumes de données XML pose encore des problèmes des performance dus à la complexité et hétérogénéité des données ainsi qu à la complexité des langages courants d interrogation XML. Les vues matérialisées sont employées depuis des décennies dans les bases de données afin de raccourcir les temps de traitement des requêtes. Elles peuvent être considérées les résultats de requêtes pré-calculées, que l on réutilise afin d éviter de recalculer (complètement ou partiellement) une nouvelle requête. Les vues matérialisées ont fait l objet de nombreuses recherches, en particulier dans le contexte des entrepôts des données relationnelles.Cette thèse étudie l applicabilité de techniques de vues matérialisées pour optimiser les performances des systèmes de gestion de données Web, et en particulier XML, dans des environnements distribués. Dans cette thèse, nos apportons trois contributions.D abord, nous considérons le problème de la sélection des meilleures vues à matérialiser dans un espace de stockage donné, afin d améliorer la performance d une charge de travail des requêtes. Nous sommes les premiers à considérer un sous-langage de XQuery enrichi avec la possibilité de sélectionner des noeuds multiples et à de multiples niveaux de granularités. La difficulté dans ce contexte vient de la puissance expressive et des caractéristiques du langage des requêtes et des vues, et de la taille de l espace de recherche de vues que l on pourrait matérialiser.Alors que le problème général a une complexité prohibitive, nous proposons et étudions un algorithme heuristique et démontrer ses performances supérieures par rapport à l état de l art.Deuxièmement, nous considérons la gestion de grands corpus XML dans des réseaux pair à pair, basées sur des tables de hachage distribuées. Nous considérons la plateforme ViP2P dans laquelle des vues XML distribuées sont matérialisées à partir des données publiées dans le réseau, puis exploitées pour répondre efficacement aux requêtes émises par un pair du réseau. Nous y avons apporté d importantes optimisations orientées sur le passage à l échelle, et nous avons caractérisé la performance du système par une série d expériences déployées dans un réseau à grande échelle. Ces expériences dépassent de plusieurs ordres de grandeur les systèmes similaires en termes de volumes de données et de débit de dissémination des données. Cette étude est à ce jour la plus complète concernant une plateforme de gestion de contenus XML déployée entièrement et testée à une échelle réelle.Enfin, nous présentons une nouvelle approche de dissémination de données dans un système d abonnements, en présence de contraintes sur les ressources CPU et réseau disponibles; cette approche est mise en oeuvre dans le cadre de notre plateforme Delta. Le passage à l échelle est obtenu en déchargeant le fournisseur de données de l effort de répondre à une partie des abonnements. Pour cela, nous tirons profit de techniques de réécriture de requêtes à l aide de vues afin de diffuser les données de ces abonnements, à partir d autres abonnements.Notre contribution principale est un nouvel algorithme qui organise les vues dans un réseau de dissémination d information multi-niveaux ; ce réseau est calculé à l aide d outils techniques de programmation linéaire afin de passer à l échelle pour de grands nombres de vues, respecter les contraintes de capacité du système, et minimiser les délais de propagation des information. L efficacité et la performance de notre algorithme est confirmée par notre évaluation expérimentale, qui inclut l étude d un déploiement réel dans un réseau WAN.XML was recommended by W3C in 1998 as a markup language to be used by device- and system-independent methods of representing information. XML is nowadays used as a data model for storing and querying large volumes of data in database systems. In spite of significant research and systems development, many performance problems are raised by processing very large amounts of XML data. Materialized views have long been used in databases to speed up queries. Materialized views can be seen as precomputed query results that can be re-used to evaluate (part of) another query, and have been a topic of intensive research, in particular in the context of relational data warehousing. This thesis investigates the applicability of materialized views techniques to optimize the performance of Web data management tools, in particular in distributed settings, considering XML data and queries. We make three contributions.We first consider the problem of choosing the best views to materialize within a given space budget in order to improve the performance of a query workload. Our work is the first to address the view selection problem for a rich subset of XQuery. The challenges we face stem from the expressive power and features of both the query and view languages and from the size of the search space of candidate views to materialize. While the general problem has prohibitive complexity, we propose and study a heuristic algorithm and demonstrate its superior performance compared to the state of the art.Second, we consider the management of large XML corpora in peer-to-peer networks, based on distributed hash tables (or DHTs, in short). We consider a platform leveraging distributed materialized XML views, defined by arbitrary XML queries, filled in with data published anywhere in the network, and exploited to efficiently answer queries issued by any network peer. This thesis has contributed important scalability oriented optimizations, as well as a comprehensive set of experiments deployed in a country-wide WAN. These experiments outgrow by orders of magnitude similar competitor systems in terms of data volumes and data dissemination throughput. Thus, they are the most advanced in understanding the performance behavior of DHT-based XML content management in real settings.Finally, we present a novel approach for scalable content-based publish/subscribe (pub/sub, in short) in the presence of constraints on the available computational resources of data publishers. We achieve scalability by off-loading subscriptions from the publisher, and leveraging view-based query rewriting to feed these subscriptions from the data accumulated in others. Our main contribution is a novel algorithm for organizing subscriptions in a multi-level dissemination network in order to serve large numbers of subscriptions, respect capacity constraints, and minimize latency. The efficiency and effectiveness of our algorithm are confirmed through extensive experiments and a large deployment in a WAN.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Cloud-based Communications Planning Collaboration and Interoperability

Communications planning is a key part of the Marine Corps operational planning process. The ability to design and analyze communication network plans efficiently and accurately has a direct impact on the ability of commanders to command and control actions on the battlefield. Portions of the current process of communications network planning for military exercises and operations in the Marine Corps are unnecessarily inefficient and susceptible to human error. At the heart of network planning is the creation of accurate high-level diagrams that depict the details of the planned network topology for use in network installation, maintenance and operation. These diagrams are referenced at all levels in the planning, installation, operation and maintenance of the resultant communications architecture. Development and iterative refinement of these high-level network diagrams is a fragmented manual process. Despite the heavy reliance on network diagrams in the planning process, no software application currently exists that is designed specifically for their creation. This thesis proposes a cloud-based application for communications planning. It describes the benefits achievable through automation, collaboration and application interoperability, and provides recommendations for development of such a system. It concludes by presenting an implementation of these recommendations via a proof of concept application.http://archive.org/details/cloudbasedcommun109457400Captain, United States Marine Corps,Major, United States Marine Corp

Efficient and Flexible Search in Large Scale Distributed Systems

Peer-to-peer (P2P) technology has triggered a wide range of distributed systems beyond simple file-sharing. Distributed XML databases, distributed computing, server-less web publishing and networked resource/service sharing are only a few to name. Despite of the diversity in applications, these systems share a common problem regarding searching and discovery of information. This commonality stems from the transitory nodes population and volatile information content in the participating nodes. In such dynamic environment, users are not expected to have the exact information about the available objects in the system. Rather queries are based on partial information, which requires the search mechanism to be flexible. On the other hand, to scale with network size the search mechanism is required to be bandwidth efficient. Since the advent of P2P technology experts from industry and academia have proposed a number of search techniques - none of which is able to provide satisfactory solution to the conflicting requirements of search efficiency and flexibility. Structured search techniques, mostly Distributed Hash Table (DHT)-based, are bandwidth efficient while semi(un)-structured techniques are flexible. But, neither achieves both ends. This thesis defines the Distributed Pattern Matching (DPM) problem. The DPM problem is to discover a pattern (\ie bit-vector) using any subset of its 1-bits, under the assumption that the patterns are distributed across a large population of networked nodes. Search problem in many distributed systems can be reduced to the DPM problem. This thesis also presents two distinct search mechanisms, named Distributed Pattern Matching System (DPMS) and Plexus, for solving the DPM problem. DPMS is a semi-structured, hierarchical architecture aiming to discover a predefined number of matches by visiting a small number of nodes. Plexus, on the other hand, is a structured search mechanism based on the theory of Error Correcting Code (ECC). The design goal behind Plexus is to discover all the matches by visiting a reasonable number of nodes

A Framework for Model-based Testing of Integrated Modular Avionics

In modern aircraft, electronics and control systems are designed based on the Integrated Modular Avionics (IMA) system architecture. While this has numerous advantages (reduction of weight, reduced power and fuel consumption, reduction of development cost and certification effort), the IMA platform also adds an additional layer of complexity. Due to the safety-critical nature of many avionics functions careful and accurate verification and testing are imperative. This thesis describes results achieved from research on model-based testing of IMA systems, in part obtained during the European research project SCARLETT. It presents a complete framework which enables IMA domain experts to design and run model-based tests on bare module, configured module, and application level in a standardised test environment. The first part of this thesis provides background information on the relevant topics: the IMA concept, domain-specific languages, model-based testing, and the TTCN-3 standard. The second part introduces the IMA Test Modelling Language (ITML) framework and its components. It describes a tailored TTCN-3 test environment with appropriate adapters and codecs. Based on MetaEdit and its meta-metamodel GOPPRR, it defines the three variants of the domain-specific language ITML, each with its abstract and concrete syntax as well as static and dynamic semantics. The process of test procedure generation from ITML models is explained in detail. Furthermore, the design and implementation of a universal Test Agent is shown. A dedicated communication protocol for controlling the agent is defined as well. The third part provides an evaluation of the framework. It shows usage scenarios in the SCARLETT project, gives a comparison to related tools and approaches, and explains the advantages of using the ITML framework for an IMA domain expert. The final part presents several example ITML models. It also provides reference material like XML schemata, framework source code, and model validators

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

A software architecture for electro-mobility services: a milestone for sustainable remote vehicle capabilities

To face the tough competition, changing markets and technologies in automotive industry, automakers have to be highly innovative. In the previous decades, innovations were electronics and IT-driven, which increased exponentially the complexity of vehicle’s internal network. Furthermore, the growing expectations and preferences of customers oblige these manufacturers to adapt their business models and to also propose mobility-based services. One other hand, there is also an increasing pressure from regulators to significantly reduce the environmental footprint in transportation and mobility, down to zero in the foreseeable future. This dissertation investigates an architecture for communication and data exchange within a complex and heterogeneous ecosystem. This communication takes place between various third-party entities on one side, and between these entities and the infrastructure on the other. The proposed solution reduces considerably the complexity of vehicle communication and within the parties involved in the ODX life cycle. In such an heterogeneous environment, a particular attention is paid to the protection of confidential and private data. Confidential data here refers to the OEM’s know-how which is enclosed in vehicle projects. The data delivered by a car during a vehicle communication session might contain private data from customers. Our solution ensures that every entity of this ecosystem has access only to data it has the right to. We designed our solution to be non-technological-coupling so that it can be implemented in any platform to benefit from the best environment suited for each task. We also proposed a data model for vehicle projects, which improves query time during a vehicle diagnostic session. The scalability and the backwards compatibility were also taken into account during the design phase of our solution. We proposed the necessary algorithms and the workflow to perform an efficient vehicle diagnostic with considerably lower latency and substantially better complexity time and space than current solutions. To prove the practicality of our design, we presented a prototypical implementation of our design. Then, we analyzed the results of a series of tests we performed on several vehicle models and projects. We also evaluated the prototype against quality attributes in software engineering