The amount of information on the Web is spreading very rapidly. Users as well as companies bring data to the network and are willing to share with others. They quickly reach a situation where their information is hosted on many machines they own and on a large number of autonomous systems where they have accounts. Management of all this information is rapidly becoming beyond human expertise. We introduce WebdamExchange, a novel distributed knowledge-base model that includes logical statements for specifying information, access control, secrets, distribution, and knowledge about other peers. These statements can be communicated, replicated, queried, and updated, while keeping track of time and provenance. The resulting knowledge guides distributed data management. WebdamExchange model is based on WebdamLog, a new rule-based language for distributed data management that combines in a formal setting deductiverules as in Datalog with negation, (to specify intensional data) and active rules as in Datalog:: (for updates and communications). The model provides a novel setting with a strong emphasis on dynamicity and interactions(in a Web 2.0 style). Because the model is powerful, it provides a clean basis for the specification of complex distributed applications. Because it is simple, it provides a formal framework for studying many facets of the problem such as distribution, concurrency, and expressivity in the context of distributed autonomous peers. We also discuss an implementation of a proof-of-concept system that handles all the components of the knowledge base and experiments with a lighter system designed for smartphones. We believe that these contributions are a good foundation to overcome theproblems of Web data management, in particular with respect to access control.
Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00640725 |
Date | 28 September 2011 |
Creators | Galland, Alban |
Publisher | Université Paris Sud - Paris XI |
Source Sets | CCSD theses-EN-ligne, France |
Language | English |
Detected Language | English |
Type | PhD thesis |
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