The Story of Webdamlog

International audienceWe summarize in this paper works about the management of data in a distributed manner based on Webdamlog, a datalog-extension. We point to relevant articles on these works. More references may be found there. 1 The Webdamlog approach Information of interest may be found on the Web in a variety of forms, in many systems, and with different access protocols. Today, the control and management of the diversity of data and tasks in this setting are beyond the skills of casual users [1]. Facing similar issues, companies see the cost of managing and integrating information skyrocketing. We are concerned with the management of Web data in place in a distributed manner, with a possibly large number of autonomous, heterogeneous systems collaborating to support certain tasks. We summarize in this paper works in this setting around Webdamlog and point to the relevant articles on it. The thesis is that managing the richness and diversity of data residing on the Web can be tamed using a holistic approach based on a distributed knowledge base. Our approach is to represent all Web information as logical facts, and Web data management tasks as logical rules. A variety of complex data management tasks that currently require intense work and deep expertise may then greatly benefit from the automatic reasoning provided by inference engines, operating over the distributed Web knowledge base: for instance, information access, access control, knowledge acquisition and dissemination. We propose to express the peers logic in Webdamlog, a datalog-style rule-based language. In Webdamlog, peers exchange facts (for information) and rules (in place of code). The use of declarative rules provides the following advantages. Peers may perform automatic reasoning using the available knowledge. Because the model is formally defined, it becomes possible to prove (or disprove) desirable properties. Because the model is based on a datalog-style language, query processing can benefit from optimization techniques. Because the model represents provenance and time, the quality of data can be better controlled. Because We thank all the researchers who participated in the Webdamlog project and in particular

An Autonomous Engine for Services Configuration and Deployment.

The runtime management of the infrastructure providing service-based systems is a complex task, up to the point where manual operation struggles to be cost effective. As the functionality is provided by a set of dynamically composed distributed services, in order to achieve a management objective multiple operations have to be applied over the distributed elements of the managed infrastructure. Moreover, the manager must cope with the highly heterogeneous characteristics and management interfaces of the runtime resources. With this in mind, this paper proposes to support the configuration and deployment of services with an automated closed control loop. The automation is enabled by the definition of a generic information model, which captures all the information relevant to the management of the services with the same abstractions, describing the runtime elements, service dependencies, and business objectives. On top of that, a technique based on satisfiability is described which automatically diagnoses the state of the managed environment and obtains the required changes for correcting it (e.g., installation, service binding, update, or configuration). The results from a set of case studies extracted from the banking domain are provided to validate the feasibility of this propos

Dynamic Model-based Management of Service-Oriented Infrastructure.

Models are an effective tool for systems and software design. They allow software architects to abstract from the non-relevant details. Those qualities are also useful for the technical management of networks, systems and software, such as those that compose service oriented architectures. Models can provide a set of well-defined abstractions over the distributed heterogeneous service infrastructure that enable its automated management. We propose to use the managed system as a source of dynamically generated runtime models, and decompose management processes into a composition of model transformations. We have created an autonomic service deployment and configuration architecture that obtains, analyzes, and transforms system models to apply the required actions, while being oblivious to the low-level details. An instrumentation layer automatically builds these models and interprets the planned management actions to the system. We illustrate these concepts with a distributed service update operation

Distributed First Order Logic

Distributed First Order Logic (DFOL) has been introduced more than ten years ago with the purpose of formalising distributed knowledge-based systems, where knowledge about heterogeneous domains is scattered into a set of interconnected modules. DFOL formalises the knowledge contained in each module by means of first-order theories, and the interconnections between modules by means of special inference rules called bridge rules. Despite their restricted form in the original DFOL formulation, bridge rules have influenced several works in the areas of heterogeneous knowledge integration, modular knowledge representation, and schema/ontology matching. This, in turn, has fostered extensions and modifications of the original DFOL that have never been systematically described and published. This paper tackles the lack of a comprehensive description of DFOL by providing a systematic account of a completely revised and extended version of the logic, together with a sound and complete axiomatisation of a general form of bridge rules based on Natural Deduction. The resulting DFOL framework is then proposed as a clear formal tool for the representation of and reasoning about distributed knowledge and bridge rules

General Model for Infrastructure Multi-channel Wireless LANs

In this paper we develop an integrated model for request mechanism and data transmission in multi-channel wireless local area networks. We calculated the performance parameters for single and multi-channel wireless networks when the channel is noisy. The proposed model is general it can be applied to different wireless networks such as IEEE802.11x, IEEE802.16, CDMA operated networks and Hiperlan\2.Comment: 11 Pages, IJCN