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Distributed semantic search system (dsss)
This document describes a distributed semantic search system (DSSS) developed by a team of 4 students. The system allows users to search for and retrieve XML/RDF documents from a server. It follows a client-server architecture and aims to address issues like secure access management and billing. The system is designed to be highly available, reliable, concurrent, consistent, scalable and caching is allowed to improve performance. A three-tier architecture is used and the document describes the system's functional and non-functional requirements as well as its specializations, demo and server configuration.
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Distributed semantic search system (dsss)
- 1. Distributed Semantic Search System(DSSS) Distributed Computing Concepts for Artificial Intelligence
- 2. Team Members • • • • 01. A.M.Tharindu B. Adhikari 02. I.P.V. Vithana Pathirage 03. Nimesh Tharuka Kaluarachchi 04. Pahan Sri Madusanka Rodrigo MSCAI/12/04 MSCAI/12/09 MSCAI/12/10 MSCAI/12/15 Distributed Computing Concepts for Artificial Intelligence
- 3. Challenge (Identified problem) Todaythere is a large explosion of Cloud-based systems on internet. Representative is our Project, searching file, which enables users in cloud systems to search for and download files, documents, images, play lists, software and videos. One of the existing problems is how to manage secure access and bill the engaging parties. Distributed Computing Concepts for Artificial Intelligence
- 4. Distributed Computing Conceptsfor Artificial Intelligence
- 5. Program Description (1) FunctionalRequirements: • This system follows a client – server architecture. • Its server maintains a repository of XML/RDF documents. • Users through client, place a query and gets documents by their name. Distributed Computing Concepts for Artificial Intelligence
- 6. Program Description (2) NonFunctional Requirements: (2.1) High Availability: • This system provides failure transparency. • Designated client would monitor the server liveness. • This system assumes that all servers have access to a highly available file system at the back-end and do not replicate the repository. (2.2) Reliability: • Upon a server crash, the client would notify all pending requests about the failure. • Exception mechanism would be implemented to catch exceptional conditions. • Client failures would be detected by the server and would not block server resources. Distributed Computing Concepts for Artificial Intelligence
- 7. Program Description (2.3) Concurrencyand Consistency: • Synchronization would be designed to ensure the safety. • The users would not get mixed versions of documents. (2.4) Performance: • The system design would exploit multi threading in order to enhance response time and system throughput. (2.5) Caching and Coherency: • Client caching for documents would be allowed to improve retrieval performance. • Cache coherency mechanism would be employed. (2.6) Scalability: • Architecture would be scales up to large number of users and documents. Distributed Computing Concepts for Artificial Intelligence
- 8. Three-tier architecture Distributed ComputingConcepts for Artificial Intelligence
- 9. Specializations The DSS majoroffers 5 specializations, each at a different location. To meet the requirements for geographic mobility, the chosen exit point needs to differ from the chosen entry point. • Mobile Services • Cloud Operation • Cloud Infrastructures • Data Intensive Computing • Distributed Information Management Distributed Computing Concepts for Artificial Intelligence
- 10. Demo Distributed Computing Conceptsfor Artificial Intelligence
- 11. Server Configuration Distributed ComputingConcepts for Artificial Intelligence
- 12. Thank You ! DistributedComputing Concepts for Artificial Intelligence