By Beng Chin Ooi (auth.), Robert Meersman, Tharam Dillon, Pilar Herrero (eds.)

ISBN-10: 364216949X

ISBN-13: 9783642169496

The two-volume set of LNCS 6426/6427 constitutes the refereed lawsuits of three confederated overseas meetings on CoopIS (Cooperative details Systems), DOA (Distributed items and purposes) and ODBASE (Ontologies, DataBases and purposes of SEmantics). those meetings have been held in October 2009 in Greece, in Hersonissos at the island of Crete. CoopIS is protecting the purposes of applied sciences in an enterprice context as workflow platforms and data administration. DOA is masking the suitable infrastructure-enabling applied sciences and at last, OSBASe is overlaying internet semantics, XML databases and ontologies. The eighty three revised complete papers provided including three keynote talks have been rigorously reviewed and chosen from a complete of 223 submissions. resembling the OTM major meetings the papers are prepared in topical sections on strategy types and administration, modeling of cooperation, providers computing, info processing and administration, human-based cooperative structures, ontology and workflow demanding situations, entry keep watch over, authentication and guidelines, safe architectures, cryptography, information garage and processing, transaction and occasion administration, virtualization functionality, threat and scalability, cloud and disbursed approach protection, reactivity and semantic info, ontology mapping and semantic similarity, area particular ontologies.

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In: Proc. Thirteenth International Database Engineering & Applications Symposium (IDEAS 2009) (2009) 6. : Extend UDF Technology for Integrated Analytics. In: Proc. DaWaK 2009 (2009) 7. : Experiences with MapReduce, an abstraction for large-scale computation. In: Int. Conf. on Parallel Architecture and Compilation Techniques. ACM, New York (2006) 8. : Clustera: An Integrated Computation And Data Management System. In: VLDB 2008 (2008) 9. : Continuous Analytics: Rethinking Query Processing in a NetworkEffect World.

Despite having different architectures, all of the presented tuple stores share common components like request routing and storage and use common dependable and distributed systems techniques such as partition and replication. Figure 6, shows the architecture of each system and highlights which layer is responsible for each component. In the following, we focus on those components highlighting the similarities and differences on how each component is realized in each data store. The characterization of the architecture is directly related to the way each system realizes data partitioning, an aspect of major importance.

Conceptually we refer to the above meta-data manipulation as “changing labels” that is extremely efficient compared with data moving/copying. For example, assume that the cloud service exposes to the clients with table named “current_road_condition”, but actually stores the CSA results in the tables internally identified by T1, T2, …, T9, for the traffic status of the current hour h and h-1,…, h-7, h-8. When a client connects to the cloud service and requests the current-hour traffic status using a SQL API for access the table “current_road_condition”, a cloud service provided query rewriter will change the table name from “current_road_condition” to, say T9, should the analytics results of the current hour is stored in T9.

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On the Move to Meaningful Internet Systems, OTM 2010: Confederated International Conferences: CoopIS, IS, DOA and ODBASE, Hersonissos, Crete, Greece, October 25-29, 2010, Proceedings, Part II by Beng Chin Ooi (auth.), Robert Meersman, Tharam Dillon, Pilar Herrero (eds.)


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