Titlebook: Intelligent Distributed Computing VII; Proceedings of the 7 Filip Zavoral,Jason J. Jung,Costin Badica Conference proceedings 2014 Springer

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Integration Computing and Collective Intelligence, In general, an integration task most often refers to a set of elements (objects) with the same kind of structures, the aim of which is based on determining an element best representing the given. The kinds of structures mean for example relational, hierarchical, table etc.

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Evolution of a Relational Schema and Its Impact on SQL Queries,nt task. In this paper we study its specific part – evolution of a relational database schema and its impact on related SQL queries. The proposed approach shows an ability to model database queries together with a database schema. The feature then provides a solution how to adapt database queries re

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Semantically Partitioned Peer to Peer Complex Event Processing,ical scaling, or stratification of an Event Processing Network. The solutions usually aren’t distributed and require centralized coordination. In this paper, we are introducing a technique for scaling Complex Event Processing in a distributed fashion and by taking semantic information of events into

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A Heuristic to Explore Trust Networks Dynamics,nce, scalability, and reduction of costs. A significant drawback though is the potential lack in security and trust, due to a huge number of different, dispersed devices. In such a context, trust-based networks allow to rank nodes (e.g. devices) so that only the . are chosen to store and manipulate

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Resource Scaling Performance for Cache Intensive Algorithms in Windows Azure,gh the cloud service provider offers the specified infrastructure. The real expectation is limited due to memory access type, how data fits in available cache, nature of programs (if they are computation-intensive, memory or cache demanding and intensive) etc. Cloud infrastructure in addition rises

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