By Dan Suciu (auth.), Georg Gottlob, Giovanni Grasso, Dan Olteanu, Christian Schallhart (eds.)
This publication constitutes the completely refereed post-conference lawsuits of the twenty ninth British nationwide convention on Databases, BNCOD 2013, held in Oxford, united kingdom, in July 2013. The 20 revised complete papers, provided including 3 keynote talks, tutorials, and one panel consultation, have been conscientiously reviewed and chosen from forty two submissions. designated concentration of the convention has been "Big facts" and so the papers disguise quite a lot of issues reminiscent of question and replace processing; relational garage; benchmarking; XML question processing; immense info; spatial info and indexing; facts extraction and social networks.
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Additional info for Big Data: 29th British National Conference on Databases, BNCOD 2013, Oxford, UK, July 8-10, 2013. Proceedings
1 in Figure 6(b) attempts to repair the RT with the least amount of reprogramming. This is done by ﬁrst locating sections of the RT where the failed node and any unpinned nodes (initially an empty set) communicate with each other. Each of these sections is repaired independently. , node 1. Each section then gives rise to a Steiner tree problem where the inputs of the leaf nodes of the section (node 2 and 8) and the parent of the root node of the section (node 0) become mandatory nodes (represented as double circled nodes in Figure 7).
3(a) for our example query. Each vertex is a sensor node; an edge denotes that the two nodes can communicate; the arrow denotes the direction of communication; double-line circles denote the sink or else nodes that do sensing; single-line nodes do processing or communication or both. Recall that a Steiner tree is a minimum spanning tree (and hence likely to be energy-eﬃcient) that necessarily includes a given set of nodes. , the base station). Step 5 in Fig. 2 decides which fragment instances to place for execution in which node.
4. 5. 6. 7. 8. 9. 10. 11. 12. : Survey of graph database models. ACM Comput. Surv. : Survey of graph database performance on ¨ the HPC scalable graph analysis benchmark. , Shao, J. ) WAIM 2010. LNCS, vol. 6185, pp. 37–48. : Mining billion-scale graphs: Patterns and algorithms. In: SIGMOD 2012, pp. : Optimizing regular path expressions using graph schemas. In: ICDE 1998, pp. : Eﬃcient RDFS entailment in external memory. , Herrero, P. ) OTM-WS 2011. LNCS, vol. 7046, pp. 464–473. Springer, Heidelberg (2011) 32 A.
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