By Xian-he Sun, Wenyu Qu, Ivan Stojmenovic, Wanlei Zhou, Zhiyang Li, Hua Guo, Geyong Min, Tingting Yang, Yulei Wu, Lei Liu (eds.)
This quantity set LNCS 8630 and 8631 constitutes the lawsuits of the 14th overseas convention on Algorithms and Architectures for Parallel Processing, ICA3PP 2014, held in Dalian, China, in August 2014. The 70 revised papers offered within the volumes have been chosen from 285 submissions. the 1st quantity contains chosen papers of the most convention and papers of the first foreign Workshop on rising subject matters in instant and cellular Computing, ETWMC 2014, the fifth overseas Workshop on clever verbal exchange Networks, IntelNet 2014, and the fifth overseas Workshop on instant Networks and Multimedia, WNM 2014. the second one quantity includes chosen papers of the most convention and papers of the Workshop on Computing, verbal exchange and keep an eye on applied sciences in clever Transportation method, 3C in ITS 2014, and the Workshop on safeguard and privateness in computing device and community platforms, SPCNS 2014.
Read or Download Algorithms and Architectures for Parallel Processing: 14th International Conference, ICA3PP 2014, Dalian, China, August 24-27, 2014. Proceedings, Part II PDF
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Additional resources for Algorithms and Architectures for Parallel Processing: 14th International Conference, ICA3PP 2014, Dalian, China, August 24-27, 2014. Proceedings, Part II
Commun. ACM 51(1), 107–113 (2008) 5. : Bitdew: A data management and distribution service with multi-protocol ﬁle transfer and metadata abstraction. J. Network and Computer Applications 32(5), 961–975 (2009) 6. : Adapt: Availability-aware mapreduce data placement for non-dedicated distributed computing. In: ICDCS, pp. 516–525. IEEE (2012) 7. : Mapreduce on opportunistic resources leveraging resource availability. In: CloudCom, pp. 435–442 (2012) 8. : Reliable mapreduce computing on opportunistic resources.
For Distributed Grep application, the Reduce stage is very simple, and it just collects and sums up the intermediate results. As you can see from these two ﬁgures, as the increase of input text ﬁle size, job completion time also increases. From these two ﬁgures, we can see that there is also only little performance diﬀerence between HybridDFS and HDFS. 4 Scheduler Optimization In this scenario, experiments on WordCount application and Distributed Grep application have also been performed to testify the eﬃciency of the node prioritybased fair scheduling (NPBFS) algorithm.
Springer, Heidelberg (2009) 11. : Fast Clustering Using MapReduce. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 684–689 (2011) 12. : Clustering Very Large Multi-dimensional Datasets with MapReduce. In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 690–698 (2011) 13. : HaLoop: Eﬃcient Iterative Data Processing on Large Clusters. VLDB Endow 3(1-2), 285–296 (2010) 14. : Twister: A Runtime for Iterative MapReduce.
Algorithms and Architectures for Parallel Processing: 14th International Conference, ICA3PP 2014, Dalian, China, August 24-27, 2014. Proceedings, Part II by Xian-he Sun, Wenyu Qu, Ivan Stojmenovic, Wanlei Zhou, Zhiyang Li, Hua Guo, Geyong Min, Tingting Yang, Yulei Wu, Lei Liu (eds.)