Download Algorithms and Architectures for Parallel Processing: 14th by Xian-he Sun, Wenyu Qu, Ivan Stojmenovic, Wanlei Zhou, PDF

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 overseas Workshop on rising themes in instant and cellular Computing, ETWMC 2014, the fifth overseas Workshop on clever conversation Networks, IntelNet 2014, and the fifth foreign Workshop on instant Networks and Multimedia, WNM 2014. the second one quantity contains chosen papers of the most convention and papers of the Workshop on Computing, communique and regulate applied sciences in clever Transportation procedure, 3C in ITS 2014, and the Workshop on defense and privateness in computing device and community structures, SPCNS 2014.

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Extra resources for Algorithms and Architectures for Parallel Processing: 14th International Conference, ICA3PP 2014, Dalian, China, August 24-27, 2014. Proceedings, Part II

Example text

MapReduce process can be simply described by the following equations: Data = di (3) M ap(di ) (4) i=1:n M ap(Data) = i=1:n IRji M ap(di ) = (5) j=1:r IRji ) = Outputj Reduce( (6) i=1:n In designing the runtime of HybridMR, the general fast/slow nodes detection and fast/slow tasks detection approaches are not fit for this hybrid heterogenous environment, because CPU speed of cluster nodes are always faster than desktop PCs. In existing MapReduce computing models for desktop grid environment, such as BitDew-MapReduce [12], the FIFO scheduling policy is usually employed when processing “heartbeat” report, that the data chunks are assigned in the order that “heartbeat” arrived, without other biases or preferences.

J. Internet Services and Applications 4(1), 1–17 (2013) 4. : Mapreduce: Simplified data processing on large clusters. 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 existing MapReduce computing models for desktop grid environment, such as BitDew-MapReduce [12], the FIFO scheduling policy is usually employed when processing “heartbeat” report, that the data chunks are assigned in the order that “heartbeat” arrived, without other biases or preferences. In HybridMR implementation, we developed a new node priority-based fair scheduling (NPBFS) algorithm. In the hybrid heterogenous environment, hardware configurations of WorkerNodes or DataNodes are diverse, which proposes an urgent need of a fair algorithm that the node with stronger computing capability should process more jobs.

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