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  • 1.
    Kroll, Lars
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Ormenisan, Alexandru-Adrian
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Dowling, Jim
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Fast and Flexible Networking for Message-Oriented Middleware2017In: Proceedings - International Conference on Distributed Computing Systems, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1453-1464, article id 7980084Conference paper (Refereed)
    Abstract [en]

    Distributed applications deployed in multi-datacenter environments need to deal with network connections of varying quality, including high bandwidth and low latency within a datacenter and, more recently, high bandwidth and high latency between datacentres. In principle, for a given network connection, each message should be sent over the best available network protocol, but existing middlewares do not provide this functionality. In this paper, we present KompicsMessaging, a messaging middleware that allows for fine-grained control of the network protocol used on a per-message basis. Rather than always requiring application developers to specify the appropriate protocol for each message, we also provide an online reinforcement learner that optimises the selection of the network protocol for the current network environment. In experiments, we show how connection properties, such as the varying round-trip time, influence the performance of the application and we show how throughput and latency can be improved by picking the right protocol at the right time.

  • 2.
    Ormenisan, Alexandru-Adrian
    et al.
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Downling, Jim
    KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
    Dela-Sharing Large Datasets between Hadoop Clusters2017In: Proceedings - International Conference on Distributed Computing Systems, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 2533-2536, article id 7980225Conference paper (Refereed)
    Abstract [en]

    Big data has, in recent years, revolutionised an evergrowing number of fields, from machine learning to climate science to genomics. The current state-of-the-art for storing large datasets is either object stores or distributed filesystems, with Hadoop being the dominant open-source platform for managing 'Big Data'. Existing large-scale storage platforms, however, lack support for the efficient sharing of large datasets over the Internet. Those systems that are widely used for the dissemination of large files, like BitTorrent, need to be adapted to handle challenges such as network links with both high latency and high bandwidth, and scalable storage backends that are optimised for streaming and not random access. In this paper, we introduce Dela, a peer-to-peer data-sharing service integrated into the Hops Hadoop platform that provides an end-to-end solution for dataset sharing. Dela is designed for large-scale storage backends and data transfers that are both non-intrusive to existing TCP network traffic and provide higher network throughput than TCP on high latency, high bandwidth network links, such as transatlantic network links. Dela provides a pluggable storage layer, implementing two alternative ways for clients to access shared data: stream processing of data as it arrives with Kafka, and traditional offline access to data using the Hadoop Distributed Filesystem. Dela is the first step for the Hadoop platform towards creating an open dataset ecosystem that supports user-friendly publishing, searching, and downloading of large datasets.

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