Cross - Layer Scheduling in Cloud Computing Systems
نویسنده
چکیده
Today, application schedulers are decoupled from routing level schedulers, leading to sub-optimal throughput for cloud computing platforms. In this thesis, we propose a cross-layer scheduling framework that bridges the application level scheduler with the routing level scheduler (SDN). We realize our framework in a batch-processing framework (Hadoop [1]) and a streamprocessing framework (Storm [2]). Our experimental results show that we are able to improve throughput of jobs in Storm and Hadoop by up to 32% and 29% respectively.
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تاریخ انتشار 2014