[PDF] Top 20 Network Traffic Separation and Aggregation in Mapreduce for Bigdata Applications

... data aggregation opportunities from multiple map ...the traffic by pushing aggregation from the edge into the ...the network topology with servers directly linked to other servers, which is of ... See full document

... on MapReduce performance improvement by optimizing its data transmission optimizing network usage can lead to better system performance and found that high network utilization and low network ... See full document

... optimizing network usage can lead to better system performance and found that high network utilization and low network congestion should be achieved simultaneously for a job with good ...a ... See full document

... a MapReduce job into several time slots with a length of several minutes or an ...and aggregation scheme may not be optimal. To reduce traffic cost, we may need to migrate an aggregator from machine ... See full document

... parallelism, MapReduce systems can exploit the large amount of computing power by huge scale ...of MapReduce systems, it is convenient to view a MapReduce job as consisting of three phases rather ... See full document

... large network traffic because it ignores network topology and data size associated with each ...the traffic-oblivious partition scheme, take into account of both task locations and data size ... See full document

... local network in the data ...increase traffic in many parts of the data center network. Big data traffic that is caused by big data transmission and big data processing disturbs data center ... See full document

... In general, Wireless sensor networks (WSNs) consist of thousands of sensor nodes (SN) that gather data from deployed environments. Environment monitoring, accident reporting and military investigation [1] are some ... See full document

... Grid applications, the results of which will guide the architectural choices in the design of ...Grid applications, their middleware environments, their traffic footprints, and most importantly their ... See full document

... Testbed Network Topology The two base station nodes are positioned such that they are overlapped at the edge, making it possible for the wireless nodes to handover from one base station to another while they are ... See full document

... are applications that handle datasets of sizes in the order of gigabytes (such as class D or E applications) and there are others which have the majority of the datasets in the order of a few kilobytes ... See full document

... the network. The Agent Monitor then navigate autonomously through the network from the server end and interact with the host operating system of the target workstations, and it's utility programs as it ... See full document

... from complex operating system functions increases synchronization/communication costs. This is especially serious in large scale parallel computing and leads to significant overheads in many MPI applications [13, ... See full document

... the network will eventually cease to be ...the network operates prior to becoming unusable as the network ...of network lifetime is not straightforward and may depend on the application ... See full document

... In these casesthe monitoring parameters should cut across all cloud layerson which application components are deployed in order togive a complete picture of the current application status.Typically application are ... See full document

... the MapReduce job ...for applications that generate large intermediate data in the shuffling stage, Twister [12] introduces local reduction across tasks on the same compute nodes before sending it to the ... See full document

... ABSTRACT: Recently MPLS is used for building up VPNs in IP backbone, called MPLS VPN. To provide people with voice, data and all categories of multimedia services, distinguishing between data flows is a requirement. To ... See full document

... • MapReduce is a programming model and implementation for processing and generating large data sets – Focus developer time/effort on salient unique, distinguished application requirement[r] ... See full document

... “MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate ... See full document

... to MapReduce algorithms for running them on Hadoop clusters by translating their data analytics logic to the MapReduce job which is to be run over Hadoop ...clusters. MapReduce is the processing ... See full document