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The model has been verified and validated by implementing a distributed image-rendering algorithm over a simulated mobile cluster model.
Figure 6 Network utilization of Hadoop mobile cluster running 1 GB TeraSort workload.
This section examines the performance of Hadoop distributed processing in practical mobile cluster setups.
Hence, configuration parameters for the mobile cluster should be carefully determined by taking into account various other performance aspects.
This assumption is needed for this study to evaluate the distributed processing capability of the mobile cluster under reliable connectivity.
Consequently, the performance of mobile distributed computing may be strongly influenced by the characteristics of wireless links in the mobile cluster.
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This has made parallel computing feasible on mobile clusters, by making use of the idle processing power of the static and mobile nodes that form the cluster.
Section "Performance analysis of Hadoop mobile clusters" provides our experimental observations on the performance of Hadoop mobile clusters with details of the experimental setup and Section "Performance issues of mobile cloud clusters" discusses performance issues of mobile distributed analytics.
Before analyzing the performance of Hadoop mobile clusters, stress tests are performed on the mobile node, Google NEXUS 7, to identify the maximum operating capability of hardware resources (e.g. CPU, memory, file system, network, etc).
On the other hand, this study identifies distinct problems in conducting Hadoop distributed analytics on the mobile clusters, which come in the form of longer job completion time or frequent task failure from task response timeout and node disconnection.
Therefore, it is critical to mitigate the effect of the timeout occurrences in the Hadoop mobile clusters where the chance of particular node failures and communication problems is comparatively high.
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