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  1. Clone the GitHub repository from: https://github.com/AlexLup06/BA_Code

Download INET-4.5.2 and OMNeT++.6.0.2 from the official websites to the root directory and follow their installation guides. Then run $ source setenv in the root directory. After that move to ./CDNsimulator and run: $ make MODE=release all In ./CDNsimulator/simulations/omnetpp.ini change "resultdir" to the path of the root.

  1. Start simulations by moving to ./CDNsimulator/simulations/ and run the com- mand: $ ../out/clang-release/src/CDNsimulator -f omnetpp.ini -c NumSugg<NUM_SURROGATES> -r ’$numNet=<NUM_NET> && $cp= && $reqId=’ -m -u Cmdenv - n.:../src:../../inet4.5 examples:../../inet4.5/showcases:../../inet4.5/src:../../inet4.5/tests/validation:../../inet4.5/tests/networks:../../inet4.5/tutorials--image-path=../../inet4.5/images -l ../../inet4.5/src/INET

• <NUM_SURROGATES>:= number of surrogates (5,10,15) • <NUM_NET>:= network ID (0,...,7) • := cache-miss policy ((0,Closest Surrogate),(1,Random Surrogate),(2,Load Balance),(3,Closest Origin)) • := request trace file ID (0,...7)

  1. Evaluating Data: First, we need to extract the data. For that run: $ ./exportData.sh <NAME_DIR_TO_SAVE> <NUMBER_SURROGATES> <CACHE_POLICY>

However, ./data/ already has sorted and calculated data. All tools to plot data can be found in the directory ./python/plot_data/. Please use that data. The functions used to format the raw data and calculate the needed values are specifically written for the results that were used in this thesis. If you have the expertise you can change the source code of the Python scripts to accommodate your needs. To plot data you nee to run the python script with: python3 <PATH_TO_FILE> <NUM_SURROGATES> <NAME_DATA_DIR> <CONFIDENCE_LEVEL> • <PATH_TO_FILE>:= path to file you want to run • <NUM_SURROGATES>:= number of surrogates in the network (5,10,15) IM- PORTANT: Leave this out if you want to show a graph or cdf • <NAME_DATA_DIR>:= name of data files (base or final_flash • <CONFIDENCE_LEVEL>:= confidence level. Only specify if you plot confidence interval

The raw data from which the results in chapter five derive have been uploaded to cloud storage: https://tu-dortmund.sciebo.de/s/YJOnFi4jtr31FAX

If questions arise fell free to email me: [email protected]

  1. Generating Network In the python folder is a directory called configure_network. Here are scripts to translate the BRITE generated network into a format that omnet++ understands. To generate networks follow the installation guide from BRITE and use ./Brite_Config.conf as the config file. The seeds for the networks used in our simulations can be found in ./Networks/ This folder also includes the generated networks from those seeds. To translate the network files into omnet++ readable files use ./python/NetworkConfiguration.py This generates the network, request trace files, assigns each client a surrogate server and calculates the closest surrogate server for each surrogate servers.

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