def getBitrateHarm(solo_bitrate_df, combi_bitrate_df):
    networks = ["Homelink", "3G"]
    ccas_video = ["reno", "cubic", "bbr", "none"]
    ccas_iperf = ["reno", "cubic", "bbr", "none"]

    for cca_video in ccas_video:
        for cca_iperf in ccas_iperf:
            for network in networks:
                # print(cca, cca_2, network)
                solo_bitrate = pick_solo_bitrate(solo_bitrate_df, cca_video,
                                                 network)
                combi_bitrate = pick_combi_bitrate(combi_bitrate_df, cca_video,
                                                   cca_iperf, network)
                if not combi_bitrate.empty:
                    harm, percentage = util.calculateHarm_more(
                        solo_bitrate.iloc[0], combi_bitrate.iloc[0])
                    # print(harm, percentage)
                    combi_cca = cca_iperf + "-" + cca_video
                    data = [[
                        combi_cca, harm, percentage, cca_iperf, cca_video,
                        network
                    ]]
                    new_df = pd.DataFrame(data)
                    new_df.to_csv(ex.DATAPATH_PROCESSED +
                                  '/harm/bitrate_harm_video.csv',
                                  header=False,
                                  index=False,
                                  mode='a')
Beispiel #2
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def getHarm2(solo_iperf_goodput_df, combi_iperf_goodput_df):
    networks = ["Homelink", "3G"]
    ccas = ["reno", "cubic", "bbr"]
    ccas_2 = ["reno", "cubic", "bbr", "none"]

    for cca in ccas:
        for cca_2 in ccas_2:
            for network in networks:
                # print(cca, cca_2, network)
                solo_iperf_goodput = get_iperf_solo_goodput(
                    solo_iperf_goodput_df, cca, network)
                combi_iperf_goodput = get_iperf_combi_2_goodput(
                    combi_iperf_goodput_df, cca, cca_2, network, 5202)
                if not combi_iperf_goodput.empty:
                    harm, percentage = util.calculateHarm_more(
                        solo_iperf_goodput.iloc[0],
                        combi_iperf_goodput.iloc[0])
                    combi_cca = cca + "-" + cca_2
                    data = [[combi_cca, harm, percentage, cca, cca_2, network]]
                    new_df = pd.DataFrame(data)
                    new_df.to_csv(ex.DATAPATH_PROCESSED +
                                  '/harm/goodput_harm_iperf_youtube.csv',
                                  header=False,
                                  index=False,
                                  mode='a')
Beispiel #3
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def iperf_iperf_harm(solo_iperf_goodput_df, combi_iperf_goodput_df):
    networks = ["Homelink", "3G"]
    ccas = ["reno", "cubic", "bbr"]
    ccas_2 = ["reno", "cubic", "bbr"]
    for cca in ccas:
        for cca_2 in ccas_2:
            for network in networks:
                solo_iperf_goodput = get_iperf_solo_goodput(
                    solo_iperf_goodput_df, cca, network)
                combi_iperf1_gp = get_iperf_combi_goodput(
                    combi_iperf_goodput_df, cca, cca_2, network, 5202)
                combi_iperf2_gp = get_iperf_combi_goodput(
                    combi_iperf_goodput_df, cca, cca_2, network, 5203)
                if not combi_iperf1_gp.empty and not combi_iperf2_gp.empty:
                    logval = cca + "-" + cca_2 + "-" + network + "-" + str(
                        solo_iperf_goodput.iloc[0]) + "-" + str(
                            combi_iperf1_gp.iloc[0]) + "-" + str(
                                combi_iperf2_gp.iloc[0])
                    print(logval)
                    iperf1_harm, iperf1_perc = util.calculateHarm_more(
                        solo_iperf_goodput.iloc[0], combi_iperf1_gp.iloc[0])
                    iperf2_harm, iperf2_perc = util.calculateHarm_more(
                        solo_iperf_goodput.iloc[0], combi_iperf2_gp.iloc[0])
                    gp_jfi = calculate_jfi(combi_iperf1_gp.iloc[0],
                                           combi_iperf2_gp.iloc[0])
                    harm_jfi = calculate_jfi(iperf1_harm, iperf2_harm)
                    gp_1_jfi = 1 - gp_jfi
                    harm_1_jfi = 1 - harm_jfi
                    combi_cca = cca + "-" + cca_2
                    data = [[
                        combi_cca, iperf1_harm, iperf1_perc, iperf2_harm,
                        iperf2_perc, cca, cca_2, network, gp_jfi, harm_jfi,
                        gp_1_jfi, harm_1_jfi
                    ]]
                    new_df = pd.DataFrame(data)
                    new_df.to_csv(ex.DATAPATH_PROCESSED +
                                  '/harm/goodput-harm-iperf-iperf.csv',
                                  header=False,
                                  index=False,
                                  mode='a')
def getBitrateHarm(solo_bitrate_df, combi_bitrate_df):
    networks = ["Homelink", "3G"]
    ccas = ["reno", "cubic", "bbr"]

    for cca in ccas: 
        for network in networks:
            solo_bitrate = pick_solo_bitrate(solo_bitrate_df, cca, network)
            combi_bitrate = pick_combi_bitrate(combi_bitrate_df, cca, network)
            harm, percentage = util.calculateHarm_more(solo_bitrate.iloc[0], combi_bitrate.iloc[0])
            print(harm, percentage)
            data = [[harm, percentage, cca, network]]
            new_df = pd.DataFrame(data)
            new_df.to_csv(ex.DATAPATH_PROCESSED +'/harm/bitrate_harm_localvideo.csv', header=False, index=False, mode = 'a')
def getBitrateHarm2(solo_bitrate_df, combi_bitrate_df):
    networks = ["Homelink", "3G"]
    ccas = ["reno", "cubic", "bbr"]
    ccas_2 = ["reno", "cubic", "bbr"]

    for cca in ccas: 
        for cca_2 in ccas_2:
            for network in networks:
                # print(cca, cca_2, network)
                solo_bitrate = pick_solo_bitrate(solo_bitrate_df, cca, network)
                combi_bitrate = pick_combi_2_bitrate(combi_bitrate_df, cca, cca_2, network, 5203)
                if not combi_bitrate.empty:
                    harm, percentage = util.calculateHarm_more(solo_bitrate.iloc[0], combi_bitrate.iloc[0])
                    print(harm, percentage)
                    combi_cca = cca + "-" + cca_2
                    data = [[combi_cca, harm, percentage, cca, cca_2, network]]
                    new_df = pd.DataFrame(data)
                    new_df.to_csv(ex.DATAPATH_PROCESSED +'/harm/bitrate_harm_localvideo.csv', header=False, index=False, mode = 'a')
Beispiel #6
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def getHarm(solo_iperf_goodput_df, combi_iperf_goodput_df):
    networks = ["Homelink", "3G"]
    ccas = ["reno", "cubic", "bbr"]

    for cca in ccas:
        for network in networks:
            solo_iperf_goodput = get_iperf_solo_goodput(
                solo_iperf_goodput_df, cca, network)
            combi_iperf_goodput = get_iperf_combi_goodput(
                combi_iperf_goodput_df, cca, network, 5202)
            # print(combi_iperf_goodput)
            # print (solo_iperf_goodput.iloc[0])
            harm, percentage = util.calculateHarm_more(
                solo_iperf_goodput.iloc[0], combi_iperf_goodput.iloc[0])
            # print(harm, percentage)
            data = [[harm, percentage, cca, network]]
            new_df = pd.DataFrame(data)
            new_df.to_csv(ex.DATAPATH_PROCESSED +
                          '/harm/goodput_harm_iperf_localvideo.csv',
                          header=False,
                          index=False,
                          mode='a')