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23 lines
1.4 KiB
23 lines
1.4 KiB
1. Objective:
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We want to forecast the peak and off-peak times of internet usage given a few full cycles of internet traffic history.
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2. License: Free to use but requires citation of the following paper: P. Cortez, M. Rio, M. Rocha and P. Sousa. Multiscale Internet Traffic Forecasting using Neural Networks and Time Series Methods. In Expert Systems, Wiley-Blackwell, In press.
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3. Data Source: https://datamarket.com/data/set/232n/internet-traffic-data-in-bits-from-a-private-isp-with-centres-in-11-european-cities-the-data-corresponds-to-a-transatlantic-link-and-was-collected-from-0657-hours-on-7-june-to-1117-hours-on-31-july-2005-data-collected-at-five-minute-intervals#!ds=232n&display=line
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4. Data Set Information:
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Internet traffic data (in bits) from a private ISP with centers in 11 European cities. The data corresponds to a transatlantic link and was collected from 06:57 hours on 7 June to 11:17 hours on 31 July 2005. Data collected at five minute intervals.
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5. Field Meanings:
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A. _time: UNIX epoch time (local time)
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B. bits_transferred: Data transferred in bits and collected at five-minute intervals, aggregated in 120-minute bin size.
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6. Parameter Selection:
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A. Dashboard: Forecast Time Series
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Settings:
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1) Search command: | inputlookup internet_traffic.csv | timechart span=120min avg("bits_transferred") as traffic | eval traffic=round(traffic)
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2) Field to predict: traffic
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1) Method: LLP
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2) Withhold: 112
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3) Forecast: 112
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