Details

    • Epic
    • Status: Resolved (View Workflow)
    • Major
    • Resolution: Fixed
    • None
    • 2.0.1
    • Situation Detection Engine: DBSCAN + Hellinger Distance
    • ALEC20220413_Iteration_1, ALEC20220518_Iteration_6, ALEC20220525_Iteration_7, ALEC20220608_Iteration_8, ALEC20220622_Iteration_9, ALEC20220706_Iteration_10, ALEC20220720_Iteration_11

    Description

      One of the main issues we have with the way we are currently trying to group alarms into situations is the usage of timestamps.

      Both our engines (DBSCAN and Deep Learning), use the offset between the ending time the two alarms is trying to associate. This doesn't take into account the alarm duration.

      By using Hellinger Distance we attempt to fit these start and end timestamps of alarms into a distribution which would allow us to calculate a more robust distance. Hellinger Distance between alarms would be a measure between 0 (identical alarms in terms of time) and 1 (alarms have no time overlap).

      Our hypothesis is that this measure can improve the situation generation process for either engine.

      Goals:

      • Learn how to calculate Hellinger distance. (ALEC-102)
      • Implement Hellinger distance for machine learning engines:
        • Clustering (DBSCAN) (ALEC-122).
        • Deep Learning (ALEC-XXX).
      • Assess if Hellinger Distance has a positive impact in ALEC: (ALEC-107 and ALEC-XXX)

      Target:

      • Network Operator / Administrator, looking at our alarm dashboard.

      If we can provide better accuracy, we will let the Network Operator / Administrator be more efficient at reducing the Mean Time to Repair (by having a more focused approach).

      Attachments

        Issue Links

          Activity

            People

              gmantecon Gerardo Mantecon
              joseanes Jose
              Votes:
              0 Vote for this issue
              Watchers:
              1 Start watching this issue

              Dates

                Created:
                Updated:
                Resolved:

                Time Tracking

                  Estimated:
                  Original Estimate - 1 day, 2 hours
                  1d 2h
                  Remaining:
                  Remaining Estimate - 1 day, 2 hours
                  1d 2h
                  Logged:
                  Time Spent - Not Specified
                  Not Specified