lectures.alex.balgavy.eu

Lecture notes from university.
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network-monitoring.md (1505B)


      1 +++
      2 title = 'Network monitoring'
      3 +++
      4 
      5 ## Network monitoring
      6 Tasks:
      7 - which path id my packet take?
      8 - which rules on the switch did the packet follow?
      9 - how long did the packet queue at each switch?
     10 - who did the packet share the queue with?
     11 
     12 In-band network telemetry: leverage programmability of switches to insert monitoring info into packet header along network path
     13 
     14 Heavy hitters: network flows that are larger (in number of packets, or bytes) than some fraction *t* of total packets seen on the link or some top *k* flows by size
     15 
     16 Space-saving algorithm: counter-based algorithm that uses O(k) counters to track k heavy flows
     17 - properties:
     18   - no flow counter in the table is ever underestimated
     19   - min value in the table (`val_r`) is an upper bound on the overestimation error of any counter
     20   - any flow with true count higher than average table count will always be present in the table
     21 - if flow has appeared in table: hash to flow key, increment corresponding counter
     22 - if flow not contained in table: find the min counter in the table, replace the key with the current flow key, increment the counter
     23 
     24 Universal streaming:
     25 - there exists universal approach to estimate G-sum when function `g(*)` is non-decreasing such that g(0) = 0 and g(x) does not monotonically grow faster than x²
     26 - universal sketch construction can be used to estimate G-sum with high probability using poly-logarithmic memory
     27 
     28 Item i is a g-heavy hitter if changing its frequency `f_i` significantly affects its G-sum