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NeXtworking

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NeXtworking'03 June 23-25,2003, Chania, Crete, Greece ... QoS tends to mean 'hard' qos (Intserv-like) ... why are we insisting on modelling TCP and RED ... – PowerPoint PPT presentation

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Title: NeXtworking


1
Traffic modelling and traffic control ...
  • ... are necessary for QoS (or qos) and this is
    still an issue
  • (over)provisioning...
  • ... and controlled sharing
  • QoS tends to mean "hard" qos (Intserv-like)
  • for an announced connection a priori traffic
    descriptor, admission control, scheduling and/or
    traffic conditioning
  • statistical network calculus is the state of the
    art in realizing hard QoS guarantees (delay lt d,
    negligible loss)
  • Diffserv is softer qos
  • aggregate descriptors, conditioning and per hop
    behaviours
  • but how can we meet the SLA's?
  • some believe even softer qos is sufficient (and
    necessary?)
  • a self-managed Internet...
  • ... or a network with implicit admission control
    and implicit differentiation
  • we also need modelling to understand best effort
    control!
  • eg, TCP modelling and re-design

2
Answering the questions
  • is standard queueing theory enough?
  • frequently model at the appropriate granularity,
    seek insensitivities
  • is first course control theory enough?
  • significant advances cf. work on stability of
    TCP
  • how can we understand time-scale interactions and
    design for them?
  • time scale separation is key to successful
    modelling
  • but beware of drawing conclusions without regard
    to all time scales
  • are time varying averages enough, or do we need
    to capture higher moments?
  • insensitivity results suggest time averages are
    often sufficient
  • stationarity is a key assumption is this valid
    with LRD traffic?

3
Answering the questions
  • what happens to "effective" bandwidth and good
    old Erlang?
  • effective bandwidth is useful for sizing
  • Erlang is still insensitive ... to criticism!
  • why are we insisting on modelling TCP and RED
  • evolution to higher rates, ensure stability,
    improve fairness? improve efficiency?
  • why did it take us some time to be more careful?
  • self-similarity vs pseudo ss, limit cycle vs
    instability, etc
  • who was not careful? who is now more careful?
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