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CATV Networks Bandwidth Allocation for the Upstream Channel

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Map Properties. The maps advertisement, must be continues with no unallocated time slots. ... Every user with best effort connection will get his requests while: BW. ... – PowerPoint PPT presentation

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Title: CATV Networks Bandwidth Allocation for the Upstream Channel


1
CATV Networks Bandwidth Allocation for the
Upstream Channel
Final presentation (winter 2001)
A project by Chen Yaniv 031763071 Lavi
Abramovich 032214363
Instructor Nir Menkerman
2
Project Definitions .
Learning and Understanding the DOCSIS/MCNS
standard for data over cable networks.

Developing an efficient scheduling algorithm for
the Cable Modem Termination System(CMTS).

Demonstrate the behavior of the algorithm with a
simulator implemented in Matlab.

3
Why Cable Network ?(Physical Layer)
Transparent IP Traffic, Through The
Data-Over-Cable System
- Economic
  • Broadband communication
    service.

- Widespread
- Integrate all communication services (Video,
Data)
4
Bandwidth Allocation MAC Layer
The upstream channel is modeled as a stream of
mini-slots.
The CMTS allocates the upstream slots by
broadcasting a map message to the CMs.
Mini slots
Previous map
current map
Yet unmapped time
5
Requests
  • The map includes allocation of the following
    types of upstream messages for the CMs (SIDs)
  • Unicast (data or request) supports piggyback
  • Multicast (requests)
  • Data/Request immediate access
  • contention resolution based on exponential back
    off .

6
Map Properties
7
CMTS Transportation Policy
QoS demands for Min/Max bandwidth, Timing

8
Best Effort
We focused on developing the algorithm for
supplying the regular users, the best bit rate
possible.
9
Solution The Algorithm
Parameters T simulation total time W window
time Delta - map size (mini slots) MinBW MaxBW Win
dowPriorities PendingVector RequestVector
10
Algorithm Improvements
  • Support concatenation.
  • Use map remains.
  • Best decision between modems with
  • the same priority.

11
Performance Evaluation
  • Compare with FIFO algorithm
  • Find 100 capacity a-posteriori.
  • Delay count.

12
Implementation IssueHow to Model the Cms ?
  • Does the modem's requests affected by the CMTS
    allocation policy?

2) What kind of random variables would best
represent the modems behavior ?
3) Can a modem support fragmentation ?
13
Our SolutionUse Buffers
FIFO Algorithm
GetRequestsBuff()
Fairness Algorithm
14
Simulation Results (1)
  • 200 modems.
  • All the modems are the same.
  • No concatenation support.
  • Simulation time 2000 sec
  • Window size 4 sec
  • Map size 60ms (2400 minislots)

15
Simulation Results (2)
  • 40 modems.
  • Linear increasing cms requests
  • No concatenation support.
  • Simulation time 2000 sec
  • Window size 4 sec
  • Map size 60ms (2400 minislots)

16
Simulation Results (3)
  • 200 modems.
  • Linear increasing cms requests
  • 100 supports concatenation.
  • Simulation time 2000 sec
  • Window size 4 sec
  • Map size 60ms (2400 minislots)

17
Simulation Results (4)
  • 40 modems.
  • Linear increasing cms requests
  • No concatenation support.
  • Simulation time 2000 sec
  • Window size 4 sec
  • Map size 60ms (2400 minislots)

18
Conclusions
  • Fairness was achieved!
  • Channel capacity usage is best when map size is
    much bigger then average request length.
  • Table statistics and all other algorithm
    improvements are most efficient when requests are
    small in compare to the map size.
  • Delay is minimized.

19
Future Suggested Improvements
  • Optimization of concatenation max size and
    W/delta ratio.
  • Add protocol overhead.
  • Support dynamic map size.
  • No need in table when all requests can be
    allocated without pending.
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