1 Traffic Shaping and BW Allocation Papalexidis Nikos 30/3/2001

2 Traffic Shaping-Motivation  Prevent probable exceed of the Qos contract negotiated at the admission control (due to burstiness)  Reduce the bandwidth requirements for the shaped streams

3 Traffic Shapers  Shapes the traffic so that a source may not violate the traffic envelope negotiated  If the traffic generated by the source does not conform to the traffic envelope enforced,the shaper can  Drop the violating cells  Tag them as a lower priority traffic  Hold them in a reshaping buffer

4 Desirable Properties  The traffic envelope it enforces on a source should be easy to describe  Simple to implement  Able to capture a wide range of traffic characteristics

5 Traffic Shapers-Schemes  Leaky Bucket  Window shapers  Jumping window  Moving window  Composite Shapers  Composite Leaky Bucket  Dual LB  Triple LB  Composite windows

6 Leaky Bucket Data buffer Peak rate λ p Average rate λ a Token buffer λ t token rate d b

7 Leaky Bucket  Simple to implement  The size of the bucket imposes an upper bound on the burst length  The tolerance against a long burst depends on the size of the bucket and the leaky rate  Worst case:A burst at t=0 equal to the bucket size followed by bit rate equal to the rate of the token generation

8 Leaky Bucket  Peak rate easy to police  Average rate not so easy (Cells arrive at peak rate during bursts)  Leaky rate > Mean bit rate for stability and achieving the required QoS

9 Leaky Bucket Actual bit rate=Y x Negotiated mean bit rate

10 Leaky Bucket Mean bit rate entering the network(leaky rate)=E x Negotiated mean bit rate

11 Leaky Bucket  The larger the LB size the better the control but the reaction time also increases.That is the time between the increase in average bit rate and its detection becomes large.LB size decreases as the leak rate increases for the same Qos.This provides a fast reaction to big jumps in the mean rate.  Trade off between LB size and the leaky rate  Ideal behavior as M increases and l decreases.  Low M and high l (near peak) provides almost no control

12 Leaky Bucket  LB often introduces excessive access delays thereby making it incapable of regulating real-time traffic  A policy which is less stringent on short-term burstiness while bounding long-term behavior with a LB-bound would be better suited for time critical traffic  Alternative  Allow the violating cells to enter the network with low priority and discard them at the congested nodes (increase of the utilization/probable congestion)

13 Different LB types  One LB is not effective for policing both peak and mean rate.Dual LB is proposed  First LB should control the peak rate.  Leaky rate set to the peak rate  Cell which do not confirm are simply dropped  Second LB controls the mean rate  As stated there is a trade-off between high reaction time and high sensitivity in detection of violating cells.If both are required a mechanism consisting of a LB to control the peak connected in series with two LB in parallel to control the mean bit rate is the ideal solution.(Triple LB).Cell that passed the 1 st LB is discarded whenever one of the parallel buckets (controlling the mean rate) overflows.

14 Triple LB

15 Time window shapers  Jumping window: Divides the time into fixed-size windows of length w and limits the number of cells accepted within a window to a maximum number m Worst case: Burst length of 2m  Moving window: Similar restrictions but the window can slide on the time axis Worst case: Burst length of m Traffic generated is smoother More complexity in implementation

16 Composite window shapers Composite jumping window  Time windows are encapsulated Composite moving window  Extra complexity

17 Shaping and BW allocation  BW allocated to the shaped stream depends on the shaper parameters  Traffic policing imposes access delay avoiding overflow delays into the network  Trade-off between the access delay(stringent policy) and the network delay(lenient policy) at the switching nodes due to buffer overflows

18 Bandwidth Allocation  The viability and economical feasibility of packet video are largely contingent on the ability to reduce its BW requirements:Several approaches have been proposed that rely on one or more of:  Statistical multiplexing  Temporal smoothing  Multicasting

19 Statistical Multiplexing The goal: Reduce the BW requirements of bursty sources.  Aggregation mechanism by which several individual streams are asynchronously superposed and transported over the same channel  BW is allocated to the aggregated traffic, resulting in a reduction in the per-stream allocated BW

20 SM with statistical guarantees  Relies on stochastic models.Useful in determining the required resources for real-time video whose traffic profile is unknown Obstacles:  Difficulty in characterizing the departure traffic from a statistical multiplexer  Restricted applicability of the models  Accurate video models often require specifying more parameters than what is currently supported by the standards

21 SM with deterministic guarantees MPEG sources can be statistically multiplexed at the video server and transported to a switch with minimal bounded delay and no losses. The server allocates BW to the multiplexed traffic based on the peak value of the aggregate envelope.By manipulating the phase shifts between the MPEG sources the allocated BW can be less than the sum of the source peak rates

22 SM with deterministic guarantees  PSAB (Per Stream Allocation BW) Depends on the relative starting times of the MPEG streams  u :vector of the relative phases Specifies the synchronization structure of the MPEG streams with respect to their GOPs  u vector can be optimized by allowing the server to control the starting times of new streams in order to minimize the PSAB at the cost of adding delay  Maximum delay:GOP period

23 SM with deterministic guarantees   MRP scheme (Minimum Rate Phase) A new stream is scheduled for multiplexing in a phase for which the aggregate bit rate is minimal  Even if no scheduling is performed,some bandwidth gain can still be realized by multiplexing MPEG streams.In this case u has an arbitrary structure,not controlled by the server

24 Temporal smoothing  General idea is to introduce a buffer in the path of the stream,either at the sender or at the receiver to reduce the variability in traffic  Sender : Real-time video stringent relay requirements and delay jitter guarantees  Receiver : Archive video buffer placed inside the client set  Smoothing buffer acts as low pass filter by averaging the bit rate over a time window whose length is determined by the size of the buffer and its drain rate

25 Temporal smoothing  For archived video the availability of the traffic profile makes it possible to combine video smoothing with pre-fetching.  Video frames are transported to the client prior to their playback times  The client maintains a buffer that temporally store and smoothes out the received frames  Research for a transmission schedule which ensures that underflow and overflow will not occur at the client’s buffer

26 Temporal smoothing- JSQ pre-fetching  JSQ(Join the Shortest Queue) approach for pre-fetching archive video  Assumes :  A single shared link between server-clients  Buffer in the client’s set  Principal idea:  Keep track of the number of frames that have been sent to each client.Sending different numbers of frames to each client,the server exploits the VBR nature of video  Favoring clients with shortest queues  Up to 100% utilization of the link

27 Smoothing/SM  Investigate how video smoothing affects the statistical characteristics of video streams  Investigate the effect of smoothed independent/correlated video streams on network resource control and management(impact on SM gains)

28

29  Unsmoothed: Periodic correlation  Smoothed: Strong correlation(depending on the buffer size)  Reducing of fast-time scale rate variability has implications on network resource management, especially buffer allocation.

30 Smoothing/SM gain  Independent streams:Video streams arriving at the multiplexer are randomly displaced.The starting frame is likely to be any one of the frames  Correlated streams:many users may start watching videos with a short time span,thus producing correlated video streams.  Multiplexing gain: (1-Total BW /Total peak rate)x100%

31  Unsmoothed:70%-80%  Smoothed :10%-60%  Still significant multiplexing gains to be exploited by VBR when individual streams are smoothed,especially when client buffers are relatively small Independent smoothed streams-SM gain

32 Correlated video streams-SM gain  Correlated video streams have an enormous impact on aggregation of homogeneous sources,leaving almost no gain.  There is much less severe impact when heterogeneous streams are aggregated

33 Comparison  Statistical multiplexing:  Suitable for real-time video in which multiple distinct streams are to be transported over the same path  Omnidirectional video where several collocated cameras generate distinct video streams which are sent to the same direction  Temporal smoothing:  Preferred for archive video whose traffic profile is known a priori.  Multicasting:  Best suited when a single video stream is to be transmitted to multiple destinations sharing portions of the path

34 CISCO Proposals  Transmit priority: 4 levels  Bandwidth allocation:  Call Admission Control  Insured Rate  Maximum Rate

35 CISCO Proposals  Traffic Policing: at the edges of the network  Maximum Burst  Insured Burst

36 CISCO Proposals  LB algorithm-Dual LB