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Traffic Shaping and BW Allocation Papalexidis Nikos
30/3/2001
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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
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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 canDrop the violating cellsTag them as a lower priority trafficHold them in a reshaping buffer
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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
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Traffic Shapers-Schemes
Leaky Bucket Window shapers
Jumping windowMoving window
Composite ShapersComposite Leaky Bucket
Dual LBTriple LB
Composite windows
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Leaky Bucket
Data buffer
Peak rate
λp
Average rate
λa
Token
buffer
λt token rate
d
b
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Leaky BucketSimple to implementThe 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
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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
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Leaky Bucket
Actual bit rate=Y x Negotiated mean bit rate
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Leaky Bucket
Mean bit rate entering the network(leaky rate)=E x Negotiated mean bit rate
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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 rateIdeal behavior as M increases and l decreases.Low M and high l (near peak) provides almost no
control
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Leaky BucketLB 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
AlternativeAllow the violating cells to enter the network with low
priority and discard them at the congested nodes (increase of the utilization/probable congestion)
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Different LB typesOne LB is not effective for policing both peak and
mean rate.Dual LB is proposedFirst LB should control the peak rate.
Leaky rate set to the peak rateCell which do not confirm are simply dropped
Second LB controls the mean rateAs 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 1st LB is discarded whenever one of the parallel buckets (controlling the mean rate) overflows .
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Triple LB
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Time window shapersJumping 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
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Composite window shapers
Composite jumping windowTime windows are encapsulated
Composite moving windowExtra complexity
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Shaping and BW allocationBW 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
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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 multiplexingTemporal smoothingMulticasting
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Statistical MultiplexingThe 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
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SM with statistical guaranteesRelies 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 multiplexerRestricted applicability of the modelsAccurate video models often require specifying more
parameters than what is currently supported by the standards
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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
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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
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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
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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 trafficSender : 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
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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
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Temporal smoothing-JSQ pre-fetching JSQ(Join the Shortest Queue)
approach for pre-fetching archive video Assumes :
A single shared link between server-clientsBuffer 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
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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)
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Unsmoothed: Periodic correlationSmoothed: Strong correlation(depending on the buffer size)Reducing of fast-time scale rate variability has implications on network resource management, especially buffer allocation.
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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%
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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
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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
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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
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CISCO Proposals Transmit priority: 4 levels Bandwidth allocation:
Call Admission Control Insured RateMaximum Rate
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CISCO Proposals Traffic Policing: at the edges of the network
Maximum Burst Insured Burst
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CISCO Proposals LB algorithm-Dual LB