Enforcing application-level QoS by frame-induced packet discarding in video communications

Enforcing application-level QoS by frame-induced packet discarding in video communications Srinivas Ramanathan, P Venkat Rangan, Harrick M Vin and Srihari Sampath Kumar

Advances in networking are making it feasible to support a wide spectrum of video services over fast packet-switched networks. In this paper, we investigate the problem of providing efficient QoS guarantees for video communication, when they are expressed at the application-level, in terms of video frames, rather than at the network-level, in terms of packets. We propose a simple to implement, yet effective, strategy called frame-induced packet discarding (FIPD), in which, upon detection of loss of a threshold number (determined by an application’s video encoding scheme) of packets belonging to a video frame, the network attempts to discard all the remaining packets of that frame. We present extensive, trace-driven performance simulations that demonstrate the efficacy of the FIPD strategy. Networks employing the FIPD strategy exhibit significant increase in the number of video channels that they can support. Towards such networks, using a discrete time Markov chain model of the FIPD strategy, we devise a method for computing the frame loss probabilities of video applications, which then serves as the criterion for admission control: the network admits an incoming application only if the predicted frame loss probability (in the event of admission) does not exceed the frame loss bounds of any of the applications being serviced.

Keywords: multimedia terminals and systems, video communications, multimedia protocols

Motivation

Technological advances in hardware are revolutionizing computers and networks so as to support multimedia collaborative applications, including those that employ virtual reality, and services such as multimedia mail, news distribution, advertisement and entertainment in

Multimedia Laboratory, Department of Computer Science and Engineering, University of California at San Diego, La Jolla, CA 92093, USA (email: {venkat}@chinmaya.ucsd.edu)

the near future”*. An important problem in supporting digital multimedia communication over computer networks is Quality of Service (QoS) management, which refers to strategies for allocating network resources so as to guarantee real-time performance of continuous media, such as video and audio. The design of a novel QoS management strategy targeted at supporting video services efficiently over ATM-like fast packet-switched networks constitutes the subject matter of this paper.

The importance of strategies for efficient apportion- ment of network resources is underscored by the wealth of related literature. Strategies for providing deterministic delay bounds have been presented by Golestani3, who proposes the Stop-and-Go queueing discipline, and by Parekh and Gallagher4, who develop a rate-based scheduling discipline called Generalized Processor Sharing. Such strategies, which provide hard real-time guarantees, are not tailored for video applications that can withstand minor, infrequent QoS violations, the extent of which is governed by human perceptual tolerances. Hence, QoS management strategies relying on statistical multiplexing techniques that take advantage of such tolerances to enhance network utilization are gaining prominence. Ferrari and Verma’ present such a strategy that allocates network bandwidth and buffer space only if QoS violations predicted based on an analytical model are within application-specified tolerance bounds. Analytical techniques for providing statistical guarantees have also been proposed by Guerin et al.(j and Kurose7. An observation-based approach for offering QoS guarantees has been proposed by Clark et al.8. In this approach, an application is admitted for service only if predicted extrapolations from status quo network measurements indicate that the QoS requirements can all be met satisfactorily. Hyman et al.’ develop the

742 0140-3664/95/$09.50 0 1995-Elsevier Science B.V. All rights reserved computer communications volume 18 number 10 October 1995

concept of an admissible load region that delineates network conditions under which bounds on loss, delay and connection blocking probabilities are guaranteed to be satisfied.

In the above-mentioned approaches, QoS requirements are both expressed and enforced in terms of network-level transport units, such as packets (or cells in ATM terminology). The QoS requirements of video applications, on the other hand, are generally in terms of video frames, each of which may be composed of multiple packets. Merely using the frame-level QoS requirement itself as the packet-level QoS requirement may not be sufficient. To see why, consider a scenario in which video frames are encoded using the basic DPCM algorithm”. Although it achieves a high degree of compression, the DPCM algorithm is highly susceptible to losses; loss of even one of the packets of a frame will result in the loss of that entire frame. Suppose each video frame is composed of 100 packets, and that an application requests for a 1% bound on the frame loss. If the .network were to provide a 1% bound on the packet loss instead, in the pathological case, one packet could be lost for every consecutive 100 packets transmitted by the application, thereby resulting in the loss of each and every video frame. Of course, a straightforward way in which the network can guarantee the application-requested 1% bound on the frame loss is by providing a 0.01% bound on the packet loss. However, this constitutes an overly stringent demand on the network, potentially leading to its under-utilization.

Based on the above reasoning, we advocate that future integrated networks must implement mechanisms that can exploit video application specified hints to better utilize the network resources. Doing so will not unduly complicate the network design; rather, such an approach will be mutually beneficial to the video application and to the network provider: from the application’s perspective, such an approach relieves the application of mapping its requirements to the network domain, and from the network’s perspective, such a design enables the network to provide exactly what the application requires and no more, thereby optimally utilizing its resources.

Our contributions

To address the problem of satisfying frame-level statistical QoS requirements of video application, we introduced’ ’ a simple packet discarding strategy called frame-induced packet discarding (FIPD). In this strategy, upon detection of loss of a threshold number (determined by an application’s video encoding scheme) of packets belonging to a video frame, the network attempts to discard all the remaining packets of that frame.

In this paper, we elaborate upon the implementation of the FIPD strategy and its effectiveness in providing frame-level QoS for video applications. We present a

Enforcing application-level QoS: S Ramanathan et al.

detailed end-to-end design for a network of high-speed switches implementing FIPD, and highlight the simpli- city of this implementation. We present extensive trace- driven performance simulations to demonstrate the efficacy of the FIPD strategy. In particular, networks employing the FIPD strategy exhibit significant increase in number of video channels that they can support. Towards such networks, using a discrete time Markov chain model of the FIPD strategy, we develop a method for computing the frame loss probabilities of video applications. The frame loss probability thus computed serves as the criterion for admission control: the network admits an incoming application for servicing only if the frame loss probability following the admission does not exceed the QoS limits of any of the applications being serviced.

Although described as a frame discarding scheme, the FIPD strategy is applicable even when coding schemes employ block-level encoding, aggregating strips of neighbouring pixels into self-contained video blocks12. In such cases, loss of a packet only affects other packets constituting the same block as the lost packet. Hence, for supporting block-level video encoding schemes, network switches can distinguish between packets belonging to different video blocks, and can selectively discard packets constituting individual blocks (rather than entire frames). Hierarchical encoding schemes too can benefit from the FIPD strategy: different loss thresholds can be assigned to the high and low resolution components, and statistical guarantees can be independently provided for each of the components.

The rest of the paper is organized as follows. In the next section, we present the FIPD strategy. A detailed performance evaluation of the FIPD strategy is then given, and a channel admission procedure for a switch servicing homogeneous video channel is developed. This is extended for the case of heterogeneous video channels. End-to-end issues in the FIPD-based admission procedure are addressed, and finally conclu- sions drawn.

QoS MANAGEMENT BY FRAME-INDUCED PACKET DISCARDING

The system environment we consider is a network of fast-packet switches interconnecting multimedia work- stations and video capture and display sites such as video cameras, videophones, etc. (see Figure I). Video information is captured as frames and transmitted as fixed sized packets over connection-oriented channels through the network. The switches are assumed to be output-buffered’33 14: associated with each output link of a switch is an internal buffer of size B packets, where packets destined for that link are temporarily stored prior to transmission. Each buffer is serviced for transmission at a constant rate of one packet per time slot.

At the time of establishment, each video channel requires guarantees of minimum bandwidth, and

computer communications volume 18 number 10 October 1995 743


Figure 1 Network of high-speed switches interconnecting video capture and display sites

maximum end-to-end delay, delay jitter, frame loss and asynchrony. Whereas the minimum guaranteed bandwidth must be large enough to accommodate motion video of acceptable resolution, the end-to-end delay must be small enough for interactive communication. To avoid breaks in continuity of video display, both delay jitter and frame loss must be sufficiently small. Simultaneous display of multiple media also requires that the asynchrony between their display be bounded within human perception tolerances. Among these QoS requirements, bandwidth, delay and loss guarantees can be regarded as fundamental, since they have to be provided by the network layer*5. On the other hand, both delay-jitter and synchronization guarantees can be enforced at the transport or higher layers of the network architecture (using bandwidth, delay and loss guarantees provided by the network layer)‘5”6. Furthermore, assuming bounded buffers, violation of either the bandwidth or the delay constraint at the network layer induces buffer overruns at switches, resulting in frame losses ‘. Hence, if the buffers at network switches are appropriately sized, QoS management strategies only need to explicitly control frame losses at the switches.

For providing efficient frame loss guarantees for video communication, we propose a simple to implement, yet effective, packet scheduling strategy called frame-induced packet discarding (FIPD) that can be employed at the network switches. This strategy attempts to exploit the inevitability of loss of a frame on a channel whenever a subset of the constituent packets of that frame is lost. The subset of packets (of a frame) whose loss invalidates the frame (henceforth referred to as packet resiliency) depends upon the encoding scheme employed. In the simplest case, as in the basic DPCM algorithm, loss of even one of the packets of a frame may result in the loss of that entire frame. In a more

*This is assuming that frame losses at the network layer cannot be compensated for at higher layers using retransmission-based schemes, mainly due to the real-time nature of video. + Since errors during transmission over tibre optic networks are negligible, we assume that the communication links are reliable, and hence buffer overruns at the switches are the only cause of packet loss.

general case, such as when forward error correcting schemes are employed’7, the loss of up to a certain threshold number of packets can be tolerated before the corresponding frame is lost. A switch that implements the FIPD strategy forcibly discards all the packets constituting a video frame whenever it detects the loss of more than the threshold number of packets of that frame. The network bandwidth and buffer space released by the packets thus discarded can be reallo- cated to other video channels, thereby permitting networks employing the FIPD strategy to admit and service a larger number of video channels as compared to those that only consider packet-level QoS strategies. The closer the first packet loss of a frame is to the beginning of the frame, the larger is the performance gain of FIPD. Thus, when buffer overrun occurs, a switch may implement a latest frame first (LFF) discarding policy according to which, the video frame to be discarded is the one that has received minimum service (i.e. the number of packets of that frame that have been serviced is minimum) at the switch.

One of the attractive features of the FIPD strategy is the ease of its implementation. To selectively discard packets, network switches must identify frame boundaries by recognizing packets that constitute the same video frame. A straightforward way is for each video source itself to associate a ‘frame-identifier’ bit with each packet, and to flip this frame-identifier bit for successive frames that it transmits (for instance, the frame-identifier bit could be 0 for the first frame, 1 for the second, 0 for the third frame, and so on, as depicted in Figure 2a). In an ATM network, the AUU bit, which is slated for inclusion in the payload type field of the ATM cell header to enable AALS compatible adapta- tion layers to reassemble fragmented frames at destina- tions, can also be used as the frame-identifier.

To implement FIPD in a multi-hop network, it is also necessary to ensure that frame discard at one switch does not affect the guarantees provided by subsequent switches on the route from a video source to the destination. As an illustration, consider the example in Figure 2a: video frames transmitted by a source pass through switches Si and S, en route to the destination. Suppose that the first frame is corrupted at switch SZ due to buffer overruns; therefore, switch Sz begins discarding all packets with a frame identifier value of 0. Further, suppose that the second frame is entirely discarded at switch Si itself, so that no packet of this frame reaches switch Sz. Now, when the third frame is forwarded by switch SI, since all packets of the third frame have the same frame identifier value (of 0) as packets of the first frame, switch S2 fails to detect the boundary between the first and third frames. Hence, switch S2 inadvertently discards the third frame comple- tely, even though this frame has experienced no packet loss at all.

The simplest method to enable all the network switches to correctly identify frame boundaries is to guarantee that at least one packet of each video frame is transmitted from the source to the destination.

744 computer communications volume 18 number 10 October 1995


Clearly, FIPD is simplest to implement when intra- s1 s2 frame encoding schemes (such as JPEG) are employed.

I I ____________________* When inter-frame encoding schemes (such as MPEG)

Frame 1 m m m m-,; are employed, information present in one video frame

-a’ (I-frame) may be used for reconstructing subsequent

____________________*

Frame1 m m u?l Et-\ ._-

Frame 2 [III m-:, ,*’

Figure 2 Bit-switching technique for identifying frame-boundaries in a multi-hop network. (a) Scheme in which the sources set the frame- identifier value for each video frame at the time of its transmission, and the network switches SI and & that are en route to the destination, continuously monitor the frame-identifier bit to detect frame boundaries. In the scenario shown, the second frame is entirely discarded by switch St (indicated by the dotted arrow), switch & fails to detect the boundary between the first and third frames; (b) bit- switching technique. While transmitting packets of the third frame, switch S, toggles the frame-identifier value, based on the last frame that it forwarded to switch S, (which in this case was frame 1)

However, for doing so, it is necessary to reserve one buffer per-channel at each switch. To avoid the overhead of explicit buffer reservation at switches, we propose a simple bit-switching technique (so named because of its resemblance to the ‘label-switching’ technique used in ATM networks for routing cells between input and output links). In this technique, as before, each video source distinguishes between packets of successive frames that it transmits by flipping the frame-identifier bit. However, in addition, for each video channel, each switch en route maintains the frame-identifier of the last frame whose packets it forwarded to the next switch. When transmission of the next frame begins, the switch toggles the previous frame-identifier value and assigns it to all the packets of the next frame that it is able to forward on the same video channel. In this way, packets of frames that arrive one after another at each switch are guaranteed to have a toggled value of the frame-identifier, and hence each switch can correctly identify frame boundaries. Figure 2b depicts how the bit-switching technique enables frame boundaries to be detected in the scenario of Figure 2a; notice that in this case, the frame-identifier value is ‘local’, known only to a switch and its successor, but not ‘global’, known throughout the network. Since this bit- switching technique closely resembles the label- switching technique being proposed for ATM networks, it is amenable to implementation in hardware.

video frames (P and B frames), and hence a single video frame loss at the network may, in fact, trigger multiple frame losses, as seen by the application. In this case, it is simplest to regard a group of related frames as a meta- ,frame and to implement the FIPD strategy by considering all packets within a meta-frame as ‘related’. Alternatively, if the network can distinguish between different types of frames (for instance, in an ATM network, the cell-loss priority (CLP) bit in the cell header can be used for this purpose), the switches can implement different packet resiliencies for different frames (for instance, the packet resiliency for an I- frame may be much higher than that for a B-frame). This approach can also be used to distinguish between frames of different media (e.g. video and audio) during transmission of multiplexed media streams in which the different media are multiplexed together and transmitted over the same channel.

For video channels whose packet resiliency exceeds one, each switch must also maintain a count of the packets dropped for each frame. Since packet losses can occur at different switches at different times, and none of the switches may have global information about the other switches, the packet resiliency can be partitioned (equally, in the simplest case) amongst all the network switches en route to the destination. Each of the switches can independently monitor packet loss at its buffers, and discard frames as and when the per-switch packet resiliency bound is violated. Such an approach is proactive in the sense that it discards a frame at the first instance at which the frame may have been rendered corrupt by packet losses during transmission. While doing so, however, this approach may result in some frames being discarded because the per-switch packet resiliency for a frame is exceeded, even though the total packet resiliency for the frame may not have been exceeded.

To demonstrate the practical utility of the FIPD strategy, in the next section, we present trace-driven simulations that we have carried out, using commonly available JPEG” and MPEG video traces.

PERFORMANCE EVALUATION OF FIPD

The target environment comprises of a network of 300 Mbit/s, ATM switches, each with a buffer capacity of 500, 53-byte packets. The JPEG video traces were 2.5 hour-long Star Wars sequences, with a frame rate of 24 frames/s, the average frame size being 628 packets/ frame, and the average bandwidth being 6.4 Mbit/s, The MPEG video traces were also transmitted at a rate of 24 frames/s, the average sizes of I, P and B frames being 23 1, 158 and 76 packets/frame, respectively, and the average bandwidth being 0.97 Mbit/s.



8 O.‘O- 4

3 s 0.60.

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0 t o-50.

a Number of JPEG video channala

0.40.

0.30.

020.

0.10.

0.00 '0 io io 3i 4-o io 6-a io sb b

Number of JPEG video channels

Figure 3 Performance of a switch servicing multiple JPEG video channels. (a) In the absence of FIPD, the frame loss fraction is much different from the packet loss fraction (0: Without FIPD, frame loss vs. channels; x: without FIPD, packet loss vs. channels); (b) implementing FIPD at the switch bridges the gap between the frame loss and packet loss fractions (x: With FIPD frame loss vs, channels; 0: with FIPD, packet loss vs. channels). In both cases, video frames were transmitted at the link speed, and packet resiliency is 1 packet/frame

Our first experiment serves to validate the necessity for employing FIPD at network switches. In this experiment, several JPEG-encoded video channels are multiplexed through an ATM switch that implements First-Come-First-Served (FCFS) scheduling (all of the video channels used the same JPEG traces; however, each channel commenced transmission from a different point in the trace). Figure 3~2, which depicts the performance when packet resiliency is one packet/ frame, illustrates that in the absence of FIPD, the discrepancy between packet loss and frame loss fractions is large; when the packet loss fraction is lo%, the corresponding frame loss fraction is four times as large. Similar discrepancies between packet loss and frame loss fractions were also observed for other video encoding schemes: MPEG, hierarchical JPEG and run- length encoding, thereby demonstrating the requirement for FIPD-like QoS management strategies for enforcing application-level frame loss guarantees.

Figure 3b illustrates the effectiveness of FIPD. By discarding entire frames, FIPD isolates frames that experience packet loss from those that do not, and thereby reduces the fraction of frames that are lost during transmission. In the process, FIPD bridges the gap between frame loss and packet loss fractions; the slight difference that is observable in Figure 36 between frame loss and packet loss fractions is a result of variations in video frame sizes, introduced by JPEG compression.

By judiciously discarding all the packets of a lost frame, FIPD not only reduces the frame loss fraction but also releases network bandwidth and buffer space for new channels. Hence, a switch that employs FIPD admits and services a greater number of video channels than a switch that does not employ FIPD. Figure 4 illustrates this marked increase in servicing capacity of a switch employing FIPD, for a frame loss tolerance of 0.15.

Figure 3 also illustrates the influence of applications’

OJ I

0 10 20

wacofmm*4~~8/uc.~

Figure 4 Increase in number of video channels admitted at a switch when FIPD is employed; a fractional frame loss tolerance of 0.15 and packet resiliency of 1 packet/frame are used in this simulation (0: with FIPD; x: without FIPD)

frame loss tolerances on the effectiveness of FIPD. Some applications may require very high-quality transmission, e.g. medical imaging, and may have very low frame loss tolerances. For such applications, the performance gains yielded by FIPD are low; in the limit when an application cannot tolerate any frame loss, FIPD becomes ineffective. In general, video applications possess moderate to high tolerances. Moreover, loss tolerances also increase with the rate of video display: whereas at a frame rate of 10 frames/s loss of three frames every second is likely to be perceived as lack of motion and, hence, deemed intolerable; at a frame rate of 30 frames/s, the same fractional loss may be tolerable. The larger an application’s loss tolerance, the greater is the number of frames that can be discarded durin; transmission; the performance benefits accruing from FIPD accumulate with each such discard, hence FIPD is more effective at higher tolerances.


0 0.00 0.10 0.20 0.M 040 0.50 060 0.70 0.80

a JPEG Video Iram loss ftacthm

b 000 0.10 020 0.30 040 0.50

JPEG Viwo ‘Em i:Yactb:*

0.00 o.io o.io 0.530 o.io 0.30 O.ko o.io 0.80

C JPEG Video tim loss fraction

Figure 5 Effect of increasing packet resiliency on the performance of a switch implementing FIPD. (a), (b) and (c), respectively, represent the cases when the packet resiliency is I, 150 and 250 packets/JPEG frame, out of a total number of approximately 628 packets per frame. In this case, video frames are transmitted as and when digitized. 0: with FIPD; X: without FIPD

Packet resiliency may also vary, depending both upon the robustness of the encoding scheme and the application. As the packet resiliency of a video channel increases, a switch has to wait for a longer duration

a


before deciding to discard a frame (in the extreme case, when the packet resiliency equals the frame size, the switch is not able to discard any frame). The concomi- tant delay in detection of frame loss reduces the buffer space and bandwidth savings that accrue from FIPD. Hence, the higher the packet resiliency, the lower is the effectiveness of FIPD. Figure 5 demonstrates the drop in effectiveness of FIPD as packet resiliency increases for the case when video frames are transmitted immediately following their digitization.

Interestingly, our simulations reveal that the choice of packet resiliency also depends upon the transmission patterns of video frames: the frequency and distribution of packet losses is influenced by whether video frames are transmitted as and when they are digitized, or whether the video sources voluntarily shape their traffic by distributing transmission of the packets of each frame within the playback duration of a frame. In the former case, when video frames are transmitted immediately following digitization, packet losses are bursty: only a small fraction experience large losses and a large fraction of frames experience few packet losses. On the other hand, when traffic shaping is resorted to, packet losses are distributed more uniformly amongst all the frames. Figure 6 contrasts the packet loss distributions that occur in the above two cases, for the same frame loss fraction (0.15) and the same packet resiliency (150 packets/frame). In the absence of traffic shaping, over 63% of frames experience nd packet loss at all, whereas when traffic shaping is in effect, only 0.3% of frames experience no loss, but over 70% of frames lose as many as 50 to 150 packets/frame. In the former case, owing to the relatively infrequent occurrence of packet loss, a packet resiliency of 150 packets/ frame may be acceptable. However, owing to increased frequency of packet losses, we infer that video sources that resort to traffic shaping must specify lower packet resiliencies.

It is also interesting to compare the relative influence of packet loss and frame loss in the above experiments. Suppose that 1 is the bandwidth required for each video channel to guarantee no loss. If o! denotes the fractional frame loss and p denotes the packet resiliency as a fraction of the frame size, the minimum effective bandwidth of a video channel is (1 - LY) * (1 - b) * 1. Consequently, for two sets of values. (u,, /?,) and (~2, pz) such that (1 -c(,) * (1 - PI) = (1 - CQ) * (1 - &), the minimum effective bandwidth required per channel

b Figure 6 Influence of video transmission pattern on the distribution of packet losses at a switch. (a) Packet loss distribution when JPEG frames are transmitted as and when digitized; (b) effect of traffic shaping on the packet loss distribution: packet losses are more uniformly distributed over all the frames. In both cases, the fractional frame loss is 0.15 and

( packet resiliency is I50 packets/frame, each frame comprising. of 628 packets,

Pdul Ik9 ps Ime - on average



remains the same. Therefore, one would expect the maximum number of video channels multiplexed through a switch to be equal in both cases. However, this is not the case in practice. For instance, compare the scenario when an application can tolerate up to 40% frame loss, but no packet loss within a frame (i.e. when video frame loss fractions is & = 0.40 and packet resiliency is one in Figure 5a, with the case when an application cannot afford to drop a frame, but up to 40% of the packets of a frame are discardable (i.e. when video frame loss fraction is 0% and packet resiliency is 250 packets/frame in Figure 5~). Whereas in the first case up to 42 channels can be admitted by the switch, in the second case only 15 channels can be admitted. This result stems from the fact that intra-frame packet losses are much more bursty than frame losses over a channel. It is precisely this bursty nature of packet losses that FIPD exploits to improve network performance signifi- cantly.

Variations in frame sizes also influence the performance of FIPD. When the average frame size is high, packet losses are more bursty. Moreover, since the effectiveness of FIPD is directly related to the bandwidth freed up by frame discarding, the larger the sizes of video frames, the greater are the bandwidth savings, and hence the greater the effectiveness of FIPD. Table 1 corroborates this observation. In this experiment, video frame sizes are doubled and the frame rates halved, so as to retain the same per JPEG-channel bandwidth as before. As expected, the decrease in frame loss fraction is greater when the frame size is larger.

All of the above-mentioned experiments point to the effectiveness of FIPD when employed at a switch that is directly connected to the video sources. Figure 7 depicts the performance of the FIPD strategy in a multi-hop network that is structured as a three-level hierarchy of 300 Mbit/s switches. The performance gain in this case is comparable with that observed for a single switch, illustrating that FIPD retains its effectiveness even in multi-hop networks.

Figure 8 illustrates the performance of FIPD for MPEG-encoded video channels. In this experiment, different packet resiliencies are employed for I, P and B frames, and frame discarding is adaptively triggered, reflecting the greater priority of I frames compared to P

Table 1 Evaluation of the performance of a switch employing FIPD with increase in frame size. The video frame size is doubled, and the frame rate is halved to 12 frames/s so as not to alter the bandwidth required’ per video channel. As can be observed, the greater the average frame size, the greater is the reduction in frame loss fraction yielded by FIPD

No. of JPEG video channels

Reduction in frame loss fraction

Normal frame size Doubled frame size

5 0.0000 0.0000 10 0.0000 0.0003 I5 0.0057 0.1573 20 0.0748 0.2376 25 0.0852 0.2447 30 0.1082 0.3101

a

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E” 0.30.

E $ 0.20.

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0 10 20 3Q 40 54 60 70 80 90 loo

b Number of JPEG video channels

Figure 7 Evaluation of FIPD in a multi-hop network. (a) Multi-hop network under consideration. The network is structured as a hierarchy of 300 Mbit/s switches through which several JPEG video streams from different sources are multiplexed and transmitted; (b) reduction in frame loss fraction resulting from deployment of FIPD in a multi- hop network is of the same order as that observed in the case of a single switch. The packet resiliency in this experiment is 150 packets/ frame (0: with FIPD; x: without FIPD)

Figure 8 Performance of a switch implementing the FIPD strategy when MPEG encoded video channels are multiplexed through the switch. The video frame rate is 24 frames/s and the packet resiliencies for I, P and B frames are chosen to be 50, 25 and 10 packets/frame, respectively. 0: with FIPD; x: without FIPD

and B frames, and that of P frames over B frames. For a frame loss tolerance of 0.15, FIPD permits a switch to admit almost 60 additional MPEG channels. Besides demonstrating that the effectiveness of FIPD is inde-



pendent of the media-encoding scheme used, this experiment also highlights the resilience of FIPD to different frame size distributions (MPEG channels exhibit more than 6:l variations in frame sizes; as compared to the 3:l variation exhibited by JPEG channels”).

Having demonstrated the practical utility of the FIPD strategy, in the next section, we proceed to develop methods to analytically quantify the performance of FIPD so as to obtain fractional frame losses that can be guaranteed to video channels at the network. The fractional frame losses thus computed serve as the basis for admission control of video applications at the network level.

FIPD-BASED ADMISSION CONTROL AT THE NETWORK

When an application request for a video channel is received by the network, an underlying routing mechanism is assumed to yield a candidate path for the video channel. The video channel is established only if (i) each of the switches along the path determines that the channel can be admitted without violating the loss guarantees provided to all the existing channels serviced by the switch, and (ii) the frame loss for the new channel aggregated over all the switches does not exceed the maximum loss tolerance of the channel. Assuming video sources to be Markovian20*2’*, the formulation of the FIPD-based admission control procedure at a switch consists of the following steps:

1. Modelling of the switch and the video channels multiplexed through it as a discrete time, finite state, Markov chain: each state in the Markov chain encapsulates the buffer occupancy at the switch and the activity modes of all the channels.

2. Computation of the frame loss probability at the switch and its comparison with frame loss tolerances of each of the channels: the frame loss computation requires the identification of all possible states of the Markov chain in which buffer overruns will occur, and the determination of the probabilities of occurrence of each of these overflow states. The computed frame loss probability, if it is within the bounds of all of the existing channels, represents the lowest frame loss guarantee that is offered by the switch to the new channel requesting admission.

Both of the above steps are elaborated in the following sections. We restrict our analysis to the case of an intra-frame video encoding scheme in which loss of any packet of a frame invalidates the entire frame, and also assuming that the video channels are homogeneous, i.e. the video channels are all characterized by

*Coding schemes that induce Markovian behaviour of the video sources have been proposed recently”. Sources with more complex models can be analysed by approximating them to ‘equivalent’ Markovian models, using moment-matching techniques, such as those described by Guerin et al.‘.

the same average recording rate R, frame size V, as well as maximum fractional frame loss guarantee, fmax; subsequent sections generalize the results so obtained to heterogeneous channels.

Markov chain modelling of video channels at a switch

Consider a switch $ that implements the FIPD strategy for servicing N video sources. The video sources are assumed to be periodic Markovian: each video source shuttles between ON and OFF modes (see Figure 9); the ON mode corresponding to the transmission of packets of a video frame, and the OFF mode corresponding to the idle period between successive frame transmissions.

Given the average rate of video recording, R (in frames/slot), and the average size of video frames, /(in slots/frame), since the video sources are Markovian, both the ON and OFF periods will be geometrically distributed with mean durations I/ and $ - I/, respectively. The probability, CY of transition of a video source from ON to OFF, and the probability, b of a transition from OFF to ON can be obtained based on computa- tions of expected values of geometric distributions as follows:

cx

c 1 i*(l-a)‘_‘*a=I/*cc=-

I=1 I/ (1)

Corresponding to the ON and OFF modes of a video source are the ACTIVE and INACTIVE modes of its associated video channel (see Figure 10). The transition probabilities from ACTIVE to INACTIVE and from INACTIVE to ACTIVE are therefore exactly equal to c( and b, respectively.

In the event of a buffer overrun during the transmission of a video frame, the FIPD strategy causes the video channel that experiences packet loss to make a transition from the ACTIVE mode to a HOLD mode. Once the channel enters a HOLD mode, it remains in that mode until all of the remaining packets of the lost frame are received and discarded by the switch, after which the video channel moves to the INACTIVE mode. Similar to the ACTIVE and INACTIVE periods, we assume that the period for which a channel is in the

l-a 1-P

w

B

Figure 9 ON-OFF Markovian model of each video source; r and p are the probabilities that the source changes mode from ON to OFF, and from OFF to ON, respectively



Figure 10 Activity modes of a video channel. Whereas the transition of a channel from ACTIVE to INACTIVE mode corresponds to the transition of the source from ON to OFF, the transition from ACTIVE to HOLD corresponds to the occurrence of buffer overruns at the switch

HOLD mode is also geometrically distributed. If the switch employs the latest frame first (LFF) discarding policy, packet losses are likely to occur close to the commencement of transmission of the video frames, and hence the expected duration of the HOLD period closely matches that of the ACTIVE period; thus, the probability of a transition out of the HOLD mode, y, can be approximated to F . ’ * Table 2 summarizes our usage of various symbols, subscripts and superscripts.

Owing to the Markovian behaviour of video channels, the switch and the associated video channels

*For switches that do not employ the LFF policy, y may be some fraction of $. In such cases, the value of y for a network that services v channels can be estimated based on observations of y prior to the admission of the Nth channel. This approach is validated by performance simulations of ATM networks, which indicate that changes in y between successive admissions are increased.

Table 2 Use of symbols, subscripts and superscripts in this paper

can be modelled as a discrete time Markov chain. Each state of the Markov chain, S, is represented by the buffer occupancy at the switch, b, and the number of ACTIVE, INACTIVE and HOLD channels, denoted by NA, N’ and NH, respectively; that is, state S is represented as a quadruple S = (b, NA, N’, NH), where NA, N’, NH E [0, N]. Since the sum NA + N’+ NH must equal the total number of video channels, N, assigning values to any two of NA, N’ and NH automatically fixes the value of the other. Conse- quently, the total number of states of the Markov chain that are possible is: O(B * N2).

Computation of frame loss probabilities

At a switch, the buffer occupancy and the number of channels that are ACTIVE in a state will determine whether or not a buffer overrun occurs in that state. Specitically, a buffer overrun will occur in a state Sj = (bj, Nf, Nj, NJ!) if and only if bj + NY > B, as a result of which the number of frames lost is the larger of the two values: (0, bj + Nf -B}, which if it is non- zero, indicates that Sj is an overfrow state. The expected total number of frame losses at the switch is the sum of the probabilities of occurrence of each such overflow state weighted by the number of frames lost in that state.

Computation of overflow state probabilities The probability Pj of occurrence of an overflow state Sj is product of the probability Pi of existence of the Markov chain in a state Si and the probability Pij of a transition from Si to J’j, summed over all states Sj:

Symbol Explanation

R I/

; Y N cI,...,cK B b s h4 P f max

4

Average rate of video recording Average size of video frames Probability of change in activity mode of a channel from ACTIVE to INACTIVE Probability of change in activity mode of a channel from INACTIVE to ACTIVE Probability of change in activity mode of a channel from HOLD to INACTIVE Number of video channels K heterogeneous classes of video channels Buffer capacity at a switch Buffer occupancy at a switch in state S A state in the Markov chain Total number of states of the Markov chain State or state transition probability in the Markov chain Application-specified maximum fractional frame loss tolerance Expected fractional frame loss at switch $

Subscript

i ij k

Explanation

Refers to the value of a quantity in state $, i E [l, M] Refers to the value of a quantity during the transition from state S: to state S,, i,j E [I, M] Refers to the value of a quantity corresponding to class Ck, k E [l, Kj

Superscript

A, H, I AH, HI, Al

Explanation

Refers to the value of a quantity in ACTIVE, HOLD and INACTIVE modes, respectively Refers to the value of a quantity during a change in the mode from ACTIVE to HOLD, HOLD to INACTIVE, INACTIVE to ACTIVE and ACTIVE to INACTIVE, respectively


Enforcing application-level QoS: S Ramanathan et a/.

(2)

where M denotes the total number of feasible states of the Markov chain.

In addition, by the fundamental law of probability, the state probabilities PI, P2, . , PM together must sum to unity. That is:

M

c Pi = 1

;=I (3)

The system of equations* (2) and (3) can be solved to yield the state probabilities Pi, Vj E [l, M], if transition probabilities Pi,, Vi, j E [ 1, M] are available. The method for computing the transition probabilities is presented next.

Determination of state transition probabilities For a transition of the Markov chain from a state Si to a state S/ to be feasible, it is easy to see that the following constraints have to be satisfied:

l Buffer occupancy constraints 1. If bj + Nf 6 B, Nf packets arrive in state S;,

and no packets are lost. If either b; or N: is non- zero, one packet is serviced and the value of bi for the next state Si is given by: bi = bi + Nf - 1. On the other hand, if both b; and Nf are 0, no packets are serviced and b, = 0.

2. If 6, + Nf > B, then packet losses due to buffer overruns are incurred in state Si; the buffer occupancy remains B during S; but drops to B - 1 at the end of Si due to the servicing of one of the packets. Hence, bj must equal B - 1.

l Channel mode change constraints Since a channel can move to the ACTIVE mode only from the INACTIVE mode (see Figure IO), the total number of ACTIVE channels in state Sj is bounded by the sum of the ACTIVE and INACTIVE channels in state S;. That is, N,! < NY + N;. Since a channel can make a transition to INACTIVE mode from either the ACTIVE or the HOLD mode, all the channels can potentially be INACTIVE in state Si. Hence, NJ’ d N. Since a channel can move to the HOLD mode only from the ACTIVE mode (see Figure IO), the total number of channels that are on HOLD in state S’ is bounded by the sum of the number of the channels that are ACTIVE and those that are on HOLD in state S;. That is.

If all of the above-mentioned constraints are satisfied, the transition from S, to J’i is feasible, and hence the

*Owing to the cyclic dependencies between the state probabilities, only (M - 1) out of the M equations represented by equation (2) are independent. These (M- 1) equations, together with equation (3), constitute a set of M independent linear equations that can be solved for determining PI, P?, , PM.

Figure 11 Changes in the modes of video channels during the transition of the Markov chain from state S, to S,: N!.“. NT’. N!!

I

and N;9’ represent the number of channels making a t&siti& fro& ACTIVE to HOLD, from HOLD to INACTIVE, from INACTIVE to ACTIVE and from ACTIVE to INACTIVE, respectively

probability of the transition from Si to Si, denoted by P,, is non-zero. The exact value of PI, is determined by the number of channels that change mode from ACTIVE to HOLD, from HOLD to INACTIVE, from ACTIVE to INACTIVE, and from INACTIVE to ACTIVE, denoted by N{.“, Nz’, N:’ and y.y, respectively (see Figure II), as well as their probablhties, which can be computed as follows:

l Determination of N$“. As alluded to earlier, packet loss occurs in state Si iff 6, + Nf > 8. Hence, the number of packets lost in S;, which corresponds to the number of channels changing mode from ACTIVE to HOLD is:

N {“=max(O,b;+NP-B) (4)

From the right-hand side of the above equation, it can be observed that NC” is entirely determined by state Si (and does not depend upon state Si). Hence, given that the initial state is Si, the change in mode of NC” channels from ACTIVE to HOLD is a deterministic event, that is, its probability is unity:

P!” = 1 l/ (5)

l Determination of NC’. The total change in the number of channels m the HOLD mode, during the transition from S; to Z’/, given by N,fl - NH, is the difference between the number of channels that have moved into the HOLD mode (possible only from ACTIVE mode), given by NC”, and the number of channels that have moved out from the HOLD mode), given by NY. That is:

N! - N! = N!.” - N!? I 1 Ii II

Substituting for NC.” from equation (4) and solving for NH’ we obtain: 11 ’

Nfj’=Ny-N,!+max(O,b;+N~-B) (6)

Given y, the probability that a channel undergoes a change of mode from HOLD to INACTIVE, the probability that exactly NY channels (out of a total of NH channels that are on HOLD in SJ undergo a change from HOLD to INACTIVE is given by:



(7)

l Determination of N;y and Nt!. Since the total change in the number of ACTIVE channels during the transition from S; to Sj, NJ’ - Nf , is the difference between the number of channels that have moved into the ACTIVE mode (possible only from the INACTIVE mode), given by NY, and the number of channels that have moved out from the ACTIVE mode (to either INACTIVE or HOLD modes), given by NC’ + NC.“, we have:

N;-N;=N;;-NC’-N$H

Substituting for Nt.” from equation (4) and solving the difference, N’f - Nf, we obtain:

NY-N~=N~+max(O,b;+N~--B) (8)

Consequently, the values of Nf and NY are not independent. Niy can take values ranging from 0 to N:, and Nf can take values ranging from 0 to Nf - NG”, but their difference must satisfy equation (8). The probability that N!! channels move from INACTIVE to ACTIVE and A?! channels move from ACTIVE to INACTIVE, summ& over the values that NY can take, i.e. 0 < NY < Ni, is:

p!! = ‘J

(1 -a) Nf-k+h * 1 where 6 = Nf - Nz!.

The transition of the Markov chain from Si to Sj is the collective consequence of NtH channels changing mode from ACTIVE to HOLD, NY channels from HOLD to INACTIVE, N:f channels fro; INACTIVE to ACTIVE and NY channels from ACTIVE to INACTIVE. Therefore, the probability of the transition from Si to Sj, Pij is the product of probabilities PiH, of such channel mode changes, respectively:

p- = p”.N * PfiJ * p?‘? IJ lJ II lJ (10)

Substituting for ejH, Pr and P:y from equations (5), (7) and (9), respectively, the value of Pij can be determined. The state transition probabilities, P,, computed for all pairs {Si, Sj} of feasible states of the Markov chain, can be substituted in the system of linear equations (2) and (3), and can then be solved for the overflow state probabilities.

Channel admission at a switch Having computed the state probabilities Pi, for all overflow states, Sj, the expected frame loss in a slot, which is, by virtue of the FIPD strategy, the same as the expected packet loss, can be estimated to be: CE, Pi * max (0, bi + Nf - B) where max (0, bi + Nf - B) is the number of packets lost due to buffer overruns in

state Si. Given an average video frame rate of R frames/ slot for each of the N video channels, the expected fractional frame loss at switch + for any of the channels is given by:

*max(O,Nd+&B)

R*N (11)

Whenever a new channel request is received at a switch, II/, the switch admits the new channel only if the fractional frame loss predicted by equation (11) does not exceed the frame loss tolerances of any of the existing channels. The value of F, represents the best frame loss guarantee that the switch $ can offer to the new channel.

ADMISSION CONTROL OF HETEROGENEOUS CHANNELS

The FIPD-based admission control scheme developed above for the homogeneous channels can be extended to the case of heterogeneous channels. Heterogeneity among video channels arises due to differences in encoding techniques, display rates, resolution, etc. With the emergence of standards such as JPEG** and MPEG23 (for video encoding), and HDTV (for display rates and resolution), however, it is possible to cate- gorize video channels into a small number of heterogeneous classes (within each class, the channels are homogeneous)g.

Since channels within each class are homogeneous, the admission control procedure developed above can be directly applied if the network services heterogeneous classes by statically partitioning its resources amongst these classes. However, in practice, dynamic on-demand allocation of resources, since it can potentially utilize resources much more efficiently, is preferable. In this case, the admission control formulation must take into consideration not only the interactions among channels belonging to the same class, but also the interactions among channels of the different classes. Extending the admission control procedure developed above to the case of heterogeneous channels is the focus of this section.

Suppose that a switch + services K heterogeneous classes, C,, CZ, . . . , CK, consisting of N,, . . . , NK video channels, respectively. Extending the above model, the switch and its video channels can be represented by a Markov chain, with each state of the Markov chain being represented as a (3K + I)-tuple:

S = (6, {N;, N;‘, . . . , N;}, {N:, N;, . . . , N’,},

{N:, N;, . . . , N;})

where (i) b E [O,B], (ii) Vk E [l,K] Nf, NL, Nf E [0, Nk] and (iii) Vk E [l, Kj Nf + N: + NF = Nk. Using the above constraints, it is easy to deduce that the number of valid states of the Markov chain is O(BNtNz . . . Ni).

The next step is the determination of the transition probabilities between states of the Markov chain.



Considering any pair of states S; and <i, defined as:

s; = (b;,{N$,. . > Nf,), {q, 3. . ., $K),

{N;,.. .y N&H

Sj = (bj,{ N,fl, . . , Nj$}, IN;, 7 , N; K),

{N&,Ni’l,))

The feasibility of the transition S; to Sj depends, as before, upon the constraints imposed by the buffer occupancy and the states of the media channels. These constraints can be rederived for the case of heterogeneous channels to be:

l Buffer occupancy constraints

1. If b,+C,K_,N$ < 8, no packets are lost. If

either bi or C,“=, Ntk is non-zero, bj is given by:

bi = bi + C,“=, N$ - 1. On the contrary, if

both bi and C,“=, N$ are 0, b/- = 0.

2. If bi + C,“=, N$ > B, buffer overrun occurs,

and bj must equal B - 1. l Channel mode change constraints

1. V/G[l,K]N,;,<N;k+N:k

2. Vk E [I, K] Nlk d Nk

3. Vk E [l, K] N,yk G N$ + Nyk

If all of the above constraints are satisfied, the transition from Si to Sj is feasible. To determine the probability P;j of this transition, once again, the number of channels moving between ACTIVE, INACTIVE and HOLD modes, and their associated probabilities of occurrence must be determined, the method for which is described next:

l Determination of N$T If b; + C,“=, N$ < B, no packet loss occurs. Hence, Vm E [l, K]: N$T = 0.

On the other hand, if bi + C:=, Nfk > 8, packet loss is incurred due to buffer overruns. How the total number of packet losses, given by bi + C,“=, N$ -8, is distributed among the different classes that share buffer space at the switch is determined by a buffer management policy chosen by the switch. For instance, the switch may distribute the packet losses among classes in proportion to their number of ACTIVE channels. Under such a policy, the number of ACTIVE channels of each class that experience loss and hence, move to HOLD mode is given by:

V’kE [l,K] N;.; = b;+cN$-g * i= I

N:k

c: 1 N$ (12)

l Determination of NFk The number of channels moving from HOLD to INACTIVE during a state transition can be derived in a manner similar to equation (6) to be: Vk E [l, K]: Nck = N$ - Ni’[‘k + N;,:.

l Determination of N& and N$ Following the same procedure as in the case of homogeneous channels to derive equation (S), we determine that the difference, Nf$ - N$ must satisfy the condition:

Vk E [l, K]: N$ - N$ = N$ - N$ + N:‘k”

Furthermore, Nfk must lie in the range [0, Nj,], and N$ must lie’in the range [0, Nfk - N$z].

The probabilities P$,“k of N;ff channels moving from ACTIVE to HOLD mode, P!’ of NY: channels moving

‘$J from HOLD to INACTIVE, Pji,k of N$ channels moving from INACTIVE to ACTIVE, and N$ channels moving from ACTIVE to INACTIVE, can then be obtained in a manner similar to equations (5) (7) and (9). Since the transition of the Markov chain from S; to Sj is the collective consequence of all the above-mentioned mode changes of channels, its probability, Pij is the product of probabilities Pt.:, Pyk and PC!, taken over all the K classes, and is given by: ’

pi.,= [fiptT] * [gp$Ik] * [$p$!k] (13)

The computation of state probabilities of the Markov chain using the state transition probabilities obtained from equation (13), and the subsequent computation of expected fractional frame loss for each of the K classes can be carried out in a manner similar to that given earlier.

END-TO-END ADMISSION CONTROL

When an application request for a video channel is received by the network, an underlying routing mechanism determines a candidate path for the video channel. Each switch II/ along the chosen path independently performs the admission control test to determine whether it can admit the new channel without violating the guarantees provided to all of its existing channels. As an outcome of a successful admission test, the switch also determines the best fractional frame loss guarantee, fti, that it can offer to the new channel. Assuming that the frame loss at a switch is independent of those at other switches, the probability of successful transmission of a frame over the new channel is the product of the probabilities of successful transmission at each of the switches along the chosen path: &,, (1 - f+). Hence, the end-to-end frame loss probability for the new channel is: 1 - n,, (1 - f $).

The new video channel is admitted to the network only if the end-to-end frame loss probability computed above does not exceed the application-specified frame loss tolerance, &,,,, that is:

F,,,2 [1 $1 -f*)] (14)

In the above admission procedure, each of the switches (in the path chosen for the channel) performs



the admission test independently, in assuming that the video channel traffic at its input is Markovian. In reality, the video traffic at the input of a switch may have undergone perturbations at the preceding switches; such perturbations can be smoothed out by reshaping the traffic at the input of the switch5. Furthermore, the admission test at each switch along the path also assumes that the frame rate and size of a channel at its input is the same as that of the application at the input of the first switch on the path. This is a slightly conservative assumption, since some frames may be discarded by the intermediate switches employing the FIPD strategy.

CONCLUDING REMARKS

In this paper, we have addressed the problem of satisfying statistical QoS requirements of video applications at the video-frame level. We have proposed a simple, yet effective, strategy called Frame Induced Packet Discarding, in which, upon detection of loss of a threshold number of packets belonging to a video frame, the network attempts to discard all the remaining packets of that frame. Although described as a frame discarding scheme, the FIPD strategy can also be adapted to coding schemes that employ block-level or scan-line by scan-line encoding. In such cases, network switches only discard packets pertaining to the same block or scan-line, respectively. Likewise, FIPD strategy is also applicable in conjunction with hierarchical encoding schemes: different loss thresholds can be assigned to the high and low resolution components, and statistical guarantees can be independently provided for each of the components. For reliable data transport protocols such as TCP/IP, FIPD can bound the proportion of retransmissions that may be necessary, thereby permitting networks to be utilized more efficiently.

Using a discrete time Markov chain model of the FIPD strategy, we have developed a method for computing the frame loss probabilities of video applications, which then serves as the criterion for admission control (by bounding the buffering capacities at the network switches, this very same approach can also be used to yield delay guarantees as well). Enhancing this admission control procedure to account for inter-frame dependencies, as well as different packet loss resiliencies, is the current focus of our research.

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Enforcing application-level QoS by frame-induced packet discarding in video communications