A Flow Control Algorithm for Multimedia Network Applications ...

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A Flow Control Algorithm for Multimedia Network Applications Raffaele Bolla, Alessandro Iscra, Mario Marchese, Sandro Zappatore Department of Communications, Computer and System Science (DIST) University of Genoa, Italy lelus, iscra, dama, zap @dist.unige.it

Abstract: A flow control mechanism operating at the application level and aimed at controlling audio/video flows in order to provide a sufficient level of perceived quality of service (P-QoS) to each user is presented. Compression parameters and techniques are varied to dynamically adapt the output bit rate of the application to the network load, according to a mechanism based on feedback information from the receiver. The novelty of the paper is, more than the algorithm itself, the proposed integration of audio and video and the effects of p-loss on the MOS of the audio and video streams. The results show that the algorithm yields not only a drastic reduction of the video packet loss but also a significant improvement for the audio streams, due to the reduction of the congestion over the network while MOS of the multimedia applications are substantially unchanged. The implicit improvement of the P-QoS in the video flow is an important result, that highligths the effectiveness of an end-to-end control mechanism for best-effort traffic.

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Introduction The Experimental Setup The Control Scheme Experimental Results Packet-Loss VS MOS Conclusions Bibliography About this document ...

Introduction Internet is characterized by heterogeneity of algorithms and management, as well as of physical links. It hosts high speed channels like ATM, FDDI, low speed phone links, wireless multi-access channels. The formulation of a flow control problem is very difficult in this context, since an algorithm suited to a high speed, guaranteed service network, cannot be applied in a low-speed best effort environment. Moreover, Internet is a mix of many organizations and providers and its development will be incremental and independent as concern the resources management policy. Meanwhile, the number of services and applications is growing faster and faster and the danger of network collapse due to congestion is real. The Internet research community is very active to find countermeasures, and various groups are working on Internet control and performance guarantees.

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Different approaches and intervention are considered: some are based on a pre-allocation of resources [1,2,3], other use characteristics of the IP packet [4]. The approaches based on a preallocation of resources [5] are attractive because they allow to get precise performance requirements; nevertheless, they heavily depend on the used traffic models and they are affected by the network heterogeneity, as stated above. Control schemes at higher level (as TCP) cannot control parameters at application level (like, for instance, the coding mechanism) being independent from the upper layers. Moreover, many real-time applications (e.g. video-conference) use UDP, that is connectionless and does not apply any control mechanism. A possible choice is moving the control mechanisms at the application level. It allows controlling all the parameters at application level and delegates the control problem to the network borders (end-to-end). In this case independence is achieved from the network characteristics, there is no need of channel admission control (CAC) schemes and of complex traffic models. Besides, it is believed that Internet will continue to be dominated by best-effort traffic [6,7]. This type of traffic does not require precise performance guarantees which could be obtained by a resource pre-allocation, but the congestion implications are severe, since the traffic which is not controlled affects the behaviour of other traffic, both controlled and not. In this context, end-to-end control at application level acquires a particular meaning. From this point of view, the reference has been RTP [8] and the Audio/Video Working Group [9]. The proposed flow control mechanism is sketched in Fig. 1. The overall communication is divided into blocks. The block called ``Smart Coder'' is the control part: the ``Congestion/Encoder Controller'' implements the control algorithm that in this way operates at the application level. Finally the Encoder processes both the video and audio streams generating the bit rate input to the network. The goal of the Smart Coder is to provide a sufficient level of P-QoS to end users by controlling the video encoder parameters that are changed to dinamically adapt the output bit rate of the application to the network load. The mechanism is based on feedback information [10,11,12,13] from the receiver The algorithm presented is not new, because it has been already experimented [14] in a video only environment.

Figure 1: The Overall Communication Scheme The novelty of the paper is the proposal of integration between audio and video and some considerations about the effect of P-loss on the MOS of the audio and video streams. The QoS perceived by the users is considered along with the formal definition of the ``Encoder parameters'' as a vector. The proposed technique takes into account the possibility of changing not only some parameters inside a coding technique, as tipically done by the other approaches in the literature, but the compression technique itself. Within the above described framework the paper deals with point-to-point audio/video communication. The paper is structured as follows: Section II contains the description of the experimental setup and some results about the traffic behavior. Section III summarizes the flow control scheme and Section IV presents the experimental results in terms of P-loss related to the audio/video integration. Finally, relationships between packet loss values and the P-QoS of some standard encoding schemes are discussed in Section V. The conclusions are contained in Section VI.


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The Experimental Setup In this section we summarize the main features of our network testbed and the characteristics of the traffic behaviour upon which our control scheme is based. The testbed consists of a stub local Ethernet network with a limited number of computers. A workstation is devoted to generate a copy of a previously recorded traffic, thus reproducing the data load that are present in a real LAN (i.e. traffic not due to multimedia sources); we call this kind of traffic an ``asynchronous load''. Other stations play the role of a multimedia transmitter, generating both a video and an audio stream. Other hosts have been employed to receive the audio/video flows, to compute the packet loss and to feedback the transmitters. A large set of measures has revealed that packet loss is a good marker of network congestions: in other words, in presence of a high traffic load on the net, the P-loss increases and a multimedia source bit rate reduction generally yields a relevant P-loss decrease. Unfortunately, when P-loss is low no useful indication about the congestion status can be derived. Therefore, only a suitable probing can discover the capability of the network to accept a higher bit rate for the multimedia application. A more complete discussion of these issues was presented in [14].

The Control Scheme The proposed control scheme is aimed to maximize the perceived quality of service of both audio and video streams while reducing the loads offered to the network in order to minimize the risk and the duration of congestion events. Our control scheme is presented in Fig. 2 and the related algorithm is depicted as a flow chart in Fig. 3.

Figure 2: Scheme of the Smart Coder that Implements the Proposed control Algorithm According to the feedback (P-loss) of the receiver end, the transmitter varies the traffic offered to the channel by changing some parameters of the video coder (such as quality factor, frame rate and so on) without any actions on the audio codec. The reason for this strategy is the fact that ) stream compared to the output of modern audio codecs generate a very low bit rate ( commercial video codecs. In fact the audio compression is so high that any attempt to further reducing the output bit rate would drastically affect the quality of the reproduced sound/voice at


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the receiver end. On the other hand, audio encoding schemes are so sophisticated that P-QoS gains can hardly be achieved even if the channel would allow higher bit rate flows. On the contrary, video coding methods offer many degrees of freedom, related to the capability of changing output coder bitrate from fourty to three hundred of

.

Figure 3: Flowchart of the Proposed Control Scheme This property can be taken into account in order to avoid or prevent network congestions that could hardly be reduced by a variation of audio loads, due to the extremely low bitrates produced by audio encoders ( Let

,

). In the following, we briefly describe the flowchart of Fig. 3.

to be the bit rate produced respectively by a bank of video coders and by a single

audio encoder. Then the overall audio/video information rate is (at the mux output): (1)


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Finally, let

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to be the bit rate at the output of the Smart Coder. Generally

can differ from

as the Smart Coder decides to probe network capability by adding a sort of redundancy bits to the flow produced ( ) by the video encoder. Initially the video coder is set to work with the lowest bit rate

, according to a ``slow start'' approach, and no redundancy is introduced, so

that

. A timer

Periodically (every

and a variable

are initialized to zero and

seconds) the smart coder receives the audio (

respectively. ) and video (

loss feedback from the receiver end and computes the weighted average packet losses:

) packet-

of video and audio

(2) Therefore, even if the audio encoder is not controlled, the audio packet loss plays a significant role in the control algorithm. If the average p-loss ranges in the

interval,

done and the transmission continues with the same bit rate; else if

, nothing is , the upper bound of

, the video bit rate is reduced; the new bit rate , is a function of the old one and . In our experiments, we have computed the new video load by means of the following formula: (3) where

is a factor heuristically determined and

is the lowest bit rate the encoder can

assume. No redundancy is introduced, and therefore than

. On the other hand, if

, the net capability to accept an increase in load is tested by an increase in

affecting

is less without

; in other words, a redundancy is introduced in order to protect the video and audio

flows from an increase in P-loss during the test period. The new value of old one ( ), of and ; specifically, we have chosen:

is a function of the

(4) In this new condition, if the next value of the augmented load and then

is greater than

, the network is unable to accept

is reset to the previous lower value. Else, if during the next

seconds the network is able to accept the new traffic load, another video compression scheme is chosen, characterized by a bit rate . In order to speed up the bit rate increase, a new value of

(

) is selected.

Experimental Results As stated in Section II, in our experimental tests, four workstations transmit audio/video streams and one reproduces the asynchronous load shown in Fig. 4, that has been recorded over a LAN located in the Image Processing Laboratory of DIST. Due to the applications used, typically image exchanges via ftp and nfs, the traffic is very high and impulsive. Two sets of results are presented


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in the following: the first one shows the audio and video packet loss in case no control is applied. In this case the video stream bitrate is kept constant at

. The second set of tests has

been performed by employing the control algorithm to the video sources. In this case the video up to

streams are characterized by a variable bit rate ranging from audio flow bit rate is kept constant to

. The

and no control is applied in all the results

presented. The values of the parameters mentioned in the flow chart depicted in Fig. 2 have been chosen heuristically: ,

,

, ,

,

,

,

. Fig. 5 shows the values in percentage of the P-loss of the

overall audio stream averaged over a measure window. The video flows are not controlled. The P-loss values of the overall video flow in the same situation are reported in Fig. 6. Fig. 5 and Fig. 6 have to be taken as a reference to perform a comparison with the controlled case. P-losses for the audio and video traffic if the control algorithm is applied are shown in Fig. 7 and Fig. 8, respectively. It is important to note that not only the P-loss of video flows is drastically reduced, but the audio stream too takes advantage of the application of the control scheme. This is due to the reduction of the congestion over the network. A comparison between Fig. 5 and Fig. 7 shows how the significant reduction of the loss peaks. Fig. 9 shows as the control algorithm acts on the encoder reducing or increasing the bit rate of this latter according to the packet-loss estimates. Many other experiments have been performed with different parameters and all the results confirm the behaviour of the sample case reported in the mentioned figures. It is important to remark that the control mechanism acting on all the multimedia sources does not affect the fairness of the whole system; in other words, no multimedia station dominates over the other ones.

Figure 4: Asynchronous Traffic Load (in kbit/s) vs Time Used to Perturb Video/Audio Sources.


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Figure 5: Measured Average Packet-loss vs Time of Audio Streams when no Control is Applied to Video Flows of 256 kbit/s.

Figure 6: Measured Average Percentage Packet-loss vs Time of Video Streams of 256 kbit/s when no Control is Applied.


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Figure 7: Measured Average Percentage Packet-loss VS Time of Audio Streams when the Control Algorithm is Applied to Video Flows. (Video Source Bitrate Ranges from 32 up to 256 kbit/s).

Figure 8: Measured Average Percentage Packet-loss vs Time of video Streams when the Control Algorithm is Applied to video Encoders. (Video Source Bitrate Ranges from 32 up to 256 kbit/s).


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Figure 9: Bit Rate Offered to the Channel when the Control Algorithm is Enabled The implicit improvement of the P-QoS in the audio flow (the audio application is not controlled and its bitrate never reduced) is an important result that highligths the importance of an end-to-end control mechanism for best-effort traffic. The analysis of video and audio traffic and their impact on the user are currently under investigation, but some preliminary results are presented in the next section.

Packet-Loss VS MOS In this section, the relationships between packet loss and related MOS values are discussed in order to show the effectiveness of the proposed control scheme. For this purpose, some standard coders have been taken into account and the corresponding measure of P-QoS at different levels of packet loss has been estimated. The results reported in Table I must be considered preliminary because of the limited number of subjects (twelve people chosen among technicians and students of our laboratory) and the small set of the audio and video coders that have been tested. Specifically, MOS has been evaluated for the following coders: H.263, NV (the coder used by the popular Network Video application), JPEG with quality factor of 25, 50 and 80. Moreover, a raw video sequence has been also evaluated, as a sort of reference stream. All the sequences have been displayed in the standard CIF format by using a high quality 17'' color monitor at 4 frames per second. We have decided to use this frame rate so that the output bit rate of the codecs corresponds to the values of load offered to the network during the experiments presented in the previous section. Table I presents in each column the MOS values obtained for the employed codecs at a fixed packet-loss value (first row). In other words, in each row of the table the MOS at different levels of packet-loss is reported for a selected coding scheme (first column). Table I: Relationship Between Packet-loss and MOS for Six Standard Video Coders. Each Cell Reports the MOS for a Codec (row) and a Fixed Value of Packet Loss (column) 0 H263(41 kb/s)

5

10 15 20 25

3.3 3.1 2.9 2.8 2.7 2.5


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NV(115 kb/s)

3.5 3.0 2.4 2.7 1.8 1.5

JP25(350 kb/s)

4.5 3.7 3.5 3.0 2.5 2.2

JP50(422 kb/s)

4.5 3.6 3.4 2.9 2.5 2.2

JP80(562 kb/s)

4.5 4.1 3.6 3.4 2.7 2.4

PLAIN(9.5 Mb/s) 4.7 4.0 3.4 2.8 2.6 2.4 The audio stream was always processed by the G.729 coder thus producing a

output

flow. In order to improve the robustness of the received audio stream, we have assumed to quadruple each packet by means of a suitable, packet oriented, interleaving algorithm. The description of this latter is out of the scope of this paper and will be the object of future works. By comparing Figs 6, 8, 9, we can note that, in presence of high P-loss values (see, for instance, the estimates between 1200 and 1500 seconds), the control changes the encoder speed in order to reduce the bit rate from

to

. Therefore, the coding agent chooses the encoding

scheme in order to comply with the suggestion of the congestion controller: in our case (see Table I) the speed reduction is obtained first by switching the encoder from JPEG25 to NV and then from NV to H.263. Taking into account the corresponding values of P-loss and the MOS estimated for the previous codecs, we can note the benefits obtained by using the control mechanism: for instance, we see that equal or higher values of MOS can be achieved with NV or H.263 coders when P-loss is lower than a MOS value of 3 when the packet loss is

, with respect to the case of JPEG coder that presents . Benefits are also achieved for the quality of the

received audio stream. In fact, studies [15] have proven that generally audio is intelligible if packet loss is less than about

. We can note (compare Fig. 7 with Fig. 5) that the presence

of the control algorithm reduces the audio packet loss to values that rarely are above

, thus

granting a good audio reproduction.

Conclusions The proposed flow control algorithm has been applied in an environment where a workstation generates traffic reproducing data in a real heavily loaded LAN, while the other stations are multimedia transmitters that generate video and audio streams, and the audio flow is not controlled. Two sets of results have been obtained: audio and video packet loss in case no control is applied to the video traffic and the same quantities when the control algorithm is applied to the video sources. The results prove that the P-loss of video flows is drastically reduced and that the audio stream too takes advantage of the application of the control scheme for a reduction of the congestion over the network. Loss peaks of audio traffic are strongly reduced. The effects of P-loss reduction on the P-QoS at user-end have been also taken into account by evaluating MOS of some common codecs at different level of P-loss. The preliminary results show that video application MOS is substantially unchanged while MOS of the audio stream improves.

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