IN ATM NETWORKS 1. Duke Hong, Tatsuya Suda. Department of Information and Computer Science, Abstract

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1 CONGESTION CONTROL AND PREVENTION IN ATM NETWORKS 1 Duke Hong, Tatsuya Suda Department of Information and Computer Science, University of California, Irvine, CA Abstract The emerging B-ISDN is expected to adopt ATM (asynchronous transfer mode) as the transport network. This new network must support several classes of service with varying delay and loss requirements, such as voice, audio, data, and high quality video. It must also operate with link speeds in the hundreds of megabits per second and be scalable up to potential link speeds on the order of gigabits per second. The requirements to support multiple services and high speed pose problems not previously faced in traditional packet switched networks. Reactive methods of control become less eective due to the large propagation delay-bandwidth product. Packet processing delay becomes noticeably large in relation to the packet transmission time. Priority and other scheduling schemes must be devised to multiplex real-time streams with packet data eciently and fairly. This paper reviews some of the techniques directed at these issues. 1 Introduction B-ISDN is expected to be introduced into commercial service by the mid-1990's. It should provide support for transmission of both asynchronous data and synchronous real-time trac on an integrated ber transmission network. Expected applications include broadband video telphony, video conference, high speed digital information transmission, telefax, video/document retrieval service, and television distribution [2]. To support these services, it should provide support for interactive and distributive services, broadband and narrowband rates, bursty and continuous trac, connection oriented and connectionless calls, and point-to-point and broadcast communications [1]. ATM, or asynchronous transfer mode, is expected to be adopted by CCITT as the transport method for B-ISDN, although STM, synchronous transfer mode, was also considered. STM is an extension of the current narrowband ISDN which is based on an nb + D time division multiplexed (TDM) circuit-switched channel structure. Mostly due to its compatability to 1 This material is based upon work supported by the National Science Foundation under Grant No. NCR This research is also in part supported by University of California MICRO program.

2 narrowband ISDN, STM was initially thought to be better suited for B-ISDN than ATM. However, STM is not exible to changes in bandwidth requirements. Unlike STM, ATM does not suer from bandwidth inexibility, since ATM is a packet (or cell) switched network. Cells are xed size packets of 53 bytes each. Since calls are multiplexed on a cell level, ATM does not have the inexibility problem of rigid channel structures found in STM. New services can be readily adapted and old services dropped since bandwidth is \allocated" on demand. Another factor which favors ATM is the bursty nature of calls expected. Bursty calls are calls which generate a large amount of trac at some high peak rate for a short period of \active" time and generate little or no trac for some \idle" time. Calls in STM are deterministically multiplexed. The bandwidth allocated to a call would have to be based on the peak rate. With peak rate bandwidth allocation, the capacity of the network is wasted when calls are idle. In ATM, bursty calls are statistically multiplexed. Each call is assigned some bandwidth that is lower than its peak bit rate. Statistical multiplexing is more bandwidth ecient and allows more calls to enter the network. For more on ATM, see [1]-[7]. 1.1 The congestion control problem Congestion control in ATM is dicult because of the high link speed, diverse service requirements, and diverse characteristics of the trac ATM is expected to support. On the rst issue, CCITT has recommended two speeds for B-ISDN, one at approximately 155 Mb/s and the second at approximately 600 Mb/s. One eect of a high speed channel is that at these link speeds, cells must be switched at a rate greater than one cell per 3 s or 0.7 s. It has also been recommended that ATM architecture be scalable to even higher rates in the gigabit/s range. It is apparent that cell processing schemes in ATM must be performed at speeds comparable to the high switching speeds. This can only be done by simplifying the schemes enough to avoid the excessive processing time of software. Another problem caused by the high link rate is the increased propagation delay-bandwidth product. This is the amount of trac that can be in transit during a propagation delay time. Consider a 1Gb/s line with a propagation delay of 20 msec for a cross-continental distance of 6,000 km. In reactive control systems, when the network becomes congested, the destinations can send choke packets to the senders to stop or slow transmission. By the time that the choke packets are transmitted, 20 megabits are already in transit. By the time that the choke packet

3 reaches the sender, 40 megabits will have to be retransmitted. Large retransmissions can cause severe buer management problems. This can make many of the current congestion control schemes ineective. The second issue is eectively handling multiple service requirements. ATM must provide proper quality of service (QoS) for dierent service classes. A service class is a set of services which have the same QoS requirements. These requirements are usually measured in terms of maximum delays and cell loss rates. Figure 1 shows approximate delay and loss requirements for some expected services [8]. Some services such as voice, real-time video, and data for realtime control, also known as synchronous trac, have strict delay requirements. If packets are not delivered within their delay requirements, they are considered lost because of the real-time nature of the service. The delay jitter, the variance of delays, should also be small so that the output can be reconstructed in a continuous fashion. Although lost packets will have some adverse eects on real-time trac, in many cases a certain amount of loss is tolerable and will appear as noise. The service requirements of this type of trac is delay sensitivity, where the maximum amount of packets should be delivered within a delay requirement, with exible loss sensitivity. Asynchronous data trac can generally be characterized by a exible delay requirement and a strict loss sensitivity. As an example, le transfers have a stringent loss requirement. While the information transfer must be accurate, relatively long delays can be tolerated. In ATM, even if a call is admitted to the network, the network delay and cell loss may not be guaranteed due to ATM's packet switching nature. To satisfy diverse service requirements of synchronous and asynchronous trac, favorable treatment of some service classes may be necessary. The common ways of satisfying numerous QoS are with priority treatment of cells. We will examine these schemes later in detail. The third issue that aects congestion control in ATM is the diverse trac characteristics. Continuous bit rate trac will be accompanied by bursty trac. A typical example of bursty trac is very high bit rate trac such as video. Video has been modelled by peak and average bit rates of (11.75, 3.0), (14, 4.2), and (44.7, 16.8) Mb/s [10]. Burstiness is generally characterized by the ratio of a call's peak rate and the average rate of transmission. This is not an accurate measure since two calls with similar peak and average rates as in Figure 2 may actually have dissimilar trac characteristics. This implies other factors such as the burst length, the amount of time spent at the peak rate, or some equivalent measure must be considered. Although many methods exist for characterizing burstiness, most

4 are too complex for real-time implementation in ATM networks. For suitability of real-time timplementation, some recent papers have suggested using only the peak and average rates for feasibility [19][44]. To allow statistical multiplexing, bursty calls should only be allocated some bandwidth less than the peak rate so as to take advantage of the small probability that a large number of calls will be active simultaneously. Determining how much bandwidth to allocate to a bursty call must be resolved. The problem is further complicated by ATM's inability to guarantee loss and delay. In summary, the following important questions in ATM congestion control remain unresolved. What eect does the increased propagation delay-bandwidth product and fast cell processing time have on the choices made on congestion and ow control? What role does priority play in the handling of several classes of trac? Can we take advantage of the loss resiliency of real-time trac in priority handling? How do we determine how much bandwidth to allocate to a bursty call? How do we characterize bursty trac, and what is the role of burstiness in deciding a congestion control scheme? If bursty trac is detrimental to network performance, what steps can we take to shape the input trac so that it does not adversely aect the network? This paper reviews some of the recent papers that have been directed at these issues. It is organized as follows. Section 2 discusses congestion avoidance through admission control. In section 3, we discuss smoothing policies such as the leaky bucket and other rate control schemes. In section 4, priority schemes, and how they can be used to improve network performance with minimal loss in quality of service are studied. Finally, we summarize in section 5. 2 Call Level Control There are two main levels of congestion prevention in ATM networks. First, to avoid long term congestion and to maintain the trac load at a \manageable" level, we can exercise preventative control by regulating the admission of new calls into the network. Second, to avoid short term congestion, we can prevent congestion on the cell level. In this section, we will discuss the former.

5 2.1 Equivalent bandwidth Admission control is based on allocation of resources. When a new call arrives at an ATM network, the call is admitted as long as the network can support the expected trac. Since ATM is packet-switched, the network does not explicitly reserve any bandwidth for calls. Instead, expected trac is used as an indicator of the bandwidth required to support the new call to determine if the network can adequately support more calls. The diculty is in determining the amount of bandwidth that calls are expected to require, the equivalent bandwidth of a call. The measure of equivalent bandwidth is dependent on several factors. The most important factor is the ratio of the peak bit rate of the call and the link rate [14]. It was shown in [13] that (for homogeneous sources) for increasing values of available link rate, the multiplexing gain increases and the equivalent bandwidth decreases. The peak to link rate ratio should be smaller than 0.1 for statistical multiplexing gain [13][14][17][19][20]. If statistical multiplexing is protable (low peak to link ratio), then the burstiness, dened as the peak to average rate ratio, was shown in [14] to be the second most important factor. The third factor is the burst length. When the burst length increases, cell losses and delays increase signicantly [8]. The sensitivity of equivalent bandwidth to burst length is especially important when the burst length approaches buer sizes [14]. Other factors in determining equivalent bandwidth include the mean bit rate, cell loss and delay requirements of calls, and the mix of services in the network [13]. 2.2 Sharing network information One aspect of call level control is information passing. Information passing is the process building a table of link costs. Common methods use a broadcast algorithm with time stamping to order messages. Another class of methods use a shortest path tree to eliminate the need for message time stamps. One such method is the shortest path topology algorithm (SPTA) [27]. In [22], a method similar to SPTA was proposed for BISDN to provide information on cell level control. This new scheme can also be used with some modication in call level control to aid in routing. The idea behind this scheme is that with a few binary operations, a link cost table can be maintained. In this scheme, network information is in the form of a bit vector with each bit corresponding to a link indicating whether or not it is congested. Since this is a distributed asynchronous algorithm, nodes independently develop network information vectors and broadcasts this to

6 its neighbors periodically. Upon receiving a vector, rather than determining where to forward based on a shortest path tree (SPT), bit masks corresponding to the SPT are used to only keep information that is best known by the sending nodes, with the premise that neighbors on the shortest path tree will have the most recent information on links in their subtrees. This is used to update the receiver's vector. The vectors can then be used to aid in routing algorithms or admission control schemes. The processing required to maintain the vectors and use them is reduced to a set of quick binary operations. This is extremely important in an ATM environment where processing must be kept to a minimum. The vector approach has some disadvantages. This method is sensitive to the network topology and particularly to changes in the topology. Each node is required to know the exact topology of the network and propagation delay times for all links in order to generate the masks for its SPT. Applying this scheme to large networks may not be feasible since they require large bit vectors and complex maintenance of the network bit masks, particularly if nodes periodically fail and enter the network. 2.3 Admission control Once a route has been found, the admission control process must allocate resources for the new call at each node. During this process, a node must determine if it has enough resources to support the new call. The schemes described in this subsection can be used to accept or reject new calls based on their expected bandwidth usage. In a general admission control scheme, calls are admitted as long as resources are available. For instance, if we practice admission control using equivalent bandwidth, a new call is admitted if the equivalent bandwidth of a new call does not push the expected bandwidth usage for a link over the threshold of available bandwidth. This scheme is simple but may not fairly admit calls. Accepting a few calls requiring a large amount of bandwidth can block several smaller calls such that the call blocking probability becomes unacceptably high. Additionally, an inproportionate amount of bandwidth at a particular node may go to a few origin-destination pairs such that other origin-destination pairs may not have enough bandwidth. Two schemes to deal with these two problems are described below. The partial allocation scheme addresses the rst problem. Connections with high bandwidth requirements should not consume so much available bandwidth that calls with low bandwidth

7 requirements experience an unacceptable call blocking probability. Paper [23] proposed that a call should be admitted if its bandwidth requirement does not exceed some percentage of available bandwidth. Paper [23] showed through simulation that the arrival rate of high bandwidth calls did not aect the blocking probability of lower bandwidth calls under this scheme. However, this is at the expense of higher blocking probability for high bandwidth calls. The virtual path allocation scheme addresses the second problem. A virtual path (VP) is a logical link between a source and destination established on a long term basis consisting of a number of calls. Paper [24] proposed that each virtual path be allocated some small amount of bandwidth. The remaining bandwidth can be allocated to VP's upon demand as their bandwidth requirements exceed initial allocations. This dynamically allocated bandwidth is released when the virtual path no longer requires it. Analysis of two VP's with multiple connections on a single link showed that call blocking rates decreased and throughput improved by as much as 20% compared to the general allocation described above. The disadvantage of this scheme is that initially allocated bandwidth will remain unused if some VP's are temporarily inactive. Some exibility in bandwidth allocation may prove useful. The disadvantage of the admission control schemes described above and other admission control schemes are the amount of memory required and added processing overhead. The processes for admission control is generally performed at each node along a proposed route whether it uses bandwidth allocation or some measure of expected loss and delay. Each node must keep an account of the resources it has allocated and process call set-up packets. If a call is rejected, then a message must be sent back through the same route so that the intermediate nodes can free the resources. Each node must also process call tear-downs. An alternative scheme [22] replaces node-by-node admission control with pseudo-packets processed at the source and destination. Intermediate nodes do not have to perform costly operations on pseudo-packets as they would in previous admission schemes. To set up a real-time connection, a short stream of pseudo-packets called scouts with similar trac characteristics as the desired connection (such as average bit rate and burstiness) is transmitted on the desired route. If the scouts nd congestion along the path, then the scouts will either return to their source in excess of a specied maximum delay or be dropped at the congested link(s). In either case, the call is rejected. If no congestion is detected, then the call is admitted. The scout packet method of call admission and set-up may be the most viable approach for ATM among the schemes described above. However, its statistical performance is unknown. It can falsely admit a call if a large number of calls were idle when the scouts were sent.

8 Alternatively, it can falsely reject a call if there was a temporary congestion in the network caused by a large number of active calls even when there is generally enough capacity in the network to accommodate a new call. Its performance may depend on the length of the pseudopacket stream. A performance analysis of the statistical nature of the scout method is required. Call level control is a complex issue. Trade os must be made in performance and overhead in both admission control and information passing. Determining equivalent bandwidth is a dicult process at best. It is possible that the admission control scheme may need to account for any trac shaping that will be imposed on the trac source. In this case, the scheme for admission control will need to be made in conjunction with the smoothing scheme used. 3 Cell Level Control Previously, we discussed that bursty trac can deteriorate network performance. Cell level control can be exercised to reduce burstiness of trac sources. Schemes that shape trac, such as rate controls are discussed in this section. In addition, cell level control can be exercised to ensure the validity of call level control. This is done by ensuring that trac sources do not exceed allocated bandwidth. Schemes such as the virtual leaky bucket can be used for this purpose. 3.1 Leaky bucket and variants To shape the incoming trac at network edges and ensure that sources do not exceed allocated bandwidth, we can introduce a leaky bucket to the system. In a leaky bucket scheme, Figure 3, cells can only be transmitted when they can obtain a token from a token pool. If the token pool is empty, then the cell must either wait for a token before it is delivered into the network, or it can be dropped entirely. Tokens are generated at some (constant) rate r and stored in a token pool. The pool has a nite size denoted by. After lling the token pool, tokens arriving to the pool are discarded. can be seen as the maximum allowable burst length since a maximum of cells may be transmitted at one time. A token pool can be implemented using a counter that increases when tokens are generated and decreases when tokens are used. A system where cells queue instead of being discarded when the token pool is empty is considered in [25]. In this system, if there are no tokens available, then the cells queue in a buer until there is a token available. The cell blocking probability, the probability that a cell

9 arrives to an empty token pool, depends on the capacity of the cell buer and the capacity of the token pool only via their sum of the two [25][26]. This implies that by increasing the token pool capacity, we can eliminate the cell buer without aecting the steady state throughput and blocking. This is desirable since we can reduce delay due to a cell buer, and also since the implementation cost of a large token pool is smaller than the cost of a large cell buer. Paper [25] showed that the departure rate of cells can be made independent of its arrival rate by increasing the size of the token pool,, above some amount (approximately 10). The purpose of a cell buer at this point is to handle a system where the token pool control can turn on only during times of congestion (see [25] for details). One disadvantage of the leaky bucket is that the bandwidth enforcement that the token pool introduces is in eect even when the network load is light. In addition, [21] showed that the leaky bucket is highly likely to mistake nonexcessive trac as excessive. In other words, cells will be lost even though the long term average rate of the source is within the allocated bandwidth. To solve this problem, a virtual leaky bucket was proposed [8][9][28][29]. In a virtual leaky bucket, cells arriving to an empty token pool are marked red and transmitted without a token, while those that have tokens are marked green. (Other terms used are \marked" for red marked cells and \unmarked" for green cells.) Marked cells are considered violators of allocated bandwidth since the call must have exceed the allocated bit rate for some time for the token pool to be empty. Because bandwidth may still be available in the network, marking cells allows the call to exceed its allocated bit rate if it does not adversely aect other calls. If at some point along its path, a marked cell reaches a congested link, then it may be discarded so that the throughput of unmarked cells is not signicantly aected. This not only allows us to take advantage of a light network load, but it allows a larger margin of error in determining the token pool parameters [21]. Some have argued that marking is ineective and may degrade performance for unmarked cells [5]. However, buer management schemes exist which give near optimal performance for unmarked cells [9]. Another disadvantage of marking is that marking has no correlation to user level data priority. The user has a better understanding of which cells are more important in delivery whereas the marking system determines priority regardless of user level priority. This can be overcome by the user denoting which cells are best marked allowing the leaky bucket to mark those cells only when necessary. To further decrease the eects of marked cells on unmarked cells, [9] proposed the use to a second token pool for marked cells. Additionally, a spacer is used which imposes smoothing

10 as shown in Figure 4. When a cell is delivered into the network, its token is removed and the token enters a spacer. The tokens are discarded from the spacer at rate. The next cell at the head of the output queue cannot be transmitted even if there are green or red tokens available in the pool unless the spacer is empty. This assures us that cells are transmitted at a rate less than or equal to at all times by inserting \spaces" between cells (hence the name spacer). This eectively allows two levels of rate control whereas in the previous scheme, there is only one level of control, i.e. red cells can be transmitted at will. 3.2 Rate controls While leaky bucket schemes emphasize bandwidth enforcement, rate control schemes emphasize the importance of reducing burstiness to improve network throughput. The basic premise of rate control schemes is to allow some r bits of transmission per smoothing interval T. These schemes are commonly known as jumping windows or triggered jumping windows [12][30][31]. Imposing rate control on an input stream smooths trac entering the network at the cost of increased delay and occasional cell losses to maintain overall performance throughout the network. Rate control has been shown to minimize delay variance compared to straightforward non-smoothed trac. To allow for circuit emulations and to reduce the buer size, the smoothing interval, T, should not be greater than 1 msec [32]. As the smoothing interval T is reduced while keeping the same average bit rate r, [31] showed that the mean and variance of cell waiting time are reduced proportionately for the three trac types considered: voice, video, and data. Smaller smoothing intervals also reduce the required buer sizes. The smoothing interval cannot be decreased beyond some bound, however. Since the allocation of bandwidth in rate controls is determined as the number of cells allowed per smoothing interval, a smaller smoothing interval increases allowable transmission rate. The smallest unit of allocation is one cell per smoothing interval. Let 1r represent the smallest increment of bandwidth allocation. 1r = bits For T = 1 msec, bandwidth is allocated in increments of 424 kb/s which is much larger than requirements for many services. For example, voice calls require an average rate of less than 64 kb/s. To provide a small 1r, T must be larger than 1 msec. Thus, it would be benecial to study feasibility prospects of having dierent values of T for dierent classes of service. T

11 Rate control schemes reduce the burstiness of trac entering the network which improves network performance. However, even if cells enter the network smoothly, they can cluster together to form longer bursts at intermediate nodes in the network [32]. Stop-and-go queueing has been oered as a possible solution to maintain the original smoothness through intermediate nodes in the network [30][32]. In stop-and-go queueing, cells arriving during some smoothing interval F of length T do not become eligible for transmission until the next smoothing interval, F +1, as in Figure 5. This method not only maintains the smoothness property of trac entering the network, but has been shown to have an upper bound on a call's total queueing delay and required buer space. The queueing delay is bounded between H 2 T and 2 2 H 2 T, where H is the number of hops in the call. A buer space of 3C l T per link, where C l is the link rate, can eliminate buer overow. Another scheme which can guarantee service at intermediate nodes is to perform a pseudocircuit emulation. The 2-queue server with rate control, introduced in [33], can be used in conjunction with a smooth trac stream to provide guaranteed service for connection oriented (CO) services. In this scheme, two classes of trac are assumed, CO and data. For each byte of data serviced, we explicitly reserve bandwidth for K times as many bytes of CO trac through TDM. Data trac has an associated time of service (TOS) which is a measure of its delay requirement per node. The server services CO trac or remains idle if there is no CO trac until the time spent since the last data trac serviced becomes greater than TOS. The 2-queue server strategy provides good circuit emulation for CO trac. Simulations showed that this strategy is as good as a scheme where a xed priority is given to CO trac in minimizing delay jitter. 3.3 Observations To summarize cell level controls, we compare the leaky bucket approach and the rate control approach. Both schemes enforce allocated bandwidth and both schemes reduce burstiness. Rate control schemes are better at ensuring smoothness because of the burst capability of leaky buckets. A call under leaky bucket may use all its tokens at once during a burst. However, with a spacer, the smoothness of rate control schemes can be achieved in leaky buckets. Even without a spacer, [12] favors the leaky bucket to rate control schemes such as jumping window. [15] also found leaky bucket schemes to be near optimal for a practical control scheme. Another aspect which must be considered is exibility. By allowing marking, virtual leaky

12 buckets can allow calls to exceed its allocated bandwidth for short periods of time while still maintaining an overall level of cell transmission near the allocated rate. Conversely, rate controls do not allow excessive transmission for short periods of time. Marking not only allows exibility for the user to exceed allocated bandwidth, but exibility for the network in determining allocation as well. The denition of parameters need not be so precise if marking is used. 4 Priority Schemes We discussed in the previous section cell level control pertaining to bandwidth enforcement and trac shaping. In this section, we will discuss how to provide service for service classes with varying delay and loss requirements. To provide multiple grades of service with ATM, we can use priorities between and within service classes. Having determined priority levels for various services, we must handle prioritized cells in an appropriate manner during cell discarding and in scheduling. Discarding priority determines which cells are dropped when buer overow occurs. Scheduling priority determines the order of cell transmission. 4.1 Voice coding and reconstruction Before we begin on how to handle priority, we will investigate the delay and loss properties of voice. Many of the principles discussed here are applicable to other services such as video which also have strict delay requirements. The properties of the construction of analog signals, such as voice and video, from digital samples, allows us to take advantage of the ability of these services to withstand some losses and delay. Loss and delay appear as noise and do not render the rest of the trac useless as loss in, say, a le transfer might. Since cell loss is inevitable in an ATM network, schemes need to be devised to avoid severe degradation in the quality of the reconstructed signal. By dividing the information into important parts and less important (enhancement) parts, some cell loss can be tolerated. If any cells must be discarded, then enhancement parts should be dropped to protect the quality of the reconstructed signal. The lost cells can be recovered using a variety of methods. Four cell recovery methods are covered below [20][34]: substitution, sample interpolation, speech energy detection threshold, and embedded coding with LSB-dropping. These four methods involve separating the cells into important parts (those that should always be delivered) and enhancement parts (those that can be discarded during congestion).

13 substitution: Missing waveform is replaced by all 0 or some previous waveform. Priority can be based on an even or odd sequence number. Even sequence numbered cells can be made more important than odd numbered cells (or vice versa) to avoid situations where large segments of the signal are missing. The disadvantage of this scheme is that in low bit rate coding, one cell may contain information corresponding to a large segment of real time such that cell loss can result in long periods of loss in real time. Large segments of loss in real time may degrade the quality of service. sample interpolation: In sample interpolation, the missing waveform can be interpolated from previous and later waveforms rather than just replacing with 0 or a previous waveform. An even/odd priority can be used to avoid large sections of missing waveform. This is also poor in low bit rate coding. speech energy detection thresholds: During periods of high energy (talkspurts), samples can be classied as high priority cells. During periods of medium energy (semi-silence), samples can be classied as low priority. Finally, no cells are generated during periods of low energy (silence). embedded coding with LSB-dropping: Samples are partitioned into some number of more significant bits and less signicant bits. During periods of congestion, cells containing the less signicant part (LSP) or less signicant bits (LSB) can be dropped while cells containing more signicant parts (MSP) should never be dropped. Embedded coding with LSB-dropping is the method found best suited for ATM by [34][35] in subjective tests and in analyses of signal-to-noise ratios [35]. It has been found superior to using speech energy detection thresholds in both analysis of cell delay and loss and in subjective tests [20]. In a subjective test of 12-bit linearly quantized PCM, [20] showed tolerable loss for speech energy detection thresholds to be 8% while sample interpolation with even/odd coding could tolerate a loss of 10%. In the same test, embedded coding with LSB-dropping could tolerate losses of 15% for 6-bit LSB and 20% for 3-bit LSB. Two advantages of embedded coding with LSB-dropping are that there is no mistracking in time and that the degradation in quality is natural and smooth. Mistracking refers to a sequential loss of cells such that the amount of time of the waveform lost is unknown. If MSP cells are never dropped, mistracking is not possible since some part of the waveform information will always arrive. The signal quality of embedded coding with LSB-dropping also degraded

14 gracefully for increasing cell loss compared to other schemes. Tests in [34][35] showed that embedded coding with LSB-dropping can produce acceptable quality of reconstructed voice for a missing cell rate up to 4% for 64 kb/s PCM and 32 kb/s embedded adaptive dierential PCM. Others have suggested that losses can be as high as 15% [20]. The acceptable loss rates for embedded coding with LSB-dropping is generally twice that of other schemes. Similar results favoring LSB-dropping have been obtained for video [36] although sample interpolation should still be considered in real-time video 2. In addition to handling cell losses in voice and video with embedded coding with LSBdropping, variable bit rate coding (VBR) using energy detection thresholds can be used to reduce the amount of trac generated. Talkspurts in voice are constructed with the maximum bit rate, and silent periods are sampled at a lower bit rate. Cells may still be generated during silent periods to adequately reproduce background noise and to maintain continuity. Subjective tests in [11] indicate that even during periods of high cell loss (on the order of 10%) variable bit rate coding provided an unnoticeable degradation in reconstructed voice quality. In summary, [11] concluded that: variable bit rate coding using energy thresholds (talkspurts, semi-silence, silence) allows for an acceptable degradation in quality even when cell loss is high ( 10%), silent periods can be coded at a very low rate without signicant degradation: 16 kb/s with 2 bit MSP coding only is sucient for silent periods, even with background noise, semi-silent intervals can be coded at 32 kb/s with 2 bit MSP and 2 bit LSP, and talkspurts should be coded at 48 kb/s with 3 bit MSP and 3 bit LSP. Priority construction of voice and video is one method to oset the eects of loss. Another problem is caused by delay variance or delay jitter. Cells may arrive at the destination within specied delay times but because the network delays may vary, immediate playback of voice cells can result in a \jittery" output. We can reduce the eects of delay jitter by intentionally adding delays at reconstruction, namely, by delaying the playback. Delaying the playback of the rst cell of a talkspurt allows some exibility in the arrival times of following cells, 2 Line block replacement is one method of sample interpolation. This is the process in video where a line is replaced by a previous line. This may appear annoying in still pictures but it is insignicant in moving pictures. The chances of severe picture quality degradation is greatly reduced. See [38]

15 up to a reasonable limit. There are three basic methods of introducing delays in voice and video reconstruction [18][39][40]. See Figure 6. In the rst, null timing information, D R, the playback delay, is constant. The network transit time, D N, is unknown, thus the total delay time D T = D N + D R is unknown. Time stamps in the cells are not used. In the second scheme, complete timing information, D R is varied to keep D N constant. This requires a time stamp for the cells and update of time stamps at the intermediate nodes. In the third, incomplete timing information, because measurement of the network transit time is dicult to measure, the network transit time is estimated, a variable D R is added, and an eort is made to maintain D T constant. Time stamps are used but are not updated at intermediate nodes. By adding delays at voice reconstruction before playback, the probability of receiving packets before playback deadline increases, but at the expense of longer total delay. The public telephone system has a maximum tolerable reconstruction delay of 600 msec. It has been proposed by many that the delay should be between 100 and 600 msec for ATM. The packetization delay for voice cells is 4 to 8 msec for 32 to 64 octets; the depacketization delay is about 1 msec [2]. 4.2 Priority scheduling In this subsection, priority scheduling schemes are discussed. A xed, or head-of-line (HOL), priority scheme is a simple scheme to serve multiple classes with various delay requirements. The trac is classied into k xed priorities. The input buer is divided into k queues, and an arriving cell is placed in its corresponding queue. As long as the class 1 (highest priority) queue is not empty, cells in the class 1 queue are served. When the class 1 queue becomes empty, then class 2 cells can be served. When both the class 1 and class 2 queues become empty, then class 3 cells can be served and so forth. This method has been proposed to handle CBO trac [44]. It is advantageous for CBO since it will always have service priority. However, performance for lower priority classes is poor. The delay for the lower classes may become untolerably large if there is a large volume of of high priority trac. A exible priority scheme solves the problem of giving too much priority to one class. The basic idea is that cells in lower priorities should also have some chance to transmit even if there are higher priority cells in queue. Thus, lower priority cells that have waited a long time can preempt higher priority cells in service order. This will put some bound on the maximum delay which lower priority cells will encounter. Flexible priority disciplines have been shown in [46]

16 to minimize the weighted sum of the mean waiting times in an M/M/1 network. Head-of-line with priority jumps (HOL-PJ), proposed in [45], is an implementation of a exible priority scheme. In HOL-PJ, when a cell has spent a time in a queue greater than the local delay limit for that queue, it jumps to the next higher priority queue. Since clocking can be performed locally, HOL-PJ can be implemented without too much cost or complexity [43]. Like in HOL, class 2 packets can be serviced only if the class 1 queue is empty and so forth. However, in HOL-PJ, the queueing delay at a node is bounded since cells jump upward in priority after waiting assigned delay limits. By bounding the maximum queueing delays for each class, HOL-PJ equalizes the tail probabilities, the probability that a cell will wait longer than its delay limit, for all classes [45]. Implementation of HOL-PJ was also shown to be simple in [46]. 4.3 Priority discarding In this subsection, we will discuss how discarding based on the priorities of the embedded coding scheme described in section 4.1 can be used to prevent and tolerate periods of congestion. Normally, cells are accepted into the input buer until the buer becomes full. With multiple priorities, the push-out scheme can be used to decide which cells can be dropped when buer overow occurs. When buers become full, higher priority cells can \push out" lower priority cells. To maintain a minimal throughput of lower priority trac, push-out can be limited such that high priority cells can push out cells of class j only if there are more than N j cells of class j [42]. The total number of cells lost is the same whether the push-out scheme is used or not since the push-out scheme determines which cells are to be discarded, not how many. The push-out scheme gives nearly optimal performance but is dicult to implement. High priority cells must be able to discard a low priority cell at any location in the buer. This can be extremely dicult to implement. A practical alternative is to accept low priority cells in the buer only if the total occupancy of the buer is less than some threshold. This method also has been shown in [9] to give near optimal performance. In a previous section, we discussed marking for purposes of bandwidth enforcement. A similar marking scheme can be used in voice or video coding with high priority (unmarked) cells corresponding to the most signicant parts (MSP) and the low priority (marked) cells to the less signicant parts (LSP). By combining bandwidth enforcement priority and coding priority, loss can be tolerated. If the bandwidth enforcement scheme will require some cell to be marked, then the best way to determine which

17 cells are marked is to mark those cells which will have the least eect on service quality. In addition to discarding cells when buers overow, preemptive discarding can be used in conjunction with other priority schemes such as HOL-PJ to reduce trac. Preemptive discarding is based on knowing in advance that cells may eventually be discarded. The cells that are likely to be discarded, particularly marked or low priority cells, can be discarded before more network resources are invested in them. Preemptive discarding not only relieves congestion at the node where cells are discarded but alleviates other nodes of unnecessary trac. There are four schemes which can be used to determine when a cell might be preemptively discarded. These four schemes are [41]: Upon arrival to a queue, cells may be discarded if a check of load indicates congestion at the node. Cells may be discarded if the time spent at a node exceeds a local deadline. Cells may be discarded if the time spent at a node exceeds the end-to-end deadline. Cells may be discarded if the time spent in the system plus the node exceeds the end-toend deadline. Although a scheme using end-to-end deadlines is optimal in that cells are only discarded if their delivery to their destinations will be too late to be useful, because synchronization of clocks in ATM are near impossible, only the rst and the second method above may be practical. 5 Conclusion This paper covered some of the congestion control methods commonly considered to be suitable for an ATM network. We have discussed various issues such as admission control, bandwidth enforcement and rate control, voice coding and reconstruction, and priority schemes. Schemes that are most likely to succeed in ATM emphasize congestion prevention (such as call admittance, bandwidth policing, and rate control) over reactive congestion control based on feedback. A summary of the observations is presented below: The bit map vector approach of managing control information [22] is fast and ecient. If the network topology does not change often and the network is of manageable size, then this is a good approach to exchange network information.

18 Scout packets may be a practical as a means of call set-up [22]. However, scouts may mistakenly admit calls into the network if a large portion of the calls are inactive at the time scouts are sent. The performance of admission control using scouts needs to be investigated. The performance of this scheme should be compared to the performance of other common resource allocation schemes. The virtual leaky bucket with spacer and stop-and-go queueing can be combined to support bursty trac while maintaining some smoothness [9]. Cell marking can be used in congestion control, rate control, and in recovery of lost cells. The performance of marking in voice/video coding is shown to work but its performance in bandwidth policing is unknown [5] and should be investigated. Preemptive discarding, especially with embedded coding with LSP dropping via cell marking, can oset high cell loss rates of 5% to 15% for voice [20][34][35][41]. Variable bit rate coding can reduce trac without noticeably aecting voice quality [11]. Managing congestion in an ATM environment is a challenging problem. The high channel speed changes the focus of network design from bandwidth eciency to processing eciency. The large propagation delay-bandwidth product moves the focus from feedback control to a preventive control. New congestion control schemes are required for this environment. New network architectures for an ATM based B-ISDN were reviewed in this paper. The future of ATM architecture will require continued simplicity and preventative control as link speeds increase beyond the gigabit per second range. References [1] S.E. Minzer, \Broadband ISDN and asynchronous transfer mode," IEEE Commun. Mag., vol. 27, no. 9, pp , Sep [2] R. Handel, \Evolution of ISDN towards broadband ISDN," IEEE Network Magazine, vol. 3, no. 1, pp. 7-13, January [3] I. Toda, \Migration to broadband ISDN," IEEE Communications Magazine, vol. 28, no. 4, pp , April [4] I. Cidon and I.S. Gopal, \Control mechanisms for high speed networks," IEEE ICC 1990, pp

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