Adaptive Description of ATM Traffic Flows 1

Transcription

1 Adaptive Decription of ATM Traffic Flow 1 Juergen Rochol Mouriac Halen Diemer (juergen@inf.ufrg.br) (mouriac@univate.br) Univeridade Federal do Rio Grande do Sul - UFRGS Intituto de Informática - Departamento de Informática Aplicada CEP Av. Bento Gonçalve, 95 Porto Alegre RS Caixa Potal 1564 Abtract Today, the great challenge in broad band network, uch a ATM, i to upport application that need guaranteed QoS. Efficient reource allocation for connection that need guaranteed QoS i only poible if the application can provide a precie and reliable traffic decriptor that the network can undertand. Thi work preent a methodology to obtain the parameter of the traffic decriptor of an ATM application from an initial ample of the flow. Baed on real-time meaurement of the flow, we ugget periodic renegotiation of the parameter, every time they vary above or below their predefined limit. We apply thi method to a VBR MPEG video flow and demontrate it performance. Oberved reult are dicued and ome future ue of the methodology are uggeted. Keyword: ATM, traffic decriptor, traffic haping, traffic policing. I. INTRODUCTION Modern broad band application typically require variable band width and pecific performance requirement. ATM technology allow the implementation of a network capable of upporting the QoS requirement of uch application, a long a the application provide the network with a flow of cell within negotiated UPC (uer parameter control) parameter. Thi et of UPC parameter i part of the application traffic decriptor, which mut be able to capture the main tatitical characteritic of the flow. Thi i the only way a network can allocate the required reource to meet uch application QoS requirement. However, the application often ha no mean to provide precie information about it flow behavior, which force the network to adopt QoS tandard baed olely on the application ervice category, which not alway tranlate a an efficient allocation of network reource concerning band and buffer pace. In uch cae, a feaible alternative being propoed would be to try to ue an initial ample of the flow to infer a et of attempt-parameter and renegotiate them a ignificant deviation of thee parameter from the current flow occur. Figure 1 how a block diagram of the traffic model we are propoing and it main function block. The decription and control block acquire UPC parameter from an initial ample of the flow, which are then ent to the network by the ignaling block through ignaling protocol Q of ITU-T. The haping block monitor UPC parameter behavior tatitic and tart their renegotiation when they vary above or below predefined value. Uer environment Traffic characterization & UPC control Signaling Block New UPC Requet Accept/Reject ATM Acce Switch ATM Network ou rce Traffic Shaping VC Flow Policing UPC Fig. 1. Model for an adaptive traffic decription and traffic haping module for a VC flow in ATM 1 Thi work wa partially financed by FAPERGS Fundação de Amparo à Pequia do Rio Grande do Sul, Proceo n. 1/575.9

2 Thi work i organized a follow: ection 2 define a model for the adaptive haping of a flow aociated to a generic VBR virtual connection (VC) baed on UPC parameter obtained from the decription module. We outline the theoretical foundation of the method adopted to obtain UPC parameter and preent a implified, practical method, to obtain UPC parameter from a real flow ample. Section 3 preent imulation and experimental reult obtained when the method wa applied to an MPEG video flow. in ection 4 we preent a dicuion of the reult obtained and alo ome concluion and prognoe, forecating the ue of the method in ome pecific area, beide poible extenion to it. A. Adaptative Shaping of an ATM Flow The trategy that the ATM Forum adopted to decribe cell flow i baed on a decription on two time cale: (1.) decribing the behavior of hort-term burt, by uing parameter uch a peak rate (PCR) and it correponding jitter rate (CDVT), and (2.) decribing the flow long-term behavior, or the flow tatitical decription, in which the tatitical time interval correpond to the connection time. The parameter ued in thi cae are the tatitical cell rate (or utainable cell rate, SCR) and a tolerance regarding uch rate, which i, however, bound to the peak rate, and called burt tolerance (BT). CDVT i not exactly a ource-generated traffic-related parameter, but a network-engineering parameter, ince it account for the jitter entering the flow a it travel from the ource to entry in the network through the UNI interface. Burt tolerance BT i related to the maximum burt ize (MBS) and the average rate (SCR) and peak rate (PCR) through expreion (1) [2]. 1 1 BT = τ = ( MBS 1) (1) SCR PCR Characterizing, or decribing, variable bit rate (VBR) flow i a generic trategy, ince one can conider any flow in other ATM Forum ervice categorie to be particular cae of thi generic VBR flow. In order to police flow, ATM Forum [2] ha uggeted two equivalent verion of leaky bucket (LB), known a GCRA (Generic Cell Rate Algorithm). They are the continuou-tate leaky bucket and the virtual caling leaky bucket. A more detailed analyi of their operation and performance can be found in [3]. Leaky bucket (LB) i a imple count mechanim that can be ued for haping and policing traffic flow. Our analyi ue the leaky bucket model uggeted by Mark [4]. In thi model, leaky bucket operation i decribed by a fictitiou./d/1/b queue ytem erved at a contant µ rate and having buffer capacity B, decribed a a leaky bucket LB(µ, B), a hown in Figure 2a. Cell arrival l Leaky Bucket Virtual Queuing Sytem:./D/1/B Server Serving rate Cell arrival Buffer FIFO (./D/1) B Leaky Bucket Virtual Queuing Sytem:./D/1/B Ecalonamento B (bucket capacity) l Server m (PCR) (a) (b) Fig. 2. (a) Model for a Leaky Bucket LB(µ, B) and (b) Model for a Leaky Bucket Shaper (LBS) for PCR conformance. A leaky bucket, when ued to conform, or hape traffic, i alo parametered through (µ, B) and operate imilarly to a policing leaky bucket, except that non-conforming cell are not marked or dicarded, but rather delayed. The operation can be undertood in term of a./d/1 queue ytem of infinite capacity, a hown in Figure 2b. If, upon the arrival of a cell, the number of client on the fictitiou queue i B or more, thi cell i put on the infinite capacity buffer erved on a FIFO bai. Every time a client leave the fictitiou queue, a cell i ent from the FIFO buffer. Thi model i equivalent to the one known a Token Bucket, or leaky bucket with a memory or buffer [5], [6]. The Double Virtual Scaling Shaper (DVSS) on our approach ue two GCRA virtual caling algorithm one for PCR and another for SCR. DVSS operation i baed on the imultaneou uperviion of two parameter: conformed emiion time at the cell peak rate (CETP), and conformed emiion time at the cell utainable rate (CETS). Baed on thee parameter, the cell conformed emiion time (CET) can be defined to enure imultaneou conformity of the flow to CETp and CET a follow:

3 CET = max(cet-bt, CETp) The operation can be decribed a follow: upon the actual arrival ta time of a cell, it CET i determined. If CET ta, it i caled; otherwie it tay on buffer for later tranmiion. Figure 3 illutrate the operation of the algorithm. CET = max( CET S BT, CET P ) parameter update: CET P ta + I P e CET t + I S a S No CET ta ye Cell wa not cheduled Double Virtual Scaling Shaper (DVSS) (CET: Conforming Emiion Time) Cell wa cheduled ta Time arrival of a cell at: ta Buffer with infinit capacity erver µ B Fig. 3. Double Virtual Scaling Shaper (DVSS) conformant flow The haper enure that the peak rate doe not exceed λp, the long-term average rate doe not exceed λ and the maximum burt length (tranmitted at peak rate) doe not exceed: λ p B c = B (2) λ λ ( ) The value of Bc, in uch cae, can be eaily related to the MBS parameter of the connection traffic decriptor defined in (1). Conformance can be adapted in relation to the tatitical variation of thi flow, by oberving it behavior at predefined time interval and by regularly renegotiating the new ample-inferred parameter with the network. B. Approximate Statitical Decription Here follow an extenion of the methodology of Mark et al. [4] that allow it direct application on ample of generic VBR flow to obtain tatitical parameter that are then mapped into UPC parameter in order to hape thi flow. The proce of approximate tatitical decription, Ĉ, i baed on the behavior of a pool of leaky bucket haper, each one of them decribed by traffic parameter that have been etimated from an initial flow ample. Auming that the pool of haper i modeled according to a queue ytem et and that the cell flow of the ample one wihe to decribe i applied to all haper of thi pool. Moreover, each haper ha a eparate and contant ervice rate equal to µi. The value of µi mut be in the range λm <µ i <λ p, where λ p and λ m are, repectively, the peak rate and the average rate of the flow ample. In practical term, the peak rate and average rate value can be obtained from a direct real-time aement of the flow ample. Beide that, auming that W repreent the average waiting time of any given cell in thi queue ytem, when the latter i balanced, uing the function of probability ditribution of the complementary waiting time a it approximate exponential form [7], the probability that the waiting time of a buffered cell be greater than a given time t i expreed a: b( µ )t P(W > t ) a( µ )e (3) In that expreion, a and b depend on µ. If t i meaured in econd, then the dimenion of b i an invere of econd. Given relatively weak hypothee of the arrival proce nature, exponential form (3) ha an aymptotic curve for very large t, i.e., e bt P(W > t ) a (for t ). Mark and Ramamurthy [4] how that p

4 thi particular aymptotic curve i true for a rather general cla of arrival procee with Markovian tructure. 1 They alo how that the weaker aymptotic form - t log P( W > t ) b (for t ) -, i valid under much more generic condition, i.e., it dipene with the Markovian uppoition of ditribution of cell arrival. However, approximation (3) i exact in the cae of ON/OFF Markovian flow ource. For relatively mall to moderate ize buffer, one obtain ufficiently precie reult for a great variety of clae of Markovian model, including elf-imilar traffic model [8]. Parameter a(µ ) and b(µ ) offer a tatitical decription of the flow a they decribe the effect of the cell flow when applied to a queue with contant ervice rate µ. A more complete decription of the cell flow can be obtained by relating a(µ ) and b(µ ) with µ value in interval (λm, λp) a follow: Ĉ = [λp; λm; (a(µ), b(µ)) where λm < µ < λp,] (4) Value for a(µ) and b(µ) can be choen in a way that approximation (3) i true for t value within the interval of interet. Auming that expreion (3) i an equality, with bai on [1] one can ay that: a( µ ) E[ Q ] = E[ W ] = τ µ [ ] a r ( )E S a +, (5) b( µ ) µ Where Sa repreent the number of ervice cell ( S a {,1 }), Qa repreent the number of queued cell and τr(µ ) repreent the average ervice time left for the ervice cell (a long a there i a ervicing cell). From expreion (3), a(µ ) can be calculated auming that: P(W>) = a(µ) = E[Sa] (6) By defining E[Qa]=q(µ) and olving for b(µ ), one ha: aµ b( µ ) = (7) a µτ q In order to complete UPC parametrization of the flow, it i alo neceary to obtain the parameter of minimum capacity B of the leaky bucket a a function of the flowing rate µ, where λm < µ < λp. Flowing rate µ of the bucket can be defined a a function of a given conformance probability ε or, when more convenient, a a function of a given probability of delay the flow can tolerate. In [1], it i hown that the minimum ize of the bucket in uch cae can be calculated a: µ a( µ ) B( Ĉ, µ, ε ) = log (8) b( µ ) ε Intead of obtaining the minimum bucket capacity a a function of a conformance probability, capacity B can be dimenioned according to delay criterion D. If the application tolerate ome degree of delay in relation to it flow, it may be more convenient to pecify the limit of flow conformance a a function of thi delay. Once again, [1] how that in uch cae the minimum ize of the bucket can be calculated a: µ a( ) B( Ĉ,, D ) log µ S µ = + 1 (9) b( µ ) b( )D µ r + II. A PRACTICAL METHOD TO OBTAIN UPC PARAMETERS What follow i a practical way for real-time etimation the UPC parameter of a flow, from an empirical methodology uggeted in [4]. Parameter etimation i baed on oberving a ample of thi flow for a time interval T and the method follow five phae: a. Etimating average and peak rate from a flow ample. b. Chooing a et of value that may be the utainable rate. c. Obtaining the approximate tatitical decription of the flow ( Ĉ ). d. Calculating a minimum bucket ize for each poible value, enough to meet the demand of delay or uer haping probability. e. Obtaining utainable rate λ and bucket capacity B, and mapping UPC traffic parameter of the flow.

5 a. Etimating average and peak rate from a flow ample Conidering the etimated average rate ˆλ and the etimated peak rate m ˆλ p on a ampling window T, the typical value of T for video ervice, according to Knightly [11], can be from two to four econd. A given interval T i ubdivided into M ubinterval of fixed length t, o that t = T/M. In cae of ON/OFF traffic, for intance, t can be the um of the ON interval and the OFF interval (t = ton + toff). A for MPEG traffic, one can ue t a the duration of each frame, i.e., t = 33m and thu M 1. Suppoing that a total A cell are iued during a T time interval, the etimated average rate will then be ˆλ m = A/T. The peak rate, on it turn, when unknown beforehand, can be etimated from ˆλ = max{ni/t}, where 1 i M, ni correponding to the number of cell emitted on the i-th t time interval. p b. Chooing a et of value that may be the utainable rate A et of poible µ value that may be the etimated utainable rate ˆλ, equally paced on interval (λm, λp), written a: µ1, µ2,... µn, where the number N of poible value mut be a commitment between how cloe one wihe to get to ˆλ and the neceary proceing time to obtain it. Auming that time i normalized in relation to the time of cell tranmiion through the link level, one mut chooe the increment between two ubequent rate value a an integer, i.e., µ 1 = = 1, 2, 3,... i + µ i c. Obtaining the approximate tatitical decription of the flow For the etimated tatitical decription Ĉ, it i conidered that, for each of the N poible rate µ i (i = 1, 2,...N), a leaky bucket Xi - which i incremented by one for each arriving cell and decremented at a contant rate µi. For each rate µi, the etimated value of parameter â( µ i ) and bˆ( µ i ) are obtained a follow: each fictitiou queue i ampled at the moment an arbitrary cell arrive, ampling i done by kipping a random Xj number of cell between moment j-1 and moment j of ampled arrival. Since all N queue are hown at the ame time, only one random number i needed for all queue at the moment of ampling, thu reducing the proceing time of the algorithm. During interval T, M ampling are collected on the N queue. On any given j ampling, the following queue value will be oberved: Sj: number of client attended (Sj {,1}) Qj: number of client on queue Tj: ervice time left for the client being attended (if thi i the cae) One can then obtain the following approximate mean value: M M M â = S j, qˆ = Q j and τ ˆ r = Tj (1) M M â.m 2µ j= 1 j= 1 Auming that the average attending time of a cell in ervice can be neared to τ r 1 2µ and the value of b can be obtained by expreion (7): â. µ âµ bˆ = (11) µ.ˆ τ.â + qˆ â 2 qˆ r + The tatitical decription i a follow: Ĉ = [ λ ˆ ; λˆ ;(â( µ ),bˆ( µ )), i 1,..., N] (12) p m i i = d. Determining bucket capacity Once the approximate tatitical decription j= 1 Ĉ of the flow ha been obtained, one can determine the capacity of bucket B( Ĉ,µ,ε) for each µ rate a a function of a conformance probability ε according to relation (8). If the flow allow for a little large conformance delay, the bucket minimum capacity can be determined a a function of a given delay limit D intended, through expreion (9). e. Obtaining the utainable rate Mapping UPC parameter of the flow from the approximate tatitical decription Ĉ can be done in two way: by impoing a delay limitation, or by impoing a conformance probability. The current analyi ued

6 the latter becaue it i more practical concerning traffic flow. Thu, the et of traffic decriptor acceptable for the flow can be written a: D : [ λ ˆ, µ,b (Ĉ,,D] where i = 1,...,N T p i µ i In order to chooe the mot adequate traffic decriptor, the option i for the one with the mallet effective band aociated. To do o, an expreion adapted from [9] wa ued, which expree the effective band of a flow a a function of the parameter of it traffic decriptor. For an ON/OFF flow, the effective band can be expreed a: λ( λp λ )B beff( λ, λp,b ) = λ + K (13) λ The effective band aociated to a UPC-controlled flow equal rate λ plu a term that take into account the burtne aociated to uch flow. The value of contant K, in thi expreion, depend on the characteritic of the ATM multiplexer and the burtne of the flow and can be determined, according to [4], by the expreion: log( 1 ε mux ) K = (14) 2kB In thi expreion, εmux i the probability of lo of MUX cell, k i a coefficient related to the burtne of the flow and Bmux i the capacity of the MUX buffer. According to experiment reult in [4], the value of K for CBR-type flow i near zero, wherea for ON/OFF flow, which can be rather exploive, it can be near one. It wa conidered that K had an intermediary value (K,1), aiming at keeping the generality intended for the method. Parameter i i choen by minimizing the following expreion of effective band aociated to flow:.1µ i ( λp µ i )B b = + eff min min λ p, µ i (1 i N) (15) λp The value of î within the N poible value of i wa called minimum effective band, which minimize the previou expreion. The parameter of the traffic decriptor λ,,b ), aociated to the conidered flow, can then be approximated a: ˆλ λ p = p µ î mux p ( λ p λ = e B = B ( Cˆ, λ, D ) (16) It can be noticed that if the etimated value of the peak and average rate are too cloe, i.e., CBR flow, then it i true that: λ p = ˆλ p, λ = ˆλ p e B = 1 (17) III. SIMULATION AND EXPERIMENTAL RESULTS In order to ae the performance of the practical method in obtaining UPC parameter, an application wa ought that were a cloe a poible to real-time proceing, which mean that the UPC parameter mut be inferred from a mall initial ample (duration of a few econd) becaue uch time may be the fixed delay to be introduced on the flow. The practical method wa applied to a flow of real video compreed according to the MPEG tandard [12]. Under thi tandard, the video i tranmitted according to a equence of frame of varied ize. When tranmitting uch flow on an ATM network, each frame i egmented into cell. Cell are tranmitted at a contant rate λp at the beginning of a frame interval until the frame ha been tranmitted. The ource then ilence until the beginning of a new frame interval, which reult in a VBR ON/OFF flow with alternate ON and OFF period. On MPEG coding, there are three type of frame: frame I (Intracoded frame), frame P (Predicted-coded frame) and frame B (Bidirectional-coded frame). Frame I follow codification called intraframe and contain the complete information of a cene, wherea frame P and B, or interframe, codify only a prediction of movement baed on other frame. In general, the ize of thee frame have the relation I > P > B. The repetition equence of different frame i fixed and periodical, determined through Group of Picture (GOP). The GOP equence i characterized by two parameter, N and M, which define the ditance between I frame and P frame, repectively. Our evaluation ued the firt 1,2 frame of the firt cene of MPEG video Star War, which

7 preent a fixed frame rate of 3 fp, which correpond to a frame interval of 33m. Figure 4 how a graph of the variation of the ize of frame in thi equence, whoe approximate duration i 4. Thi equence wa divided into 1 egment, called ample, each with 12 frame and approximate duration of 4. Sample-1 i the name given to the frame correponding to the firt 4, ample-2 are the ubequent four, and o on. Figure 5 how the graph of the 12 frame that make up ample cell frame Fig. 4. Size of frame of the firt 4 of Star War video cell frame Fig. 5. Size of frame of ample-1 of Star War MPEG video. The firt 12 frame of the Star War equence (ample-1) preent a frame with maximum ize of 117 cell, a frame with minimum ize of 4 cell and an average ize of cell/frame. Auming a link acce of Mbit/, the cell inertion time (or timelot-t) i 2.75 µ. For implicity reaon, time in our analyi ha been normalized in relation to thi unit. For ample-1, the peak rate wa etimated a λ p = 9,75 1^-3, and the average rate a λ m = 1,53 1^-3, in cell unit per time-lot. For further implification, the invere of the rate wa conidered, i.e., a minimum interval between cell of tp = 1/λ p 13 t and an average interval between cell of tm = 1/λm 648 t. Baed on thee value, the initial value of 13t wa conidered, a well a 91 fixed increment of 6t to the final value of 648t. Thu, 92 intermediary rate were conidered between the minimum and maximum rate, which correpond to a pool of 92 leaky bucket, each of which with a different µi ervice rate, all ubmitted to the flow of ample-1. Simulation wa ued to obtain, on the j-th timelot, for each leaky bucket, Sj value, cell in ervice (or not), and Qj, number of queued cell waiting to be attended. The etimated value of parameter a, q, and b were then calculated through expreion (1) and (11). The other decribing parameter of ample-1 were calculated next, from thi et of baic value. Figure 6, 7 and 8 repectively preent the graph of parameter a, b and q, obtained from the imulation of a pool of 92 leaky bucket haper, each one aociated to one of the different µi ervice rate conidered (i = 1, 2,..., 92), and ubmitted to the flow of ample-1.

8 1,8 ample-1m (modified) ample-1 "a" parameter,6,4, rate Fig. 6. Variation of parameter a for ample-1 and ample-1m. 8 average bucket ocupancy ("q") ample-1 ample-1m (modified) rate Fig. 7. Variation of parameter q for ample-1 and ample-1m. It can be noticed on figure 6 that the average value of parameter a, correponding to the average value of cell in ervice on the leaky bucket for a given cell, decreae a the rate increae. Likewie, the average number of q queued cell waiting to be attended, for a given rate, repreent a ignificant increae a the ervice rate at the bucket exit decreae (Figure 7). A for parameter b (Figure 8), aociated to the invere of the average delay that cell undergo in the haper, it increae a the rate increae, i.e., delay decreae ignificantly with a rate increae.,4 "b" parameter,3,2 ample-1m (modified) ample-1, rate Fig. 8. Variation of parameter b for ample-1.

9 In order to how that parameter a and q capture flow variability, which can be meaured by CoV 2 (coefficient of variation) and tandard deviation σ of ample-1, the method wa applied to a modified flow of ample-1 called ample-1m. Thi modification conited of conidering, for all value of frame I, P and B of ample-1, their mean value, wherea keeping the ame limit for the conidered rate. Therefore, a ample wa obtained with the ame burtne factor (Fr), but lower σ and CoV in relation to ample-1. It can be noted on Figure 6 that ample-1m feature a greater a average value, wherea q i maller, epecially the lower rate. The behavior of both curve can be explained by the maller variability of ample-1m, tranlated a maller σ and CoV value. The graph on Figure 9 repreent the minimum bucket ize a a function of three different conformance probabilitie. One can notice that the bucket ize i greater with reduced rate for a given conformance probability. Likewie, the maller the probability of conformance, the greater the requirement for buffer ize. Figure 1 preent the etimated capacity of the bucket a a function of the limit of average delay (D). A conforming probability ε =,1 and a bucket capacity Bi were conidered. It i noticeable that the limit i characterized by and decreae rapidly with an increaed rate. 35 minimum bucket ize: B(e) e =,1 e =,1 e =, rate Fig. 9. Minimum bucket ize (B) a a function of conforming probability ε bucket ize: B 15 1 D=43,63m D=4,363m D=,436m rate Fig.1. Bucket ize for a given limit of average delay (D). 2 Coefficient of Variation i defined a: CoV = σx/e[x]

10 effective band-width (beff),8,7,6,5,4,3,2,1 B(e=,1) B(e=,1) B(e=,1) rate Fig. 11. Variation of effective band (beff) for different conforming probabilitie. Figure 11 preent the effective band aociated to each rate conidered. A factor K=.1 wa adopted, baed on [7], a typical Bmux of 4, a lo probability εmux of 1^-6 and k=cov of,6. The curve ha an inflection point, correponding to a minimum effective band of 3,776 x1^-3 cel/t which, on it turn, correpond to a minimum bucket capacity B=121cell (for a conforming probability ε =,1), and a tatitical rate λ of 1,912 x1^-3 cel/t. The maximum burt length (BT) that can be tranmitted at peak rate λp, i 144 cell. The etimated value of UPC parameter for ample-1, with conforming probability ε =,1, are then: λ = 1,912 x1^-3 cel/t, λ p=9,55x1^-3 cel/t, B=121 cell and BT=144 cell. The other conecutive ample of the Star War video were analyzed under identical procedure. Figure 12 how a graph of the approximate variation of parameter λp and λ, of the ten ample along the given 4-econd Star War flow. It can be noticed that each parameter of the traffic decriptor approximately follow the flow variation, a can be een on Figure 4. Figure 13 preent the variation of the bucket capacity (B) and the burt tolerance obtained for the ten conidered ample. Again, there i a clear notion of how thee parameter are directly related to flow progre, by comparing Figure 12 and 4. In order to validate the practical method to obtain UPC parameter, a Double Virtual Scaling Shaper (DVSS) wa imulated. Next, flow of each ample were applied to the Shaper, configured with the repective UPC parameter obtained with the practical methodology.. rate [cell/t],3,2, ample maximum cell rate (4) minimum cell rate (4) peak cell rate tatitical cell rate Fig. 12. Variation of peak rate (λ p) and tatitical rate (λ ) in relation to the 4-flow of MPEG video, Star War.

11 15 1 cell 5 maximum burt ize BT bucket capacity (B) ample Fig. 13. Variation of bucket capacity (B) and burt tolerance (BT) oberved throughout then ten ample conidered. The following parameter were oberved in each imulation for each flow egment: the average and maximum number of cell on the haper buffer and the number of buffer overflow (cell lo). From a total cell on the ten given ample, at no time did the buffer overflow. It ha been concluded that the practical method uggeted for haping real-time flow i valid and can be ued to etimate approximate UPC parameter on any kind of VBR flow, within the ampling time interval ( 4) in which ample were conidered. Thu, conidering the dynamic renegotiation of UPC parameter of the virtual connection (VC) from ucceive egment of traffic flow, one can obtain a dynamic adaptation of the UPC mechanim and, therefore, the actual effective connection band, while it i on. IV. CONCLUSIONS AND FUTURE DEVELOPMENTS Many ATM traffic flow either have no condition to or are not concerned with upplying a reliable decription of the tatitical behavior of the flow they generate. It i fundamental that the application offer a precie and reliable traffic decriptor for the network to enure application-required QoS. Thi paper ugget a practical method to decribe an ATM flow, baed on an initial ampling of thi flow, and the traffic parameter thu obtained can be renegotiated with the network whenever there i ignificant deviation along connection time. The model provide for flow haping through a double leaky bucket haper, which ue the UPC parameter obtained from the initial ample. Significant deviation of uch parameter from current flow trigger a renegotiation with the network for more appropriate parameter, which make the haping proce adaptive. The adaptive real-time decription and haping of a traffic flow from the uggeted practical method can be applied, in principle, to any ervice category. It mut be noted, however, that thi method will introduce a fixed delay that the application mut tolerate. Thi delay i baically caued by three factor: proceing time of the characterization algorithm, ampling time and renegotiation time of new UPC parameter with the network. Since thee three procee, which characterize thee time component, are run imultaneouly, the fixed delay will be eentially defined by the longet procedure. An examination of each component, which follow, allow for an etimate of the delay to be introduced. The algorithm runtime during imulation wa around four econd. Thi relatively long time i due to the fact that no pecial care wa taken to program them in order to optimize proceing time. We believe that pecial programming care will ignificantly reduce uch time with little effort. The flow ampling time conflict with the algorithm proceing time, becaue ideally the longer the ampling time, the more reliably the flow will be decribed, although the fixed delay will be the longer. We undertand that thee two time meaurement are committed to each other for the definition of the fixed delay to be inerted in the flow. The renegotiation of new UPC parameter with the network, on it turn, i run at the ATM ignaling level, therefore there i no lo at the uer data level. With new ATM ignaling protocol, uch a Q of ITU-T [1], the renegotiation time for a connection can be a few ten of milliecond. A for the way thi renegotiation i carried out, it can be in two way: regular renegotiation of UPC

12 parameter from flow egment of a fixed ize, or dynamic renegotiation only run if there i a variation of UPC parameter below or above predefined limit. In both cae, the reult will be an adaptive haping of flow to an actual effective band that varie along time. The ue of either kind of renegotiation (dynamic or periodical) mut be decided with bai on characteritic uch a flow variability and burtne. A for the application of the methodology propoed, motly it ue of MPEG video flow wa explored. Thu, video ervice uch a tored video, video on demand (VoD) and multicat video may benefit from the technology. For better ue of the potential behind thi mechanim of adaptive optimization of the link, it i important to extend application of the algorithm to other kind of ource, uch a ON-OFF flow, auming ON and OFF period over random ditribution. If we conider not too long ampling time 3, the long term relation that are oberved on mot current network application [9] can be atifactorily modeled according to an exponential ervice rate ditribution beide a few predefined tatitical parameter (ervice category, burtne, etc.) [13]. REFERENCES [1] REININGER, D..; RAYCHAUDHURi, D.; OTT, M. A dynamic Quality of Service Framework for Video in Broadband Network, IEEE Network, November/December, v.12, n.6, p [2] ATM FORUM/TM. Traffic Management Specification Verion 4.1, af-tm-121., March Available on the Web. <URL: >. [3] DIAZ, J. C.; PLAZA, P.; CRESPO, J. ATM Traffic Shaper: ATS. In: DATE, Proceeding...[S. l. :. n.], 1998 [4] MARK, B. L.; RAMAMURTHY, G. Real-Time Etimation and Dynamic Renegotiation of UPC Parameter for Arbitrary Traffic Source in ATM Network. IEEE/ACM Tranaction on Networking, New York, v. 6, n. 6, p , Dec [5] MONTEIRO, J. A. S. Rede Digital de Serviço Integrado de Faixa Larga (RDSI-FL). Publihed by: Silvio Lemo Meira em, IX Ecola de Computação, Recife, July, 26p, [6] SIDI, M. et al. Congetion Control Through Input Rate Regulation, IEEE Tranaction on Communication, New York, v. 41, n. 3, p , Mar [7] STALLINGS, W. A Practical Guide to Queuing Analyi. BYTE, Peterborough, N. H., p , Feb [8] HEYMAN, D. P.; LAKSHMAN, T. V. Source Model for VBR Broadcat-Video Traffic. IEEE/ACM Tranaction on Networking, New York, v. 4, n. 1, p. 4-48, Feb. 1996, [9] ECKBERG, A. E. Approximation for burty and mooted arrival delay baed on generalized peakedne. In: INT. TELETRAFFIC CONGRESS, 11., Proceeding... Kyoto: [. n.], p [1] ROCHOL, J. Caracterização e Conformação de Fluxo de Tráfego ATM no Ambiente do Uuário, Doctor dieration, Programa de Pó-Graduação do Intituto de Informática da UFRGS, December 2, p.2. [11] KNIGHTLY, E.; ZHANG, H. Traffic Characterization and Switch Utilization uing a Determinitic Bounding Interval Dependent Traffic Model. Berkley: ICSI and EECS Department, U. C., p. (Technical Report TR-94-47) Available at: <ftp://ftp.ici.berkeley.edu/pub/techreport/1994/tr p.gz>. A acceed on: 17 October 2. [12] GALL, D. L. MPEG: A video compreion tandard for multimedia application. Communication of the ACM, New York, v. 4, n. 34, p , Apr [13] ABATE, J. et al. Aymptotic for teady-tate tail probabilitie in tructured Markov queuing model. Stochatic Model, v. 1, p , The Time (t) wa conidered i the time of the average connection duration (Tm). The condition t<<tm mut be atified.