Bandwidth Allocation and Session Scheduling using SIP

Transcription

1 JOURAL OF COUICAIS, VOL., O. 5, AUGUS Bandwidth Alloation and Session Sheduling using SIP Hassan HASSA, Jean-arie GARCIA and Olivier BRU LAAS-CRS, oulouse, Frane {hhassan}@laas.fr Abstrat Session Initiation Protool (SIP) is a new signaling protool designed to establish multimedia sessions in teleommuniation networks. In this paper, we suggest the extension of SIP funtionalities to oordinate QoS mehanisms deployed in IP networks, and espeially in DiffServ domain. Indeed, the interation between small and big CP sessions may have dramati onsuenes on small CP sessions. Hene, we use SIP to ahieve QoS management on a session basis, in whih the over all ativity of the user during the session is onsidered. he suggested mehanisms deal with two issues: fit, session sheduling based on session duration and/or volume, and seond bandwidth alloation on a per-flow basis using uivalent bandwidth estimation tehniques. he proposed mehanisms are implemented in the SIP proxy server as QoS management algorithms, and they are validated by simulations. Index erms SIP, DiffServ, Web, QoS, Bandwidth alloation, Sheduling. I. IRODUCI he evolution of teleommuniation networks made of the Internet a univeal platform to support most forms of modern ommuniations inluding voie, video and data appliations. However, the Internet Protool (IP) was developed based on a onnetionless model where simple metris (e.g. delay or hope ount) are used to ahieve routing. he simple onept of IP is behind its suess and its ability to sale to very large networks. Unfortunately, no Quality of Servie (QoS) was planned with this approah. Over yea, many enhanements to QoS support were implemented in IP paket networks. Hene, two QoS arhitetures DiffServ and IntServ were introdued to arry out appliation QoS ruirements. oreover, new protools suh as PLS were oneived to extend the best-effort servie of IP networks. Besides, the onvergene to all-ip network ame with new signaling protools to handle user sessions in all aess networks regardless their partiularities. hus, the Session Initiation Protool (SIP) was proposed as a signaling protool to establish and release sessions between end use. SIP is very general and an be used for any kind of sessions in all ommuniation networks. oreover in the year 000, SIP was seleted by the hird Generation Partnehip Projet (3GPP) as the all ontrol protool for the 3G IP-based mobile networks. On the other hand, the suessful deployment of ulti-label Swithing Protool PLS in DiffServ networks delegates label swithing as an apt swithing tehnology for the future ore networks espeially for its raffi Engineering (E) apabilities. Indeed, ombining both tehnologies introdues a new vision of QoS management at the appliation level. he autonomous struture of SIP makes it possible to manage user sessions as lassi phone alls, from the beginning to the end. However, SIP an ahieve muh more than signaling the beginning and the end of a ommuniation session. In partiular, it an host traffi engineering intelligene. hus, the use of SIP over DiffServ networks allows flexible QoS management as it ombines DiffServ failities with SIP supervision. In this paper, we propose a QoS management framework based on SIP over DiffServ environment. Where QoS management mehanisms are implemented and supervised by the SIP proxy server. he proposed mehanisms onerns: fit, session sheduling based on session duration and/or session data volume exhanged during a session and seond, bandwidth alloation on a per-flow basis using uivalent bandwidth estimation tehniques. he paper is organized as follows: fit, we give a brief overview of SIP and its assoiated Session Desription Protool (SDP), and then we explain the suggested SIP over DiffServ arhiteture. Seond, we present uivalent bandwidth estimation tehniques used for bandwidth alloation. Finally, we present the session based QoS algorithms implemented along with simulation results. II. SESSI IIIAI PROOCOL Session Initiation Protool is an appliation layer ontrol protool designed and developed by the IEF [4]. he speifiation is available in form of several RFCs, the most important one is RFC36 [5] whih ontains the ore protool speifiation. he easy implementation, flexibility and good salability are the main motivations onsidered while designing this protool. he main task of the protool is to set up and release sessions between end use. he session refe to the ativity between sender and reeiver when the whole state is maintained during the ommuniation. Classi sessions inlude Internet telephone alls, but it may also 006 ACADEY PUBLISHER

2 8 JOURAL OF COUICAIS, VOL., O. 5, AUGUS 006 be multimedia onferene session, Web session, distributed omputer game session, et. he ommuniation itself between devies is ahieved by other protools (often RP, RCP and SDP) as the purpose of SIP is to initiate ommuniations only. Real ime Protool RP arries the real-time appliation data (inluding audio and video) by splitting and enoding data into pakets to allow per-paket transport on the Internet, and SDP desribes and enodes apabilities of sessions. Indeed, the harateristis of the session are negotiated between partiipants. he negotiation inludes the type of odes used to enode media in order to failitate deoding proess, maximum allowed bit rates, the transport protool, et. he end-to-end model of SIP omplies with the Internet arhiteture. Indeed, all the intelligene is stored in end devies, inluding state. his protets from single point failure while preserving salability in networks. In ontrast with Publi Swithed elephone etwork (PS) where state and intelligene are stored in the network while terminals are dump. However, SIP an provide the same funtionality as PS with the possibility to implement end-to-end servies that are hardly onfigured in PS. Finally, it is lear that the salability and deentralization of SIP ome at the ost of end-to-end message overhead. In fat, SIP is based on HP protool whih is widely used on the Web. Atually, HP an be seen as a signaling protool also, as web browse tell HP serve about the douments they need. he enoding of message heade in both protools (HP and SIP) have been inherited from RFC8 [6]. his enoding has already showed robustness and flexibility with HP. he physial elements of a SIP network fall into two ategories: lients and serve. Fig., illustrates the arhiteture of a SIP network. forward SIP messages to other SIP serve in the network. Proxy server an play several roles. Besides, it provide funtions suh as authentiation, authorization, network aess ontrol, routing, reliable ruest retransmission, and seurity. Rediret server: It takes are of direting the lient to the next hop until the lient reahes the destination server and ontats UAS diretly. Registrar server: It handles lient registration ruest for its urrent loation. Generally, Registrar server is o-loated in the same physial entity hosting the rediret or proxy server. SIP works in tandem with the Session Desription Protool (SDP) that desribes multimedia sessions. Session desription serves for session announement, session invitation and other session initiation funtionalities. SDP is ompletely independent of transport protool. It onerns mainly the format of session desription and is designed to work with any transport protool. any of the SDP messages are sent using Session Announement Protool (SAP). hese messages are UDP pakets with a SAP header and a text payload. he text payload is the SDP session desription. essages an also be sent using or the World Wide Web. Fig., depits the position of SIP and SDP in the multimedia protool stak. ultimedia Appliations Audio Video Data SIP RSVP RP RCP SDP SAP Registrar Server Rediret Server CP IP UDP Figure. ultimedia protool stak. IPetwork III. SIP OVER DIFFSERV Router Router Figure. SIP Arhiteture. Client in SIP is a general onept. It ould be any devie initiating sessions (Phones, PCs, Palms, ). On the other hand, SIP serve inlude the following main types: Proxy server: he most important element in the SIP arhiteture, as it onstitutes an intermediate devie reeiving SIP ruests from lients and forwarding the ruests on lients behalf. ypially, proxy serve A. Bakground Few researhes [], [] and [3] have addressed the arhiteture of SIP over DiffServ arhiteture in IP networks. Zhang and Guy [3] proposed an extension to the Proxy server in the SIP arhiteture to inlude raffi Engineering (E) apabilities, where the SIP proxy server uses the messages exhanged during an SIP session to provide E ruests. he proxy server may use the messages exhanged during an SIP session to exhange traffi engineering ruests. hese ruests will be exhanged between the SIP proxy server and the Label Edge Router (LER) by Common Open Poliy Servie (COPS) protool messages 006 ACADEY PUBLISHER

3 JOURAL OF COUICAIS, VOL., O. 5, AUGUS []. Indeed, we need to transfer information related to the ruest of resoure by QoS lients and for the alloation of resoures by resoure alloation serve (e.g., bandwidth broker) in a DiffServ network. Hene, this resoure alloation funtionality an be added in the COPS framework. Fig. 3, depits the proposed arhiteture for SIP over DiffServ. SIP erminal E-SIP Server COPS LER PLS etwork he SIP proxy server ould only negotiate E sessions with another E enabled SIP proxy server, otherwise normal SIP session (without E extensions) is initiated. he flow of SIP messages is resumed on Fig. 4. Assuming that ommuniation issues related to resoures management and reservation at the LER is ahieved by the COPS framework; SIP an play the role of an appliation ontrol layer protool to guarantee QoS ruirements of user sessions. B. Session based QoS Generally, we speak of QoS per type of servie. hus, for real time appliations we are onerned about end to end time onstraints like delay and jitter to guarantee the reonstitution of multimedia signals (voie or video) [7]. On the other hand, non-real time appliations (or data appliations) are less sensitive to time onstraints, while they ruire guaranteed nominal bit rates and loss free transmission. Hene, these appliations (e.g Web, FP and ) use ransmission Control Protool (CP) for reliable and in-order transmission. However, the elasti behavior of CP makes the transmission ompletely dependent of the network ongestion state. In both ases, real time and non-real time appliations, the QoS ruirements are grouped together to express an SLA ruired for one appliation. his ould be onsidered as a mirosopi view of QoS. On the other hand, a marosopi view of QoS may inlude user behavior during session. he global view per session is important in our ontext beause SIP handles the session LER COPS Figure 3. SIP over DiffServ arhiteture. E-SIP Server SIP erminal SIP-E Server LER LER SIP-E Server SIP erminal Invite Invite Invite 00 ok 00 ok 00 ok COPS R COPS De raffi Dynami WFQ priorities R De SIP erminal SIP-E Server LER LER SIP-E Server SIP erminal Figure 4. SIP over DiffServ flow of messages. SIP erminal establishment and onside the user ativity during a session as a whole. he extension of SIP to offer QoS provisioning mehanisms ruires a marosopi treatment for sessions. Consuently, we define a session based QoS in whih we onsider user ativity during the session and the type of the appliation used. Based on the above presented arhiteture we want to implement QoS management algorithms at the session level. he proposed algorithms are based on traffi engineering tehniques and will be hosted in the SIP proxy server. hus, the SIP proxy server implements QoS mehanisms on multimedia sessions, based on measurements and a priori estimation of uivalent bandwidth. Indeed, the SIP proxy server measures the duration of sessions and the data volume exhanged during sessions (funtions that are generally used for billing purposes), then a session sheduling an be ahieved. Furthermore, the SIP proxy server an perform flow based uivalent bandwidth estimation, based on information olleted about session paramete before initiating it. However, this ruires uivalent bandwidth estimation tehniques that we will present in the following setion. IV. A. Related Work EQUIVALE BADWIDH raffi ontrol is generally used to optimize the alloation of network resoures in order to sustain an aeptable QoS for network onnetions. any traffi ontrol strategies inluding ongestion ontrol and all admission poliies, rely on the notion of the uivalent (or effetive) bandwidth or the resulting onnetion load on network links. For example, aess ontrol uses this information to deide whether to aept or not inoming ruests for new onnetions. he admission riteria depend on the impat of new added onnetions on both the resoure utilization and the QoS offered for aepted and already existing traffi. he notion of uivalent bandwidth has been used in the literature and two broad ategories of uivalent bandwidth estimation approahes are generally used. he fit ategory is based on Kelly s [7] mathematial definition of uivalent bandwidth for different kinds of traffi. he seond ategory refe to the analytial methods based on traditional queuing theory. he mathematial framework proposed by Kelly relies on large deviation theory to estimate the uivalent bandwidth of a stationary arrival proess. On the other hand, analytial approahes hypothesize the traffi models in order to give an approximate expression for the uivalent bandwidths in some ases suh as arkov proesses (e.g. [,0]). In this paper, we suggest an analytial approah to estimate uivalent bandwidth based on a renewal proess approximation. B. Equivalent bandwidth estimation by renewal proess approah In order to haraterize the effetive bit rate or uivalent bandwidth of a traffi soure, we need to selet an appropriate model to speify its harateristis 006 ACADEY PUBLISHER

4 0 JOURAL OF COUICAIS, VOL., O. 5, AUGUS 006 in terms of known paramete or metris. For the purposes of our researh, we adopt a two-state model (- ) that aptures the basi behavior of the data soure assoiated with a onnetion. he rationale for suh a model is that a soure is either in an idle state, ( ) transmitting at zero bit rate, or in a but state ( ) and transmitting at its peak rate. Suh a soure model has the advantage of being both simple and flexible as it an be used to either represent onnetions ranging from buty to ontinuous bit streams. Let the following values be assoiated with one onnetion: R : Average rate of one onnetion (Kbps), : Average duration of period (Se), : Average duration of period (Se), R : Average rate in period (Kbps), Q : Average file size in period (Kb) (to be used only with CP based models), X : Buffer size, E : arget paket loss probability. he renewal proess approah is an approximation of the superposition of - proesses. In this method, we study the superposition of - proesses as a GI / D // K system. In order to evaluate the uivalent bandwidth of - proesses we study the paket loss in GI / D / / K system. he paket loss probability is alulated as a funtion of the following paramete: K : he buffer size in pakets, ρ : System load with ρ= λ / µ, λ is the aggregate arrival rate of input - proesses and µ is the average servie time. a : he squared oeffiient of variation of the input arrival proess. s : he squared oeffiient of variation of the servie time. Our approah is based on paket loss approximation formulas for the GI / D // queue presented in [9,0]. Let the number of lients in the queue inluding the one being servied, be denoted by. Whitt [9] expresses the average and the seond moment of the number of lients as: ρ ( a+ s ) g E ( ) = ρ+ ( ρ) ( ) = ( )( + ) E E g is a weighing fator depending on the value of he parameter a a : () ( ρ)( ) a 3 ρ( a s ) + g e a< = () is defined as: YY = (3) Y3 Y is the value of Var ( ) given by: Var = EW VarW (4) ( ) λ ( ) ρ ρ s λ ( ) W denotes the steady state waiting time before beginning servie. he average and the variane of W are given by: τρ( a+ s ) g EW ( ) = ( ρ) VarW ( ) = E ( W ) w τ is the mean servie time and w is the squared oeffiient of variation of the waiting time expressed as: D w (5) + σ = (6) σ σ is the delay probability whose value is: σ= PW> = ρ+ ρ ρh (7) ( 0) ( a ) ( ) + a+ ρs a ( s ) (4 a s ) h + ρ + ρ + = (8) 4ρ a a+ ρ (4 a+ s ) D is the squared oeffiient of variation of the onditional delay given that the server is busy. Its value when servie time is deterministi is given by: D ρ + 4( ρ) = 3( + ) Finally Y and Y 3 are given by: s (9) ρ+ σ Y= max{ σ+ ρ, } (0) Y = max { ρ+ λew ( ), } he maximum is used to avoid division by zero. In order to ompute the paket loss when finite buffer is onsidered the two fit moments of the paket loss distribution are not suffiient. he distribution itself is needed, whih an be obtained by a ontinuous distribution fit as shown in [9]. hus Pr( > x) is expressed as a funtion of Case >.0 value as follows: γx γx Pr( > x) = pe ( e ) + + where p= p ( p) And γ=, γ= E ( ) E ( ) Case 0.99< <.0 Pr( > x) = e x E( ) 006 ACADEY PUBLISHER

5 JOURAL OF COUICAIS, VOL., O. 5, AUGUS 006 Case 0.50< < 0.99 γx γx ( γe γe ) Pr( > x) = ( γ γ) γ where γ= γe ( ) And γ= E + Var E Case < 0.50 ( ) ( ) ( ) γx Pr( > x) = e ( + γx) Where γ= E ( ) ote that the suggested heuristi estimates the paket loss probability as a funtion of buffer size, average input rate, average output rate and the squared oeffiient of variation for both arrival and servie proesses ( a and s ). Speifially, the last two paramete play an important role in estimating the uivalent bandwidth of input traffi. C. Erlang bloking probability he uivalent bandwidth estimated by the previous tehnique onside a onstant number of - onnetions. In the general ase we model the flow arrival proess at the all level as Poisson proess. Eah flow is defined by its all arrival rate λ, period average rate R, mean rate R and average duration. hus, for onnetions with i, R uivalent bandwidth, i=,...,. he overall uivalent bandwidth BW is given by: BW = Ri, () i= In the last uation we onsider onstant sessions. When Poisson arrival proess is onsidered, one an estimate the uivalent number of onnetions (iruits) for one bloking probability, using Erlang B formula: P ( ) = A /! i= 0 i A / i! () With A= λ / µ. Hene for one flow with session Poisson arrivals, we estimate the uivalent number of sessions for one bloking probability B and the uivalent bandwidth p BW is obtained easily by multiplying the uivalent rate of one onnetion by. D. Equivalent bandwidth of multimedia flows wo types of multimedia flows are onsidered: VoIP, and Data. VoIP and Data sessions are usually modeled as - proesses. However, paket transmission is ahieved by UDP for VoIP, and by CP for Data sessions. Reall that CP algorithm reats to paket losses. Hene, the uivalent bandwidth of CP flows an only be ahieved under the hypothesis of loss free transmission. However, it is suffiient in our ase as the goal is to ahieve loss free transmission. VoIP appliations have a ommon harateristi whih is the onstant paket size and onstant paket interarrival time during periods (see [5] for more details). he squared oeffiient of variation of servie time proess in a deterministi servie queue for VoIP = 0 ) beause paket sizes are pakets is null ( s onstant, while the squared oeffiient of variation of paket arrival proess for - onnetions is given by [4]: = w + w (3) a is the squared oeffiient of variation of single - onnetion and it is alulated as funtion of the paket transmission probability p, onstant paket inter-arrival, duration: p = ( / + p) (4) w= (5) + 4( ρ) ( ) he average rate is R = P * R and the maximum rate is R =. Although Web sessions share the same - struture with VoIP appliations; the paket arrival proess is more ompliated as it depends on the CP algorithm. By onsuene, the squared oeffiient of variation of paket arrival proess an not be estimated analytially. wo solutions to this problem may be proposed: fit, we an measure the value of diretly on the generated trae. his ruires having the generated traffi before evaluating the uivalent bandwidth, whih may not be useful when used in a QoS management server (the SIP proxy server). hat is why we suggest a seond heuristi based on the approximation of paket arrival proess during periods by a onstant proess of the same average. hus, we need to estimate the average rate during the period when only the file size in known. Autho in [] present a formula to alulate the transfer time when CP is used on short-lived onnetions (one ACK per two pakets b=). log.57( b) b ( ) = R ( f( prb, ) + + 4p log.57( b) + 0 p) Assuming that: (0+ 3 Rb ) + 4( pw ) W max max a (6) 006 ACADEY PUBLISHER

6 JOURAL OF COUICAIS, VOL., O. 5, AUGUS 006 b is the file size in pakets, W max he maximum reeption window, p paket loss probability, And 3.3(p+ 4p + 6 p ) + p f( pr, ) = ( + R) 0R As we are onerned with the periods of Web sessions, the file transfer ativity is very short ompared to the idle period. hus, this formula is appropriate to our study ase. eanwhile, a major simplifiation an be done when estimating the uivalent bandwidth with small loss probabilities. Indeed, the ontribution of the fit term R log.57( b ) is dominant, and the uation an be used in its simpler form: b ( ) = R log ( b) (7) Using the estimated transmission time during the period we an estimate the average transmission rate as b Q λ = with b=. b ( ) Ps Having the average transmission rate λ we an use the same formulas as for VoIP while onsidering onstant paket inter-arrivals during the period (this is an approximation). On the other hand, we onsider a maximum segment size in the CP algorithm of 984 bytes. hus, we generate pakets of (SS+Header= =04 Bytes). As a result we generate 04 bytes for all pakets exept the last one (the residual value). Consuently, the squared oeffiient of variation of servie time in a deterministi servie queue for Web pakets an be supposed null ( s 0 ). As a result, the uivalent bandwidth estimation proedure is very similar to the VoIP ase. E. Performane validation We validate the estimated uivalent bandwidth values for G7 sessions (refer to able II) and W3 Sessions (refer to able II) in network environment. For this purpose we injet the traffi generated by the two types of sessions into a queuing system of deterministi servie while the servie rate is hosen as a funtion of uivalent bandwidth estimation values. We ompare values of observed paket loss rate of both estimation methods for the uivalent bandwidth. We show results as funtion of the number of onnetions. ote that we evaluate the uivalent bandwidth with 30 paket size buffer and % paket loss rate. ABLE I..57 VALIDAI OF HE EQUIVALE BADWIDH EB VoIP Loss rate % EB Web Loss rate % Kbps Kbps he estimated uivalent bandwidth guarantees the average paket loss rate (%) espeially when the number of onnetions is important. otie that onstant paket inter-arrivals approximation during periods for Web sessions lead to aeptable results. Although this is not the real behavior of inter-arrivals when CP is used, the uivalent bandwidth estimated with this method guarantees an aeptable loss rate. his approximation allows analytial estimation of the uivalent bandwidth for Web sessions diretly. V. QOS ECHAISS WIH SIP he goal of this setion is to introdue novel mehanisms for QoS management on a per-session basis. he SIP proxy server will be delegated for the implementation of these mehanisms. he fit mehanism relies on the sheduling of CP sessions based on session duration and data volume exhanged during a session. he seond mehanism uses the uivalent bandwidth estimation methods to alloate bandwidth per flow. he SIP proxy server is supposed to ahieve measures on session durations and data volume exhanged, as well as the uivalent bandwidth estimation based on session paramete exhanged during session initiation phase. A. Sheduling of CP sessions umerous studies show that 80% of internet flows are arried by CP. It is also shown that 80-90% of the traffi is arried by only 0-0 % of the flows (big file transfe) while % of the flows arry only 0-0% of the traffi. It is obvious that CP ruires speial attention and partiularly the interation between big and small data transfe must be onsidered in any QoS provisioning mehanisms. Indeed, several researhes dealing with the effiieny of CP ongestion ontrol mehanism in ongested networks have been undertaken. However, results show that losses have dramati onsuenes on short CP onnetions. It was suggested that aording higher priority to short CP onnetions onstitutes a good solution to this problem [8]. he question of differentiating long from short CP onnetions ruires modifiations in CP heade to perform measures on CP onnetions (Duration or data volume exhanged) reader an refer to [,3] for some other proposals. In all ases this issue was always addressed at the onnetion level. On the other hand, an appliation level solution to this problem is more appropriate and easier to implement. Indeed, we an onsider the user behavior during all the session as a whole and instead of differentiating short from long onnetion we distinguish small from big sessions. Using SIP we an manage user ommuniations at the session level with session sheduling based on session level riterion. his is ahieved by supervising mehanisms implemented in the SIP Proxy server in the extended SIP arhiteture. he main advantage of our approah is that supervising mehanisms relies on measures that are performed usually for billing purposes. By onsuene, no modifiation on CP heade are ruired and no extra transmission overhead is supported. 006 ACADEY PUBLISHER

7 JOURAL OF COUICAIS, VOL., O. 5, AUGUS ) he Conept he main idea behind session sheduling is to hange traffi priority dynamially during ommuniation based on real time measurements. he goal is to minimize the impat of long CP sessions on both short CP sessions and real time traffi. Indeed, the SIP proxy server measures in real time the duration of CP sessions and data volume exhanged during one session. All sessions initiated by the SIP server has the same priority at fit. Sessions lasting more than average session duration, or exhanging more than average data volume V are automatially delassed into a lower priority lass of traffi. In order to alulate the values of and V we introdue the notion of the referene session RS. he referene session RS represents the threshold session ativity under whih the user session is onsidered as small. he notion of small session may refer to the duration or the data volume of a session. his is quiet different from the onnetion notion in whih long onnetions are synonym of big file transfe. In fat, CP sessions may ontain long idle periods and the notion of duration may lead to some wrong differentiation between sessions. One the referene session RS is defined, the theoretial duration and data volume exhanged during referene session RS an be alulated. Let: br : Average number of periods in a session, : Average duration of period (Se), : Average duration of period (Se), R : Average rate in period (Kbps), Q : Average file size in period (Kb) (to be used only with CP based models) In order to alulate the value, we onsider the CP session transmission in the free loss ase (the simplified form of CP onnetion duration uation (7)): Q Q R log.57 = Ps Ps with Ps paket size he average session duration is given by: = br ( + ) (8) And the average session data volume is given by: V = brq. (9) ) he Algorithms Here we develop the two algorithms based on referene session duration and data volume exhanged. hose algorithms are implemented by the SIP proxy server and are applied to all inoming CP sessions. Algorithm. Servie lass differentiation based on session duration/volume Calulate referene session duration and data volume V Define two servie lasses High and Low Aept all inoming CP sessions with the High servie lass For all sessions If session duration > (or session data volume > V ) End End B. Resoure alloation Delass the session servie to the Low lass he sheduling of CP sessions is a posteriori solution to network ongestion. Indeed, it minimizes interation between big and small CP session after some threshold. Although it ruires no information about CP sessions, the hoie of its threshold may problemati. Atually, it influenes the performane of the algorithm and the overall gain in terms of QoS. On the other hand, the role played by the SIP proxy server an be enhaned to suggest a priori solutions that prevent interation between big and small CP sessions. Hene, instead of deteting big CP sessions after some threshold, use may delare their sessions previously. Aording to the session type ruired by the user a different lass of servie may be assigned and onsuently an appropriate QoS is obtained. ) he Conept Resoure alloation ruires uivalent bandwidth estimation per session type. he idea is delegate the SIP proxy server to evaluate the uivalent bandwidth of CP flows per type of session. In order to ahieve this estimation the SIP proxy server needs some speifi desription of initiated sessions. his will be ahieved by the SDP protool assoiated with SIP. Assuming a Poisson arrival distribution of lient sessions, an uivalent number of sessions an be estimated by the Erlang B formula for a determined bloking probability. hen an uivalent bandwidth estimation proedure is launhed based on session information exhanged during the SDP ommuniation phase. One the uivalent bandwidth is determined, a bandwidth sharing proess is undertaken by Weighted Faire Queuing (WFQ) system at the Edge router. Partiularly, weights are hosen as funtion of uivalent bandwidth and available bandwidth. he goal is to assign the ruired bandwidth to small CP sessions, while big CP sessions share the residual bandwidth. In the following setion we will present the algorithm that will be implemented in the SIP proxy server while onsidering only two flows types. Of oue this approah may be extended to several flows of different types (not only CP sessions). ) he Algorithm Consider two types of CP sessions: small and big. he goal is to alloate resoures for small CP sessions to eliminate interation between the two types. he SIP proxy server handles the following paramete: 006 ACADEY PUBLISHER

8 4 JOURAL OF COUICAIS, VOL., O. 5, AUGUS 006 Bp he bloking probability D Poisson session arrival rate (Session/se) B Available bandwidth And the following session paramete: br : Average number of periods in a session : Average duration of period (Se) Q : Average file size in period (Kb) Algorithm : Flow based bandwidth reservation For small CP sessions alulate the uivalent number of sessions A /! Bp( ) = With A= λ i µ A / i! i= 0 Estimate the uivalent bandwidth B for sessions Define two lasses of servie S for small and B for Big Adjust the WFQ weights so that: B B B WS = and WB= B B Assign small CP sessions to the S lass of servie Assign big CP session to the B lass of servie C. Call Admission Control for CP sessions So far only the issue of minimizing interation between flows was addressed, fit by sheduling of sessions and then by resoure alloation. Indeed, a more natural role an also be assigned to the SIP proxy server, whih is Call Admission Control (CAC). Whether it onerns small or big sessions, the overhead that may be indued by the initiation of new sessions may be onsiderable when network fall into ongestion. hus, the sheduling of sessions will have no effet if the number of small CP sessions exeeds system apaity. oreover, big sessions will endure extremely long time of servie due to the system overhead. Indeed, this issue is of partiular interest for CP sessions as the session duration is tightly linked with the loss rate observed on network links. If the number of aepted sessions is larger than system apaity, higher paket loss rate may be observed and longer transmission times are needed (beause of CP retransmission mehanisms). Let use being onneting to the system aording to Poisson proess with D session arrival rate (Session/se) and let be the session duration, then the average number of use present in the system may be obtained by the Little formula: = D * (0) otie that. Hene, the inrease of session duration results in inreasing number of ative sessions in the system. herefore, the session management overhead for the SIP proxy server will inrease rapidly affeting the performane of the server itself. Call admission ontrol ould be assoiated with the previous proposed algorithms to guarantee normal funtioning of the network. his ruires the definition of the Call Admission Control hreshold ( CAC th ) per type of sessions. When resoure alloation is performed this threshold is simply defined by bandwidth reserved for one flow (denotedb ). Indeed, the estimation of B rely on the number of sessions, thus: CACth () On the other hand, when session sheduling is onsidered this is more ompliated. In fat, the result of aepting new onnetion ould not be evaluated if the uivalent bandwidth ruired by the inoming onnetion is not known. One solution may be to ahieve all admission ontrol based on real time measurements of resoure ruirements. However, in the sope of our study we will only onsider integrating CAC with resoure alloation algorithm based on bandwidth estimation. ) CAC with bandwidth alloation Basially, the session information used for uivalent bandwidth estimation and alloation is also used by CAC algorithm. hus, for every new inoming onnetion the uivalent bandwidth neessary to allow the transmission of the flow is alulated. If the estimated value does not exeed the maximum bandwidth alloated for the flow the onnetion is aepted otherwise it is rejeted. Finally, we note that resoure alloation proedure is based on session information exhanged before session initiation. he type of the session delared by the user is determinant for aepting or rejeting his demand. eanwhile, in the ase of wrong session type delaration, big sessions may be initiated as high priority ones ausing the deterioration of the overall performane of the system. herefore, it is possible to ombine the sheduling of sessions algorithms to delass wrongly delared sessions to lower lass of servie as a posteriori validation mehanism. Algorithm 3: CAC with bandwidth alloation Bandwidth alloation algorithm (same steps as in Algorithm ) For every inoming session Calulate the new uivalent session s number Estimate the uivalent bandwidth B for sessions If B < B Else End End,max Aept the onnetion Rejet the onnetion VI. SIULAIS he QoS session mehanisms proposed in previous setions are tested in a simple network of two nodes representing the two LER route. he DiffServ domain is modeled by a bottlenek link between two LER route. Bottlenek delay is of 0 ms (used for the R 006 ACADEY PUBLISHER

9 JOURAL OF COUICAIS, VOL., O. 5, AUGUS estimation). An SIP Proxy server is harged of initiating different kind sessions. Client Sessions Figure 3. We onsider three types of web sessions (W, W, W3), and a VoIP appliation session (G79). Four flows are generated (one for eah type of session) in order to evaluate the suggested QoS mehanisms. Indeed, the G79 flow is only used for performane evaluation ends while data sessions are handled dynamially by the QoS mehanisms. Session paramete are listed in able II. Session ABLE II. Q ean (Kb) Given the above session paramete we alulate the flows paramete that will be used when applying QoS mehanisms by the SIP proxy server. Bloking probability value is % for all flows (able III). ABLE III. Reall that the estimation of CP session duration is only possible in free loss transmission. his estimation is used to determine the referene duration (and volume) for sheduling of sessions. Paket transmission is ahieved by CP new Reno implemented from end to end in the simulator. Paket sizes are of 04 bytes with 40 bytes ACKS. A. est of Algorithm Q Variane (Kb) SESSI PARAEERS ean (Se) W 0KB 40KB 0 se 0 se W 50KB 00KB 0 se 40 se W3 00KB 00KB 30 se 60 se VoIP Paket Size (Bytes) E-SIP FLOW PARAEERS Flow D Session/se Se (u) LER estbed network Paket Interarrival (ms) W W W G B Kbps We onsider only two lasses of traffis High (Priority ) and Low (Priority ). All sessions start transmitting pakets in the High traffi lass. VoIP sessions stay always in the High traffi lass and do not hange their lass. Delassing sessions onerns only CP sessions. he goal of our test is to give short Web sessions represented by W sessions higher priority on other CP sessions using sheduling of sessions. In this ase, the W session is the referene session RS and its (se) G G LER E-SIP Variane (Se) (Se) transmission time without losses is the referene time ( =0.3 se ), and the data volume exhanged during the RS session is V =00 Kbytes (those values are obtained based on W session paramete). We ompare the results of proposed sheduling mehanisms with FIFO queue system without any priority lasses. Results are shown on able IV. FIFO ime Priority Volume Priority ABLE IV. Results show no big differene in performane when using time based session sheduling. Indeed, if we analyze the ativity of W sessions we note that idle periods are very long ompared to ativity time during web sessions. Delassing sessions aording to the time passed on the network is not profitable in this ase. In fat, the ommuniation duration riterion ould only be used for FP type like sessions where there are no idle times. Conveely, we see that the performane of W sessions, G79 sessions has improved onsiderably in the ase of session delassing based on data volume exhanged during a session. In fat, W session duration is loser to theoretial value without losses, while G79 sessions endure less paket loss rate. B. est of algorithm Using the same previous example sessions, we alulate the weights of WFQ system based on the estimation of the uivalent bandwidth per flow. We onsider two WFQ queues in the edge router with two orresponding traffi lasses: High and Low. he weights are alulated to alloate the ruired bandwidth for the High traffi lass. he Low traffi lass takes the residual bandwidth. able V depits the alulated weights based on sessions paramete defined before. ABLE V. Flow B Kbps FLOWS SAISICS WIH DIFFERE PRIORIIES Flow Loss % Delay ms Average session duration se W 3% W.9% 5 40 W3.7% G79 3.5% W.9% 5 70 W.5% W3.3% G79.6% W 0.9% W.7% W3 3.% G79.% WFQ WEIGHS FOR BADWIDH SHARIG raffi lass Weight Bottlenek bandwidth kbps W+G79C 43.7 High 00 W+W Low ACADEY PUBLISHER

10 6 JOURAL OF COUICAIS, VOL., O. 5, AUGUS 006 Bandwidth alloation Results are better than fit mehanism. Loss rate and delay on the W flow and G79 flow are smaller than previous tests. Espeially, W session average duration is very lose to theoretial estimation. Even W and W3 sessions performs better ompared to the FIFO system ase. his is espeially due to the better bandwidth utilization and the isolation fator resulting in less interation between flows. o illustrate the robustness of this approah we show on Fig. 5 the evolution of session durations while the link bandwidth is redued from 00 Kbps to 800 Kbps by 00 Kbps step. he SIP proxy server adjusts weights of the WFQ queuing system to guarantee the ruired bandwidth for W and G79 flows while the W and W3 flows gets always the residual bandwidth. he urves show that the measured W session duration is stable while the measured W and W3 session durations inreases as the bandwidth is redued. Session Duration in Se ABLE VI FLOWS SAISICS WIH WFQ Flow Loss % Delay ms Average session duration se W 0.3% W % W3.% G % Evolution of session duration vs bottlenek Bottlenek in Kbps Figure 5. Evolution of session s durations vs bottlenek he stability of the duration of small CP session ould be seen as a QoS parameter for Web sessions always served as best effort traffi. It has bigger impat in wireless networks where bandwidth is a preious resoure, and guaranteed average throughput is an important parameter of the servie. VII. CCLUSI In this paper, we presented an SIP based framework for QoS at the session level. Using the SIP proxy server with extended arhiteture over DiffServ domain, we an implement session sheduling and bandwidth alloation mehanisms to minimize the interation between small and big CP sessions. he suggested mehanisms rely on session level real time measurements of session duration and data volume exhanged during a session as well as W W W3 uivalent bandwidth estimation tehnique. he ruired measurements do not ause additional overhead as they are ahieved for billing purposes. However, bandwidth alloation ruires more speifi session desription that should be exhanged between the SIP proxy and the lient using the SDP protool. Bandwidth alloation is based on uivalent bandwidth estimation per flow. Indeed, we proposed a GI / D / / K queue system model to evaluate the uivalent bandwidth using the fit and seond order moment of paket inter-arrivals and paket servie proesses. However, some heuristis to measure the uivalent bandwidth in real time ould be onsidered using iterative algorithms. his may be useful also to implement adaptive all admission ontrol mehanisms. During our study we only onsidered homogenous flows (per type of session) for the estimation of uivalent bandwidth. In fat, the estimated uivalent bandwidth depends on traffi mixes and may be influened by the different paket sizes aording to appliation types (and transport protools). Partiularly, in VoIP appliation paket sizes are very small omparing to Video and CP sessions resulting in important ovariane on the paket servie proess and the overall performane. Finally, we would like to note the QoS mehanisms proposed are applied on a per-session basis, and this may result in an extra delay on session initiation proess for use. Some aggregated reservation tehniques [] may be useful in this ase to enhane the SIP proxy server response time. REFERECES [] F. P. Kelly. Effetive bandwidths at multi-lass queues. Queueing Systems, 9:5--6,99. [] R. Geurin, H. Ahmadi, and. aghshineh. Equivalent apaity and its appliation to bandwidth alloation in high-speed networks. IEEE J. Selet. Areas Commun, 9(7):968-98, September 99. [3] C. Couroubetis and R.Weber. Effetive bandwidths for stationary soures. Prob. Eng. Inf. Si., 9:85--96, 995. [4] A. Elwalid and D. itra. Effetive bandwidth of general arkovian traffi soures and admission ontrol of high speed networks. IEEE/AC rans. on etworking, (3): , Otober 993. [5] C. Couroubetis and R. Weber. Buffer overflow asymptotis for a swith handling many traffi soures. Journal of Applied Probability, 33: , 996. [6] A. Simonian and J. Guibert. Large deviations approximations for fluid queues fed by a large number of on-off soures. IEEE J. Selet. Areas Commun., 3(7):07--07, August 995. [7] F. P. Kelly. otes on effetive bandwidths. In F. P. Kelly, S. Zahary, and I. Zeidins, edito, Stohasti etworks: heory and Appliations, pages Oxford Univeity Press, 996. [8] G. de Veiana and J. Walrand. Effetive bandwidths: Call admission, traffi poliing and filtering in A networks. Queuing Systems, 0:37--59, 995. [9]. Likhanov and R. R. azumdar. Cell loss asymptotis for buffe fed with a large number of independent 006 ACADEY PUBLISHER

11 JOURAL OF COUICAIS, VOL., O. 5, AUGUS stationary soures. Pro. of IEEE IFOCO'98, San Franiso, USA, arh 998. [0] W. Whitt, ail probabilities with statistial multiplexing and effetive bandwidths in multi-lass queues, eleommuniation Systems, pp.7-07, 993. [] B. Rong, J. Lebeau,. Bennani,. Kadoh and A. Elhakeem, raffi Aggregation Based SIP over PLS etwork Arhiteture, Proeedings of International Conferene on Advaned Information etworking and Appliations (AIA 005), 005. [] S. Salsano and S. Veltri, QoS Control by eans of COPS to Support SIP-Based Appliations, IEEE etwork, Vol. 6, Issue :, pages 7-33, 00. [3] C. Zhang and C.G Guy, E-SIP Server Design for a SIPover-PLS Based etwork, Proeedings of International Conferene on Communiation ehnology (ICC 003), Volume :, pages , 003. [4] [5] [6] [7] La qualité de servie de la voix sur IP, prinipes et assurane. [8] U. Ayesta, Stohasti Sheduling and its Appliation to CP/IP etworks, hesis of IRIA, ie-sophia Antipolie, 005. [9] W. Whitt, he queuing network analyzer. Bell System ehnial Journal, pages , ovember 983. [0] R. agarajan, J. F. Kurose, D. owsley, Approximation ehniques for Computing Paket Loss in Finite-Buffered Voie ultiplexe, IEEE Journal on Seleted Areas in Communiations (99). [] B Sikdar, S Kalyanaramana and K.S Vastola, An Integrated odel for the Lateny and Steady-State hroughput of CP onnetions. Performane Evaluation, Vol 46, no. -3, pp , 00. [] C. Estan and G. Varghese, ew diretions in traffi measurement and aounting: Fousing on the Elephants, ignoring the ie AC transations on Computer Systems, August 003. [3] C. Psounis A. Ghosh and B. Prabhakar. SIF: a simple algorithm for identifying large flows, Presented at the Stohasti etworks Conferene, ontreal, Canada, 004. [4] K. Sriram and W. Whitt, Charaterizing Superposition Arrival Proesses in Paket ultiplexe for Voie and Data, IEEE Journal of Seleted Areas in Communiations, pp , Sep, 986. [5] H. Hassan, J- Garia and C. Bokstal Aggregate traffi models for VoIP appliations, ICD 006, in press. Hassan HASSA. is a Ph.D. student at Laboratoire d Arhiteture et d Analyse de Systèmes of CRS, oulouse, Frane. He reeived his S degree in etworks and eleommuniations from the ESEEIH, oulouse, Frane, in 003 and his B.E. degree in Eletronis from ESERG, Grenoble, Frane, in 996. His researh interests inlude ultimedia raffi odeling and Performane Analysis in Heterogeneous etworks. Jean-arie GARCIA. reeived his Ph.D. from the Univeité Paul Sabatier, oulouse, Frane, in 980. He reeived his B.E. degree from Institut ational des Sienes Appliquées, oulouse, Frane, in 976, and the. A. S degree from the Eole Polytehnique, ontreal, P.Q., Canada, in 978. He performed Researh at the Institut of Hydro Quebe, Varennes, P.Q., Canada, in 977. He spent one year as a postdotoral fellow at the Eletronis Researh Laboratory, Univeity of California, Berkeley, in 98, and in 98 he joind the Laboratoire d'analyse et d'arhiteture de Systèmes of CRS, oulouse, where he is presently direteur de reherhes. His main interests are modeling and ontrol of teleommuniation networks, optimization and resoure management aspets. Olivier BRU. reeived his Ph.D. from the Univeité Paul Sabatier, oulouse, Frane, in 000. He reeived his B.E. degree from Institut ational des eleommuniations, Evry, Frane, in 995. He spent one year as a researh engineer in the Delta Partne ompany where he developed a modeling tool for large-sale telephone networks. In 00, he joined the Laboratoire d'analyse et d'arhiteture de Systèmes of CRS, oulouse, where he is presently harge de reherhes. His researh deals with stohasti modeling and network planning. 006 ACADEY PUBLISHER