End-to-end measurements of GPRS-EDGE networks have

End-to-end measurements over GPRS-EDGE networks Juan Andrés Negrera Facultad de Ingenería, Unversdad de la Repúblca Montevdeo, Uruguay Javer Perera Facultad de Ingenería, Unversdad de la Repúblca Montevdeo, Uruguay javerp@fngeduuy Pablo Belzarena Facultad de Ingenería, Unversdad de la Repúblca Montevdeo, Uruguay belza@fngeduuy Santago Pérez Facultad de Ingenería, Unversdad de la Repúblca Montevdeo, Uruguay ABSTRACT In the last years, QoS (Qualty of Servce) parameter estmaton has become a man research area n networkng due to a contnuous growth of the Internet End-to-end actve measurement s one of the topcs that focuses on ths research area However, these measurement methodologes have focused on end-to-end measurements over the wred Internet The development of cellular data servces s shftng the resarch focus on QoS from wred to wreless networks End-to-end measurement methodologes of cellular networks have some ssues that are not consdered by tradtonal measurement technques Ths paper analyzes these ssues and suggests an end-to-end actve measurement methodology that deals wth these partcular problems The proposed research and measurement methodology s based on a GSM (Global System for Moble Communcatons) network, partcularly on data servces on a GPRS-EDGE (General Packet Rado Servce/Enhanced Data Rates for GSM Evoluton) network Several experments n dfferent stuatons have been done n a real cellular network These experments have tested the performance of the methodology n dfferent data access condtons Categores and Subject Descrptors C4 [Performance of Systems]: Measurement technques, Performance attrbutes General Terms Network performance, Algorthms Keywords Performance, QoS, GSM, GPRS-EDGE Permsson to make dgtal or hard copes of all or part of ths work for personal or classroom use s granted wthout fee provded that copes are not made or dstrbuted for proft or commercal advantage and that copes bear ths notce and the full ctaton on the frst page To copy otherwse, to republsh, to post on servers or to redstrbute to lsts, requres pror specfc permsson and/or a fee LANC 07 October 10-11, San Jose, Costa Rca Copyrght 2007 ACM 978-1-59593-907-4/07/0010 $500 1 INTRODUCTION Today cellular servces nclude voce communcatons, emal, sms, audo and vdeo streamng and moble TV Ths stuaton has been generated by the ncrease n cellular access bandwdth Ths type of servces have strong constrants n performance and qualty To deal wth ths constrants a model that analyzes the end-to-end performance of a GPRS- EDGE connecton s necessary Unfortunately, the analytcal models that have been developed to analyze the performance of cellular systems make strong smplfcatons They can only be used to get a rough dmenson of the system, but not to analyze the end-to-end performance of a partcular data flow End-to-end measurements of wred IP networks has been an mportant area of research durng last years Therefore, untl last years, the focus was only on wred networks and not on wreless networks End-to-end measurements of GPRS-EDGE networks have some partcular problems that are not consdered n the wred case For example, the spectrum resource sharng adds some specal ssues, as well as the prorty of the voce traffc The focus of ths work s on end-to-end GPRS-EDGE networks capacty estmaton and some other mportant performance ssues Ths work suggests a methodology for endto-end measurements of ths knd of networks Based on ths methodology a software tool was developed Usng that tool some experments have been done to estmate dfferent performance metrcs n a GPRS-EDGE network The paper s organzed as follows A summary about the state of art concernng end-to-end measurements over IP networks s n Secton 2 An explanaton of mportant parameters to measure over GPRS-EDGE s done n Secton 3 The measurements ssues over GPRS-EDGE networks are presented n Secton 4 An algorthm whch deals wth the matters presented n Secton 4 s explaned n Secton 5 The mplemented measurement system s explaned n Secton 6 Some results obtaned wth ths system are presented n Secton 7 In Secton 8, the nfluence of the transport layer protocols on the throughput measurement s studed Fnally, the paper s concluded n Sectons 9 and 10 2 RELATED WORKS The man research topcs on end-to-end measurements on

the Internet are: Lnk capacty or bottleneck lnk capacty estmaton n a network path There are many suggested procedures n order to estmate the capacty of a wred lnk Man technques are based on sendng fxed sze probe packet pars At the recever the nter-arrval tme s analyzed and, knowng the packet sze, the bottleneck capacty s estmated Each technque fts better dependng on the characterstcs of the path and the cross traffc In general, all technques work f there s not cross traffc However, n a heavy loaded network or n a path wth cross traffc n many lnks, the errors n the estmaton can be mportant [10] Cross traffc s defned as packets whch belongs to other connectons whch nterferes wth probe packets Internet tomography The goal of Internet tomography s to estmate lnk QoS parameters from end-to-end estmatons of these parameters [1, 3, 5, 6, 11, 14, 18] These works are related to the subject studed n ths paper, because they contrbute wth methodologes and deas to measure some end-to-end parameters However, they do not solve the problems that arse n wreless networks Lnk or path avalable bandwdth" measurement The avalable bandwdth (ABW) of a lnk n the tme nterval (t, t + τ) s A (t, t + τ) = C (1 u (t, t + τ)) (1) where C s the lnk capacty and u (t, t + τ) s the average lnk utlzaton n the tme nterval (t, t + τ) The mnmum A n the path s defned as the ABW of the path There are many developed algorthms to estmate the avalable bandwdth Pathload [7, 9, 8], PathChrp [15] and Spruce [17] are mportant examples of dfferent technques Strauss et al [17] compare Spruce wth other tools used to estmate the ABW, lke Pathload All these works are based on wred networks, where each lnk capacty s fxed and the packets share each lnk n a FIFO queue Ths work bulds a methodology that can be used for end-to-end performance estmaton over cellular networks, where the prevous assumptons are not necessarly true 3 WIRELESS LINK PERFORMANCE MEA- SURES Ths work s focused on the estmaton of the followng parameters Instantaneous lnk capacty Mean lnk capacty Actvty nterval tme Total throughput Mean throughput n an actvty nterval tme Round Trp Tme (RTT) Jtter These parameters wll be estmated by sendng probe packet pars of constant sze ϖ at constant rate The nter-arrval tme between pars at the clent s t In the followng subsectons the meanng of these parameters s explaned 31 Instantaneous lnk capacty In ths work, the rato between probe packet sze and nterarrval tme between two probe packets that were queued together n the lnk s called nstantaneous lnk capacty 32 Mean lnk capacty It s the sum of the nstantaneous lnk capacty multpled by the nterval tme n whch occurs, over the sum of these tme ntervals C = P C t P t 33 Actvty nterval tme In a TDMA (Tme Dvson Multple Access) system, each clent uses the channel durng a certan perod of tme that, n ths work, s called actvty nterval tme 34 Total throughput Total throughput s defned as the amount of data transferred over the transference tme 35 Mean throughput n an actvty nterval tme The average throughput of all the actvty nterval tmes s called mean throughput n an actvty nterval tme 36 Channel actvty tme Channel actvty tme s defned as: P Tactvty Act = (3) T tot where T actvty represents a gven actvty nterval tme and T tot s the total tme of the experment Ths parameter s mportant because t shows the tme percentage durng whch the clent had the channel 37 Packet loss The packet loss s defned as: (2) Loss = 1 P rc P ss (4) where P rc s the number of packets receved by the clent and P ss s the number of packets sent by the server 38 RTT The tme elapsed taken for an IP packet to travel to a remote place an back agan s called RTT 39 Jtter The varaton of succesve values of RTT s called Jtter Channel actvty tme Packet loss

4 MEASUREMENT METHODOLOGY 41 Measurement technque In each experment probe packets are sent at a constant rate for a short tme perod In order to estmate the nstantaneous bottleneck lnk capacty, probe packets must be enqueued together n the rado access buffer (assumng that the wreless lnk s the bottleneck) The packet rate to accomplsh ths s chosen as the maxmum moble capacty (that depends on the moble class) There s a tradeoff n the selecton of the probe packet sze The accuracy n the analsys of each actvty nterval tme s mportant In order to have more samples n each actvty nterval tme t s necessary to send packets wth the smallest sze allowed However, n order to have less uncertanty n the capacty estmaton from the measures of the nter-arrval tmes, t s preferred to use as bg as possble packet szes The tme stamp absolute error s around 1 ms To solve ths tradeoff packet szes around 300 500 bytes are used These szes are the smallest that provde a capacty estmaton relatve error lower than 10% for the bggest GPRS- EDGE capactes that are around 120 240 kbps Next subsecton summarzes the most common used methodologes for wred lnk capacty estmaton In subsecton 43 wreless lnk capacty estmaton problems are explaned 42 Bottleneck lnk capacty estmaton For each packet par the lnk capacty can be estmated as ϖ, where ϖ s the packets sze and t s the nter-arrval t tme between consecutve packets at the clent After ths estmaton, the values obtaned for each packet par are classfed for further processng By ths processng a fnal capacty s estmated If a par of packets (wth packet sze ϖ) wat together n the bottleneck lnk buffer (wth lnk capacty C), and n not any other lnk, the tme between arrvals s ϖ One C mportant ssue to pont out s that packet par estmaton capacty may be dstorted by cross traffc or by lmtatons on the measurement system There are two stuatons that may affect the measurements The frst stuaton happens f there s cross traffc between probe packets In ths case they wll be separated a tme T, whch s larger than the separaton mposed by the bottleneck capacty In ths case the system wll estmate a fake bottleneck capacty C < C The other stuaton happens when the probe packets wat n queues after the bottleneck lnk In ths case they wll jon together yeldng a fake bottleneck capacty C > C These effects are llustrated n fgure 1 These cases must be fltered The capacty estmaton wll be more accurate f the bottleneck lnk s not heavy loaded by cross traffc and the last queue of the path s at the bottleneck lnk Several technques are used for processng packets pars and estmate the capacty, flterng the cases explaned before Usually, hstogram classfcaton or kernel densty estmaton are used Pathrate [4] and Nettmer [10] use these technques The man dea of these algorthms s to estmate the capacty by fndng the maxmum of the dstrbuton (or hstogram) Ths value represents the estmated capacty that occurs more frequently Fgure 1: Cross traffc effect on bottleneck capacty measures Multclass Slot DL Slots UL Slots Actve Slots 1 1 1 2 2 2 1 3 3 2 2 3 9 3 2 5 10 4 2 5 Table 1: Moble classfcaton by ts multclass slot type 43 Wreless TDMA systems ssues 431 Introducton In general, n cellular networks, the bottleneck s located on the ar nterface In addton to the problems explaned before n the case wred lnk capacty estmaton, the followng ssues arse n the case of cellular wreless lnks: Moble class Carrer to nterference ( c ) relaton Avalable tme slots for data transfer n the servng cell Moble class The moble class s a classfcaton between dfferent types of termnals whch determnes how many smultaneous tme slots can be used by the clent n order to transfer data Table 1 lsts most commonly used class types and the number of tme slots used for download (DL) and upload (UL) n each class Carrer to nterference relaton Carrer to nterference relaton ` c s the parameter whch determnes the effectve rate of data transfer per tme slot When c relaton s small, the error probablty durng the transfer s hgh In order to avod ths problem, when c relaton s small, more redundancy bts are used The more redundancy bts are used to transfer nformaton, the less s the nformaton rate per tme slot Table 2 lst dfferent avalable code schemes n EDGE (MCS) Avalable tme slots for data transfer The servce provder confgures the number of avalable tme slots for data transfer n the cell So, some of the confgu-

MCS BW per TS (at layer 2, n kbps) 1 88 2 112 3 148 8 544 9 592 Table 2: Dfferent code schemes n EDGE Data User 1 Data User N Voce Users (GSM) C V V D OD OD OD OD C: Control channel V: Voce (GSM) channel D: Data channel OD: On demand channel (between voce and data) Fgure 2: Typcal GPRS-EDGE queueng system raton varables n the cell are the number of fxed tme slots assgned to data transfer, the number of fxed tme slots assgned to voce traffc and the number of on-demand tme slots between voce and data Usually, for the ondemand tme slots, voce calls has preemptve prorty over data transfers Cellular lnk capacty can not be estmated usng the same procedures as n the wred lnks case because cellular lnks may have capacty tme varatons Ths problem s analyzed n more detal n the followng subsecton 432 GPRS-EDGE Queueng System Fgure 2 shows a typcal GPRS-EDGE queueng system As t can be seen, ths system may nclude nteracton between voce and data users There are multple factors that mpact on the capacty estmaton In the followng paragraphs dfferent stuatons are analyzed n order of complexty Number of GSM users are less or equal than fxed voce slots, there s only one data user n the cell and a fxed relaton s assumed c In ths case, voce users do not use on-demand tme slots All data tme slots are avalable for the clent Therefore, the clent has all data resources avalable all the tme The capacty wll be only determned by the moble class and c relaton Assumng a fxed c relaton ths case s smlar to the classcal wred one, lke ADSL Number of GSM users are hgher than fxed voce slots, there s only one data user n the cell and a fxed c relaton s assumed In ths case there are more users than fxed voce slots assgned by the operator So, voce users need to use ondemand tme slots, and they have prorty over data users on these channels In ths case the data users can only use the fxed data tme slots and the on-demand tme slots that are not used for voce calls So, the capacty s determned c by the moble class, relaton and on-demand tme slots avalablty (nstantaneously determned by the amount of voce calls) In ths case the lnk capacty s modulated by voce traffc Number of GSM users are less or equal than fxed voce slots, the clent shares the channel wth other data users and a fxed c relaton s assumed In ths case the clent s sharng data resources wth other data users Thus, each data user does not have the channel for hs own use all the tme Ths case can be seen as a fxed capacty system (assumng a fxed number of users transmttng all the tme wth a fxed c relaton) shared n tme wth other data users Number of GSM users are hgher than fxed voce slots, the clent shares the channel wth other data users and a fxed c relaton s assumed Ths s a more realstc case whch can be seen as the superposton of the two cases mentoned before So, n ths case the lnk capacty s modulated by voce traffc and shared n tme wth other data users More complex cases A more realstc model s obtaned by the superposton of all the above mentoned varables, whch ncludes varaton of data and voce traffc and c relaton Another relevant effect s cross traffc nserted n the channel by the data clent (another knd of traffc dfferent from the probe packets that may ntroduce certan level of nose on t) The followng algorthm deals wth ths stuaton 5 ALCE: AN ALGORITHM TO ESTIMATE CELLULAR LINK CAPACITY Ths algorthm s composed by dfferent modules man modules are the followng: 1 Actvty and nactvty ntervals classfcaton 2 Analyss of each actvty nterval The A Potental capactes detecton B Process of samples for each one of the capactes detected n A 3 Parameters estmaton 51 Actvty and nactvty ntervals classfcaton In order to fnd the actvty ntervals, an adaptaton of the K-means algorthm [2] was developed The algorthm calculates K 1 thresholds and classfes the packet par nter-arrval tme nto K groups, where K s supposed to be known In our case K = 2 represents the group of samples that belong to one actvty nterval (group 1) and the group of samples that denotes a change of actvty nterval (group 2) Once the executon of the algorthm s fnshed, the selected threshold s gven by T h Kmeans = g1 + g2 2 (5)

Fgure 3: Experment n whch actvty ntervals are clearly denoted Fgure 4: Experment n whch there s only one actvty nterval where g 1 and g 2 are the means of the groups 1 and 2 respectvely One partcular case s when durng the experment does not occur more than one actvty nterval Ths happens when the clent has the channel for hs own use In ths case, at the moment of dstngushng between actvty ntervals, f we run the pure K-means algorthm, an ncorrect dscrmnaton s done, dentfyng some dfferences of tme between consecutve packets as nactvty ntervals In order to solve ths problem a mnmum threshold s calculated when detectng the ntervals The tme between packet arrvals depends on the packet sze and on the nstantaneous capacty, so, a mnmum threshold, T h mn, s calculated based on ths parameters Applyng ths crteron, the fnal threshold appled to dfferentate between nactvty perods s gven by equaton 6 T hm = max {T h mn, T h Kmeans } (6) Fgure 3 shows the stuaton of a common experment, n whch actvty ntervals are clearly denoted and separated by nactvty ntervals On the other hand, fgure 4 shows an experment n whch there are not any nactvty ntervals,so, the adaptaton of the K-means algorthm s necessary to obtan vald results As an example, f we run the pure K-means algorthm, fgure 5 shows how a great number of false nactvty ntervals are detected 52 Actvty nterval analyss After detectng actvty ntervals, the algorthm proceeds to analyze each one of them The flow dagram of ths module s shown n fgure 6 521 Potental capactes detecton Potental capactes of each actvty nterval are detected based on kernel densty estmaton technque [16, 19] The man dea of ths technque s the followng Gven a fnte sequence of n samples, X 1,, X n, the algorthm estmates Fgure 5: Pure K-means algorthm fnds many fake nactvty ntervals the densty functon f(t) as ˆf(t) = 1 nx «t X K nh h =1 where K s a kernel functon and h s the bandwdth The kernel has the followng propertes Z (7) K(t)dt = 1, K(t) 0 (8) The Kernel used n the algorthm s the Epanechnkov Kernel, defned as where K(t) = 3 4 (1 t2 )I t <1 (9) I t <1 = j 1 f t < 1 0 n other case The optmum Epanechnkov kernel bandwdth h s gven

START Are ntervals? NO END YES Densty functon of the nterval Remove packets from these sub ntervals Fnd maxmums of the densty functon Mark sub ntervals wth ths capacty NO Are maxmums? Take the maxmum of greatest bandwdth avalable Fgure 7: Capacty detecton n presence of low level of nose YES Fgure 6: Flow dagram of the actvty nterval analyss by the followng equaton h opt = (40) 1/5 π 1/10 s n n 1/5 (10) where s n represents the standard devaton of the samples s n = 1 n! 1/2 nx (X X) 2 =1 (11) After the densty functon s obtaned the algorthm proceeds to fnd ts maxmums, beng these ponts the potental capactes durng the actvty nterval 522 Samples processng to avod false potental capactes detected In ths module, the algorthm evaluates f these potental capactes really correspond to an actvty nterval In order to dscard false capactes a set of rules are appled to the potental capactes For example, rules to avod capactes that are not possble n a cellular wreless lnk, rules to avod spurous measurements or rules to take nto account capacty varatons due to the lmted accuracy of the measurement procedure can be consdered At the end of ths procedure all vald capactes n the actvty nterval of study are saved The process s repeated wth the next actvty nterval untl there are no more actvty ntervals to analyze When ths module s fnshed, the algorthm executes the followng one Fgure 7 shows a common stuaton n the analyss of an actvty nterval In ths case, a great quantty of samples regster the same capacty However, the presence of certan solated samples whch are far from ths value could nduce to thnk, at frst sght, n the presence of many capactes durng the actvty nterval However, due to the rules mposed to flter spurous capactes, the algorthm dentfes these solated ponts as nvald measurements done by the Fgure 8: accuracy Capacty varatons due to tme stamps system or measures affected by cross traffc For these reasons the algorthm behaves as shown n fgure 7 In fgure 8 a partcular case s shown In ths experment the nstantaneous lnk capacty oscllates between 120 and 109 kbps Ths stuaton s probably caused by the accuracy n the tme stamps Partcularly, n ths case, the experment was done wth a packet sze of 300 bytes, whle the regstered nter-arrval tme were between 22 and 20 ms However, t s reasonable to suppose that the packets arrved at the clent at a rate between 22 and 20 ms Ths means that the real capacty s between 120 and 109 kbps It can be seen how, by the applcaton of the kernel densty estmaton, the fnal capacty s detected at 113 kbps Fgure 9 shows a case n whch the experment was done under several nose condtons As t can be seen t s not easy to fnd the real lnk capacty Under these condtons the capacty estmaton would have large uncertanty, so the algorthm does not mark any capacty

Fgure 9: Capacty detecton wth hgh level of nose The algorthm s not able to dstngush any capacty Fgure 10: Network measurement system 6 IMPLEMENTED MEASUREMENT SYS- TEM The mplemented measurement system conssts of a server runnng Lnux and a Servlet The clent can use an Applet (f the clent s usng a GPRS-EDGE modem) or a Mdlet (f the clent s usng a cellular phone only) Fgure 10 shows a dagram of the measurement system The system archtecture s explaned n more detal n [12] The measures are done n two phases: Phase I: Edge router deceve Phase II: Experment 61 Phase I: Edge router deceve The local GPRS-EDGE provder assgns IP addresses to ts clents from a prvate pool through an edge router applyng NAT 1 For ths reason, t s necessary to fnd a way to establsh the communcaton between the Internet server and the clent n order to make the correspondng measurements Ths frst phase deceves the edge router n order to establsh a path from the server to the clent 1 Network Address Translaton At the begnnng of the experment, ts parameters are negotated between the clent (Applet or Mdlet) and the server va HTTP packets After ths negotaton, the server begns the experment by sendng UDP probe packets wth the chosen parameters Snce the ntal request for the experment s done by the clent, the edge router regster an exchange of HTTP packets from the clent (whch has a prvate IP address) to the server (wth a publc IP address) Once ths exchange s fnshed the server starts sendng UDP packets to the clent If the server sends the UDP probe packets to the prvate clent s IP, the packets wll be dscarded by the router If the server sends the probe packets to the edge router publc IP, the packets wll be dscarded, because the router does not know whch clent has requested these packets To solve ths problem, the system mplements the deceve phase In ths phase the clent sends false probe packets to the server mmedately after the HTTP negotaton By dong ths, a regster on the NAT table of the edge router assocates an UDP flow from the clent to the server n any gven par of ports The server reads the nformaton of ths UDP packets and starts the experment by sendng the probe UDP packets to the clent usng the ports chosen by the clent n the decevng phase In ths case, when the experment packets arrve at the edge router, a record on the NAT table exsts, so the router knows that ths flow belongs to the clent - server path and routes the packets correctly 62 Phase II: Experment The experment sends UDP packets from the server to the clent n order to gather the needed nformaton to run the prevous algorthm The packets sent from the server, are rebounded at the clent and receved by the server Ths packets contan useful nformaton for the algorthm as a sequence number and the arrval tme stamps at each end of the path 7 RESULTS Durng the tral perod, many experments were done under dfferent crcumstances The varables taken nto account were the place of the experment (cell of servce), c relaton, hour of the day and the moble type Experments were done wth two mobles, Moble A and Moble B Both were used as modems, connected to a PC and usng the Applet as the clent software or as a moble clent, usng the Mdlet as the clent software The places chosen to run the experments were dfferent neghborhoods of Montevdeo (Punta Carretas, Malvín, La Blanqueada and Palermo) and a seasde (Playa Hermosa) 71 Mean capacty Table 3 shows maxmum, mean and mnmum values of capactes regstered durng the experments Punta Carretas, Palermo and Playa Hermosa (PH) were the chosen places, and the measures were done usng Moble A In these experments was observed that under normal traffc condtons mean capactes were between 190 and 220 kbps These results reveal that Moble A obtans, n general, four tme slots for download wth code scheme between MCS-6 and MCS-9 Fgure 11 shows experments made n Playa Hermosa In ths case the pattern of mean capactes on the frst three days of experments done n the afternoon were greater than

Place of Mean Mn Max study capacty capacty capacty (kbps) (kbps) (kbps) P Carretas 200 167 212 Palermo 202 187 224 PH - Afternoon 196 142 216 PH - Nght 142 115 203 Table 3: Mean capactes regstered by place wth Moble A Fgure 12: Mean capacty wth moble B (cross) and A (crcles) Fgure 11: Mean capacty n kbps n Playa Hermosa s cell wth Moble A the mean capactes regstered at nght Ths s because the experments were done durng a holday weekend n a seasde, and at nght the voce traffc s more mportant Also, t can be seen that ths phenomenon s not apprecated the last day of the holday, because the majorty of the people had returned to ther resdence ctes Fgure 12 shows the capacty obtaned wth both mobles n Malvín As t can be seen, mean capactes regstered wth moble B are much smaller than the ones regstered wth Moble A Dong several experments n dfferent hours and places, the nfluence of factors lke cell of servce or the tme of the experment were dscarded; then such behavor was caused by the type of moble used 72 Channel Actvty tme As mentoned n Secton 3, channel actvty tme s an ndcator of the amount of tme that the clent s usng the resources Fgure 13 shows the channel actvty tme regstered wth both mobles As t can be seen, channel actvty tme of moble B was bgger than channel actvty tme of moble A 73 RTT After the experment phase was fnshed, we concluded that the delays regstered on the network were hgh n order to provde real tme applcatons Values obtaned wth both mobles were dfferent, as t can be seen n table 4 Cell of servce also have nfluence over the RTT obtaned, because of the c relaton or the amount Fgure 13: Moble B (cross) and Moble A channel (crcle) actvty tme of traffc on t, as table 5 shows 74 Jtter From the experments done we conclude, as expected, that regstered jtter s tghtly related to RTT Table 6 shows values obtaned n dfferent places Ths range of values ental that certan servces whch requre low jtter values, lke Push To Talk, suffer a hgh degradaton of performance 75 Packets loss The regstered loss n the majorty of cases was between 0 and 4 % of packets sent However, n some experments ths rato was above 10 %

Moble Mean Mn Max used RTT (ms) RTT (ms) RTT (ms) Moble A 1329 833 2318 Moble B 897 709 1803 Place of Mean Mn Max study Jtter (ms) Jtter (ms) Jtter (ms) P Hermosa 36 22 92 P Carretas 23 5 57 Table 4: Regstered RTT n Punta Carretas cell wth both mobles Table 6: Jtter obtaned n dfferent places wth moble A Place of Mean Mn Max study RTT (ms) RTT (ms) RTT (ms) P Hermosa 2376 920 8043 P Carretas 1329 833 2318 INTERNET Rado base staton GPRS-EDGE Clent Table 5: RTT obtaned n dfferent places wth moble A 8 THROUGHPUT VS CAPACITY: INFLU- ENCE OF THE TRANSPORT LAYER PRO- TOCOL AND THE ROUND TRIP TIME The prevous secton analyzes the cellular lnk capacty and other mportant performance parameters The focus of ths secton s on the throughput The throughput s an mportant parameter at the applcaton layer Even f the system has hgh capacty, such capacty can not be used unless a hgh throughput s acheeved Lnk throughput s an estmator of data transfer rate that an applcaton can acheve, whereas capacty refers to the real physcal capacty of the access medum Takng these consderatons nto account, the maxmum throughput that an user could acheve s equal to the lnk capacty There are many parameters that nfluence the throughput The capacty of the bottleneck lnk s an mportant parameter, but the RTT and the transport layer protocol have an mportant nfluence too In our experments the throughput obtaned by a GPRS- EDGE connecton s n many cases, more than two tmes lower than the bottleneck lnk capacty The problem to analyze s why there s such a bg dfference Wth ths purpose, several measures have been done drectly on the net, usng dfferent knds of traffc between a server and a moble c clent Fgure 14 shows the topology used on the experments The clent has a GPRS-EDGE modem, whle n the other sde of the communcaton resdes an FTP server, from whch dfferent fle transfers and measurements have been done All measurements have been done late at nght Ths perod was chosen n order to assume a low charge of the cellular network relaton was hgh enough to ensure that durng all the experments use EDGE channels wth hgh MCS Wth these assumptons, t s supposed that the clent wll acheve hgh transfer rates 81 Study of throughput for TCP traffc n the downlnk In ths experment multple large fles were downloaded, studyng acheved throughput by the user (fgure 15) To do such measurements we have used a traffc snf- FTP Server Fgure 14: Measurement topology fer on users termnal (Ethereal) and a software that montors the rate of bts that arrves to the modem (NetStat Lve) At frst, one download was done, studyng statonary acheved throughput Then the number of smultaneous downloads was ncreased, studyng agan the aggregated statonary throughput Ths procedure was contnued untl aggregated throughput stop rsng 82 Study of capacty and throughput n uplnk for dfferent types of traffc In ths experment a tool for capacty estmaton was used, Iperf Ths tool s based on TCP and UDP traffc n order to measure real uplnk capacty and acheved uplnk throughput for the clent for dfferent knds of traffc Estmatons obtaned wth ths tool depend on the knd of traffc whch s used In the case that ths traffc s UDP, estmaton conssts n sendng one or more bursts of UDP flows from the clent to the server, floodng the lnk and analyzng the packets n the server, as shown n fgure 16 In case that ths traffc s TCP, one or more of TCP connectons are opened, determnng aggregated throughput at the server, as shown n fgure 17 83 Results 831 Study of throughput for TCP traffc n the downlnk The number of FTP transferences done, n chronologcal order, was: 1 fle, 2 fles, 3 fles, 5 fles, 1 fle, 4 fles and 5 fles Fgure 17 shows the acheved throughput for each case Table 7 shows acheved throughput n the experment varyng the number of FTP transferences Ths experment shows how the acheved throughput from a sngle TCP connecton dd not reach channel capacty The lnk capacty s around 180 kbps, because the moble was usng 3 slots for download (3+2 confguraton) Ths case shows that one connecton can acheve only a thrd of

FTP N FTP 2 INTERNET FTP 1 GPRS-EDGE Clent Fgure 15: Downlnk TCP throughput FTP Server Numb of FTP Throughput transferences (kbps) 1 58,3 2 96,1 3 135,6 5 161,5 1 64,8 4 146,2 5 158,5 Iperf clent UDP Flow Iperf server Table 7: Throughput estmaton through smultaneous FTP downloads INTERNET Server traffc and dfferent number of connectons/flows GPRS-EDGE Clent Fgure 16: Uplnk throughput the lnk capacty However, ths value could be ncreased by openng some smultaneous connectons For fve smultaneous connectons acheved throughput s close to the lnk capacty It s known that TCP throughput cannot be equal to the lnk capacty because ts congeston control algorthm decreases the throughput However, n ths case the dfference seems to be mportant The problem s that TCP throughput s nversely proportonal to the RTT [13] As t can be seen n Table 5, n all cases the RTT s hgh compared to usual values obtaned n typcal wred lnks The RTT s normally hgh n cellular networks and ths value generates the small throughput that can be obtaned by one connecton 832 Study of capacty and throughput n uplnk for dfferent types of traffc Tables 8 and 9 summarzes estmatons for both knds of Number of TCP Estmaton connectons (kbps) 1 56,3 2 74,2 3 91,5 Table 8: Estmaton of uplnk capacty wth Iperf usng TCP connectons Number of UDP flows Estmaton flows (kbps) 1 114 2 112 3 117 Table 9: Estmaton of uplnk capacty wth Iperf usng UDP flows Throughput (kbps) 180 160 140 120 100 80 60 T = 135,6 kbps T = 96,1 kbps T = 161,5 kbps T = 58,3 kbps T = 64,8 kbps 40 Fgure 17: Downlnk throughput durng the experment T = 146,2 kbps T = 158,5 kbps 20 0 50 100 150 200 250 300 350 400 Samples To analyze the results, t s mportant to consder the characterstcs of the dfferent knds of traffc In the case of UDP traffc, estmatons are equal to the uplnk capacty, ndependently of the number of flows In the case of TCP traffc, all the results obtaned were the same as n downlnk, only one connecton acheved a lower throughput than a few smultaneous connectons In ths sense, capacty estmaton usng TCP traffc s not recommended For ths reason, t was mplemented n the system end-to-end measurements usng UDP packets 9 CONCLUSIONS In ths work we have ntroduced both, an end-to-end measurement system and a specfc algorthm to measure performance parameters n TDMA based IP networks, partcularly on GPRS-EDGE Ths algorthm has the partcularty of beng specfcally desgned for the analyss of the GPRS-

EDGE protocol, obtanng bg amounts of nformaton for t Several experments have been done n order to test the robustness of the system and the algorthm, obtanng good results Due to ths results we have done an extensve measurement on a GPRS-EDGE network, gettng to know ts man characterstcs The developed system can be used through any GPRS- EDGE network The only requrement s to have a Java Vrtual Machne nstalled on the clent (n case that the clent s connected to the GPRS-EDGE network through a modem) or a Java capable moble 10 ACKNOWLEDGMENTS Ths work was supported by the Programa de Desarrollo Tecnologco (PDT), project S/C/OP/46/03, MetroNet II The authors would lke to thank ANTEL (Admnstracón Naconal de Telecomuncacones), and Laura Asprot for all the support gven to the project 11 REFERENCES [1] M Adler, T Bu, R Staraman, and D Towsley Tree layout for nternal network characterzatons n multcast networks NGC 01: Proceedngs of the Thrd Internatonal COST264 Workshop on Networked Group Communcaton, pages 189 204, 2001 [2] F Bon Técncas no supervsadas Métodos de agrupamento course notes from unversdad de granada 2001 [3] R Cáceres, N G Duffeld, Horowtz, and D Towsley Multcast-based nference of networknternal loss characterstcs IEEE Transactons on Informaton Theory Vol 45, pages 2462 2480, 1999 [4] C Dovrols, P Ramanathan, and D Moore What do packet dspersson technques measure? Infocom, pages 905 914, 2001 [5] A Downey Usng pathchar to estmate nternet lnk characterstcs Measurement and Modelng of Computer Systems, pages 222 223, 1999 [6] V Jacobson Pathchar, a tool to nfer characterstcs of nternet path Presented at the mathematcal scences research nsttute 1997 [7] M Jan and C Dovrols Pathload: A measurement tool for end-to-end avalable bandwdth Proceedngs of Passve and Actve Measurements (PAM), pages 14 25, 2002 [8] M Jan and C Dovrols Pathload: A measurement tool for end-to-end avalable bandwdth In Proceedngs of Passve and Actve Measurements (PAM) Workshop, 2002 [9] M Jan and C Dovrols End-to-end avalable bandwdth: measurement methodology, dynamcs, and relaton wth TCP throughput IEEE/ACM Transactons n Networkng, 2003 [10] K La and M Baker Nettmer: A tool for measurng bottleneck lnk bandwdth Proceedngs of the USENIX Symposum on Internet Technologes and Systems, 2001 [11] E Lawrence, G Mchalds, and V N Nar Inference of network delay dstrbutons usng the EM algorthm Techncal Report, Unversty of Mchgan, 2003 [12] J A Negrera, J Perera, and S Pérez MetroCel: Estmacón de performance sobre enlaces GPRS-EDGE, 2007 http://efngeduuy/ javerp/metrocel [13] J Padhye, V Frou, D Towsley, and J Kurose Modelng TCP throughput: A smple model and ts emprcal valdaton Proceedngs of the ACM SIGCOMM 98 conference on applcatons, technologes, archtectures, and protocols for computer communcaton, pages 303 314, 1998 [14] F L Prest, N G Duffeld, J Horowtz, and D Towsley Multcast-based nference of network-nternal delay dstrbutons ACM/IEEE Transactons on Networkng Vol 10, pages 761 775, 2002 [15] V Rbero, R Red, R Baranuk, J N J, and L Cotrell PathChrp: Effcent avalable bandwdth estmaton for network paths Passve and Actve Measurement Workshop, 2003 [16] B Slverman Densty estmaton for stadstcs and data analyss 1986 [17] J Strauss, D Katab, and F Kaashoek A measurement study of avalable bandwdth estmaton tools Internet Measurement Workshop, Proceedngs of the 2003 ACM SIGCOMM conference on Internet measurement, pages 39 44, 2003 [18] Y Tsang, M Coates, and R Nowak Network delay tomography IEEE Transactons on Sgnal Processng Vol 51, pages 2125 2136, 2003 [19] B A Turlach Bandwdth selecton n kernel densty estmaton A revew, Dscusson Paper 9317, Insttut de Statstque, Voe du Roman Pays 34, B-1348 Louvan-la-Neuve, Belgum, 1993