Rapid Estimation Method for Data Capacity and Spectrum Efficiency in Cellular Networks

Size: px
Start display at page:

Download "Rapid Estimation Method for Data Capacity and Spectrum Efficiency in Cellular Networks"

Transcription

1 Rapd Estmaton ethod for Data Capacty and Spectrum Effcency n Cellular Networs C.F. Ball, E. Humburg, K. Ivanov, R. üllner Semens AG, Communcatons oble Networs unch, Germany carsten.ball@semens.com Abstract System level smulatons for dervng data capacty and spectrum effcency of cellular wreless networs requre comple modelng and a consderable computatonal effort. In ths paper a combned analytcal / geometrc approach has been proposed allowng rapd performance estmaton n cellular pacet data networs. Ths s accomplshed by mappng measured or smulated ln level curves onto measured or smulated cell C/I dstrbutons. Two dfferent scenaros have been studed related to two generc traffc models wdely used n the lterature. The frst traffc model assumes a fed average pacet data call duraton whereas the second one assumes a fed average pacet data volume per subscrber. Based on these models the frst scenaro provdes very optmstc whle the second one more pessmstc performance results. Both GS/EDGE and the upcomng new IEEE Wa system have been studed n 3 frequency reuse, showng a consderable dfference of nearly 50-60% n terms of spectrum effcency between both traffc models. The comparson of Wa wth GS/EDGE reveals a moderate performance advantage for the new broadband OFD system n the order of 20-40% hgher spectrum effcency. Keywords Spectrum Effcency, Performance, IEEE802.6, Wa, EDGE I. INTRODUCTION A combned analytcal / geometrc method for rapd estmaton of the pacet data channel capacty and spectrum effcency n cellular wreless systems s ntroduced. The proposed method has been appled to two scenaros correspondng to two generc traffc models leadng to totally dfferent performance results. The frst scenaro assumes equal pacet call duraton for all subscrbers. In cellular envronment ths leads to consderably dfferent data volumes transferred durng the fed tme nterval snce subscrbers under good rado condtons enjoy consderably hgher data rate than subscrbers under poor rado condtons. The resultng cell throughput and consequently the spectrum effcency are too optmstc. In realty such user behavor mght be justfed n cases, where subscrbers just spend a certan fed tme perod e.g. wth web-browsng n the Internet. The second scenaro assumes an equal data volume per subscrber. Such user behavor s observed e.g. wth download applcatons such as FTP servce or Aud-Vdeo-Streamng n drve tests. In ths case subscrbers under poor rado condtons wth low data rate occupy rado resources dsproportonately leadng to too pessmstc capacty and spectrum effcency results. Obvously n a real system mplementaton a certan mture of both traffc models s epected nducng performance results n between those provded by the studed traffc models. The proposed method s based on geometrc mappng of the measured or smulated ln level performance curves on the measured or smulated cell C/I dstrbuton. Appromatng the ln level curves by star-case functons smplfes the analytcal formulas used n the performance analyss. Detaled results for GS/EDGE [], [2] as well as for broadband IEEE AN (Wa, [3], [4]) are provded. However, there are some factors le power control, admsson control as well as specfc schedulng technques, whch cannot be taen nto account by the proposed analytcal method. But at full system load downln power control has only mnor nfluence on the cell C/I Cumulatve Dstrbuton Functon (CDF). Admsson control blocs subscrbers under very poor rado condtons avodng allocaton of channel resources n case of bad rado condtons. Furthermore the spectrum effcency can be sgnfcantly affected by means of sophstcated schedulng technques. For eample a mamum C/I scheduler gves preference to subscrbers under good rado condtons at the epense of those under moderate rado condtons thus ncreasng cell throughput and spectrum effcency whereas a proportonal farly weghted scheduler mproves the throughput of subscrbers under poor rado condtons thus degradng the overall spectrum effcency. The paper s structured as follows. Secton II descrbes the theoretcal bacground used for dervaton of analytcal formulas for the two scenaros under study concernng channel capacty and spectrum effcency. In Secton III a GS/EDGE system deployed n 3 frequency reuse has been analyzed based on measured ln level and smulated C/I CDF. Secton IV presents the data capacty and spectrum effcency acheved by a state-of-the-art IEEE Wa system assumng the same frequency reuse, smulated ln level and smulated C/I CDF. Fnally the man conclusons are drawn n Secton V. II. THEORETICAL BACKGROUND A. Spectrum Effcency In a cellular networ the spectrum effcency η gven n [bps/hz/cell] s defned by: CCell CCH η () r BCH NCH r BCH wth C Cell the cell/sector throughput n [bps], N CH the number of confgured channels per cell, B CH the channel bandwdth n [Hz] and r the frequency reuse. The cell throughput C Cell s the total of the N CH ndvdual channel throughputs C CH. In a cellular rado networ rado frequency channels are allocated to cells wth a certan reuse factor r characterzng

2 CS CS 2 CS 3 CS CS 2 CS 3 Channel Throughput [bps] F 3 F 2 ) f 3 () f 2 () Channel Throughput [bps] F 3 F 2 f 3 () h 2 (); ε 2 > 0 h 3 (); ε 3 0 f 2 () F F f () h (); ε > 0 f () Fg.. Eample for a ln level performance wth three CS. the robustness of the system aganst co-channel nterference. The quantty used to descrbe the qualty of the rado ln s the Carrer-to-Interference-Rato (C/I) gven n db. Dependng on the multple access scheme of the rado technology deployed n the networ a rado frequency channel features a well defned structure fed by the standard. Typcally the structure of the rado frequency channel reflects the way t s desgned to accommodate one or multple communcaton channels, n the followng termed channel. Typcally a channel conssts of e.g. TDA tmeslots and frames carryng resource unts. A GPRS/EDGE Pacet Data Channel (PDCH) carres a rado bloc, a Wa OFD frame conssts of OFD symbols. The resource unts are assgned by a scheduler to dfferent users multpleed on the same channel n the cell. Typcally the resource unts for an ndvdual user are assocated wth a certan modulaton and codng scheme (CS) eperencng a certan error rate ε( C / I) dependng on the qualty of the ndvdual rado ln. Ln Adaptaton (LA) s usually appled to adjust the CS to the varyng rado condtons mamzng the user throughput. Hence n general each partcular resource unt of the channel carres dfferent payload. The total channel capacty (channel throughput) s the rato of the average effectve (related to ε ) payload of the channel resource unts and the transmsson tme per resource unt. Obvously the hghest channel throughput and consequently the hghest spectrum effcency s obtaned n a system wth 00% channel utlzaton,.e. all resource unts of the channel are permanently busy carryng traffc data. B. Ln Level Performance State of the art mult-rate systems support dfferent modulaton and codng schemes CS wth,,. Fg. shows an eample wth three CS. Let s defne a functon f () descrbng the throughput of a channel eplotng CS at a carrer to nterference rato C / I [ db] assumng 00% channel utlzaton. The functon f () can be wrtten as: f ( ) F ( ε ( )) (2) wth F the nomnal throughput ( ε ( ) ) of a channel utlzng CS and ε () beng the error rate of CS at C/I [db] C/I [db] Fg. 2. Appromaton of f () by step functon h (). C / I. LA automatcally selects the most sutable CS for certan C ( t)/ I( t) ( t) at tme nstant t for a partcular rado ln thus provdng optmum throughput even for a tme varyng channel [5]. The optmum throughput curve s gven by the envelope of all f () : ) ma{ f ( )},,.,. (3) There are ( ) swtchng ponts due to LA correspondng to the ntersecton ponts of the functons f () : f ( ) f ( ), 2,,. (4) Hence accordng to LA, CS s n use n a C/I range of < +, 2,,. Snce by ths notaton both the lower bound for CS and the upper bound for CS are not specfed n the followng t s assumed that CS s used from 2 down to some lmted lower C/I value whle CS s used from up to an arbtrary hgh C/I. To facltate further analytcal approach let s ntroduce the vrtual swtchng ponts and +, defnng the lower bound for CS and the upper bound for CS, respectvely. To allow for smple calculatons each functon f (),,, reflectng the channel throughput utlzng codng scheme CS has been appromated over the respectve C/I nterval < +,,, by a step (Heavsde) functon h () as follows (refer also to Fg. 2): h ( ) F ( ε ) H const. for and (5) h ( ) 0 for <. Obvously the accuracy of appromaton n (5) and hence the value of H strongly depends on the constant error rate ε chosen to represent the real one over the relevant C/I nterval for the respectve CS. As suggested by Fg. 2 the best appromaton result wll be acheved usng the epectaton value (average error rate ε, refer to Secton D) of ε () over the nterval < +. C. Cell C/I Dstrbuton Fg. 3 llustrates an eample for a CDF of C/I obtaned by system level smulatons for a heagonal cell deployment n 3 reuse (r 3) at 00% channel utlzaton. The CDF

3 Fg. 3. Cell C/I CDF (300 m cell radus, 3 reuse, 3.5GHz band, 00% channel utlzaton, downln power control off). depends manly on cell geometry, antenna confguraton (heght and pattern) as well as the propagaton model. The RF output power plays no role n nterference lmted scenaros n tght reuse, f there are no coverage problems. Table I gves an overvew of the essental parameter settngs. In the followng the cell C/I CDF s denoted by P() and the correspondng probablty densty functon by ). appng the LA swtchng ponts on the cell C/I CDF gves the porton µ of users (assumng an unform user dstrbuton over the cell area) able to use a certan CS : µ ) d P( + ) P( ),,,. (6) + In partcular µ s gven by P( 2 ) and µ by.0 P( ) snce as above defned and +. Note that µ s not necessarly equvalent to the porton of channel resource unts havng a certan CS. Ths heavly depends on the assumed traffc model as demonstrated n the followng two smulaton scenaros. TABLE I. ESSENTIAL PARAETERS OF THE RADIO NETWORK ODEL Parameter Number of stes µ Ste-to-ste dstance Frequency reuse pattern Frequency band User dstrbuton Pathloss slope Propagaton odel BS RF TX power BS antenna oble antenna Power control (PC) Slow fadng std. devaton + P() Value 6 wrapped around on torus, 3 sectors per ste, heagonal deployment 900 m (300 m cell radus) 3.8 GHz / EDGE; 3.5 GHz / Wa unform, random postonng 38 db per decade COST W / EDGE; 2 W / Wa 65, 7.5 db, 35 m above ground, no down-tlt Omn, 0 db;.5 m above ground Downln PC swtched off 8 db D. Scenaro : Channel Capacty for equal mean Pacet Call Duraton per User In the frst scenaro a traffc model s assumed, where all users occupy the channel resources for the same average tme perod ndependent of the ndvdually assgned CS and the eperenced error rate ε. The scenaro s smlar to a P ( ) p ( ) d conventonal voce traffc model havng a fed mean call holdng tme. The drawbac of the model s gven by the fact, that dfferent users obtan dfferent data volumes, e.g. users at the cell edge sufferng from poor rado condtons get sgnfcantly less data volume than users close to the base staton. The advantage of the model s ts smplcty. Obvously the C/I dstrbuton of the channel resource unts p () s dentcal to the C/I dstrbuton of the users ) and consequently the porton α of the channel resource unts havng CS corresponds to the porton µ of users able to use CS : α + + p ( ) d ) d. (7) Usng (6) t follows: α µ P( + ) P( ). The average error rate ε for CS over the nterval < + s: + ε ) ε ( ) d. (8) α The channel capacty C CH n (3) s derved by mappng the envelope g () of the throughput functons f () on the cell C/I CDF: + C ) ) d ) f ( ) d. (9) CH Usng (2) and (8) yelds: C CH + ) F ( ε ( )) d α F ( ε ). (0) Applyng the step functon appromaton for the throughput vs. C/I curves from (5) the followng easy calculaton formula has been obtaned: C α H µ H. () CH Eample: assume two user types sharng the same fully loaded channel, user type a wth µ a ½ and a ) H a 0 bps and type b wth µ b ½ and b ) H b 20 bps. Wth () the channel capacty s gven by the arthmetc mean and results n C CH ½ * 0 bps + ½ * 20 bps 5 bps. Gven the nomnal payload L, of a resource unt utlzng CS the average data payload the channel s gven by: L α L L of the resource unts on ( ε α H T µ H T (2), ) wth T the tme duraton of the resource unt. E. Scenaro I: Channel Capacty for equal mean Pacet Call Data Volume per User The second scenaro s based on a traffc model wth a fed mean data volume V per pacet call ndependent of the rado ln qualty of the dfferent users. The C/I dstrbuton of the users s stll gven by ) and the porton of users havng

4 CS s defned by µ accordng to (6). The dstrbuton p () of the channel resource unts, however, s not equal to the C/I dstrbuton of the users ) anymore, because users under poor rado condtons requre sgnfcantly more channel resources than users e.g. close to the base staton n order to transfer the same data volume V. An eample wth user type a at C/I a and user b at C/I b leads to the requred number of channel resource unts N,a and N,b respectvely: V N, a a ) T N, a and. (3) V N ), b a N, b b ) T b ) Hence the dstrbuton p () of the resource unts can be derved from )by the followng probablty transformaton: ) y) p ( ) wth Z ) Z dy. (4) y) The porton α of the channel resource unts havng CS leads to: α Z + + p ( ) d + ) d. F ( ε ( )) ) d ) Z Z + ) d f ( ) (5) Applyng the step functon appromaton from (5) and usng (8) the followng easy calculaton formula has been obtaned: µ µ ( F ( ε )) H α. (6) ( F ε H ( )) The capacty of the shared channel wth fed mean data volume s then defned by: CCH p ( ) ) d ) d Z. (7) Z The step functon appromaton accordng to (5) leads to: CCH. (8) ( F ( ε )) H The average data payload per resource unt s gven by: T L. (9) ( L ( ε H, )) The eample n Secton D wth two types of users sharng the same fully loaded channel user type a wth µ a ½ and a ) H a 0 bps and type b wth µ b ½ and b ) H b 20 bps leads wth (8) to a channel capacty of C CH (½ / 0 bps + ½ / 20 bps) bps. Wth (6) α a ½ / 0 bps 3.33 bps 0.66 and α b ½ / 20 bps 3.33 bps 0.33, thus, n contrast to the eample above wth fed mean pacet call duraton, the CS utlzaton per resource unt wth the fed mean data volume model s not equal. The rato α a / α b 2 / s recprocal to the rato H a / H b of the assumed nomnal data rates. III. NUERICAL RESULTS FOR GS/EDGE GS/EDGE supports 9 modulaton and codng schemes CS,, CS 9 utlzng both GSK and 8-PSK and provdng RLC data rates up to 59.2 bps per PDCH. Fg. 4 on the rght hand sde shows the measured end-to-end applcaton throughput per PDCH vs. C/I for all CS. Applcaton throughput means that all overhead ncludng TCP/IP and LLC headers are ncluded reducng the pea user data rates by roughly 3-5%. The measurements have been conducted on downln statc/statonary AWGN channel wth commercally avalable handset and a GSK modulated co-channel nterferer wth random payload. Ln level results based on other channel models such as TU3 or TU50 have been publshed n [6] and could also be used. In addton the statc/statonary throughput vs. C/I curves have been optmstcally appromated (assumng ε 0) by step functons H as outlned n Secton II. appng the eght LA swtchng ponts onto the cell C/I CDF for 3 reuse n Fg. 4 on the left hand sde provdes the portons µ of users to whch LA wll assgn CS accordng to the eperenced C/I at the partcular cell locaton. All data necessary for the calculatons of channel capacty and spectrum effcency by usng (), (8), and () have been collected n Table II. Obvously the 8-PSK CS (CS 5,, CS 9 ) are domnantly n use wth more than 75% vs. 25% GSK modulaton even for tght 3 frequency reuse. TABLE II. ESSENTIAL EDGE DATA FOR FURTHER PROCESSING CS [db] µ H [bps] NA A. Traffc odel wth fed mean Pacet Call Duraton Insertng the data from Table II nto equaton () the channel capacty of an EDGE PDCH s obtaned for the traffc model wth fed mean pacet call duraton: 9 9 CPDCH α H µ H 35.75bps. The average data payload per resource unt s calculated accordng to (2) usng EDGE rado blocs wth four TDA frame rectangular nterleavng duraton T of 20 ms to: L C T 35.75bps 20ms 75bt. PDCH

5 µ (20%) µ (20%) µ 7 0. (0%) µ (20%) µ (5%) µ (7%) µ (6%) µ (7%) µ 0.05 (5%) Applcaton Throughput [b/s] Η 2 Η Η 5 Η Η 4 3 Η 7 Η 6 Η 9 Η C/I [db] Fg. 4. appng of a measured GS/EDGE ln level wth appromaton by step functons (rght) on the cell C/I CDF for 3 reuse (left) at full load. The spectrum effcency s calculated for frequency reuse r 3 CS 6/7 on 64-QA. Data rates rangng from.5 bps up to accordng to (). The rado channel spacng n GS s bps are feasble n a 3.5 Hz channel. Hz. Thus the channel bandwdth of the EDGE PDCH s B PDCH Smlar to Fg. 4 the statc/statonary throughput vs. C/I curves 200 Hz / 8 25 Hz, snce the GS carrer ncludes eght have been optmstcally appromated n Fg. 5 by step tmeslots and one PDCH occupes one tmeslot. functons H (assumng ε 0) as outlned n Secton II. CPDCH 35.75bps η 0.47bps / Hz / Cell. appng the s LA swtchng ponts onto the cell C/I CDF r BPDCH 3 25Hz for 3 reuse n Fg. 5 on the left hand sde provdes the portons µ B. Traffc odel wth fed mean Pacet Call Volume of users to whch LA wll assgn CS accordng to the eperenced C/I at the partcular cell locaton. All data Usng (8) and (9) and the data n Table II the EDGE necessary for the calculatons of channel capacty and channel capacty and average payload per rado bloc have spectrum effcency by usng (), (8), and () have been been calculated n case of a fed mean data volume per user collected n Table III. as follows: TABLE III. ESSENTIAL WIAX DATA FOR FURTHER PROCESSING CPDCH bps and 9 µ CS [db] µ H [bps] H NA L CPDCH T 24.82bps 20ms 496bt. Tang nto account the PDCH bandwdth of 25 Hz (refer to the comments above) the correspondng spectrum effcency s gven by (): CPDCH 24.82b/ s η 0.33bps / Hz / Cell. r BPDCH 3 25Hz As epected the channel capacty as well as the spectrum effcency for EDGE s sgnfcantly hgher for the traffc model wth fed mean pacet call duraton than those obtaned for the traffc model wth fed mean pacet call volume. The dfference n the results s nearly 50%. The EDGE results for the traffc model wth fed mean pacet call volume are fully n lne wth the system level smulaton results provded e.g. n [6] - [9]. Note that the results descrbed above are only vald for PDCH allocated on transcevers (TRX) n 3 reuse,.e. PDCH allocaton on a BCCH TRX has not been consdered. The latter case would result n a lower overall spectrum effcency. IV. NUERICAL RESULTS FOR IEEE (WIAX) IEEE WAN (Wa) standard provdes 7 modulaton and codng schemes CS,, CS 7 as shown n Fg. 5 on the rght hand sde. CS s based on BPSK modulaton, CS 2/3 on QPSK, CS 4/5 on 6-QA and A. Traffc odel wth fed mean Pacet Call Duraton Insertng the data from Table III nto equaton () the capacty of a Wa channel s obtaned for the traffc model wth fed mean pacet call duraton: C CS9 CS8 CS7 CS6 CS5 CS4 CS3 CS2 CS 7 7 Wa α H µ H 6.95bps. The average data payload per resource unt can be calculated accordng to (2) wth an OFD symbol duraton T of 68µs (ncludng 4µs cyclc pref) to: L CWa T 6.95bps 68µ s 472bt. The spectrum effcency s calculated for frequency reuse r 3 accordng to (). The rado channel spacng n Wa s 3.5 Hz: CWa 6.95bps η 0.66bps / Hz / Cell. r B 3 3.5Hz Wa

6 µ (20%) Η 6 Η 7 µ (0%) Η 5 µ 5 0. (20%) µ (7%) Η 3 Η 4 µ (3%) Η 2 µ 2 0. (0%) Η µ 0. (0%) B. Traffc odel wth fed mean Pacet Call Volume Usng (8) and (9) and the data n Table III the Wa channel capacty and average payload per OFD symbol have been calculated n case of a fed mean data volume per user as follows: CWa 4.3bps, and 7 H L CWa T 4.3bps 68µ s 293bt. The correspondng spectrum effcency s gven by (): CWa 4.3bps η 0.4bps / Hz / Cell. r B 3 3.5Hz Wa As epected the channel capacty as well as the spectrum effcency for Wa s sgnfcantly hgher for the traffc model wth fed mean pacet call duraton than those obtaned for the traffc model wth fed mean pacet call volume. The dfference n the results s nearly 60%. The Wa results for the traffc model wth fed mean pacet call volume are fully n lne wth the system level smulaton results provded n [0] and []. The drect comparson of Wa wth EDGE shows that about 40% hgher spectrum effcency s obtaned by Wa applyng the traffc model wth fed mean pacet call duraton and about 20% applyng the traffc model wth fed mean pacet call volume. Nevertheless t shall be ponted out, that especally under good rado condtons Wa allows for a sgnfcantly hgher user throughput than EDGE due to the hgher order modulaton schemes (64-QA for Wa vs. 8-PSK for EDGE) and due to the larger channel bandwdth (e.g. 3.5 Hz for Wa vs. 25 Hz for EDGE). V. CONCLUSIONS A quas-analytcal rapd estmaton method for channel capacty and spectrum effcency n wreless pacet data networs has been derved. The method s essentally based on mappng smulated or measured ln level curves of an arbtrary rado access technology on a measured or smulated cell C/I CDF. The appromaton of the ln level performance C/I [db] Fg. 5. appng of a smulated IEEE (Wa) ln level wth appromaton by step functons (rght) on the cell C/I CDF for 3 reuse (left) at full load. curves by smple step functons allows for a very easy-to-use calculaton procedure. The proposed approach has been manfested on two generc traffc models assumng pacet calls ether wth fed duraton or fed volume. The results obtaned are n lne wth state-of-the-art system level smulaton results recently publshed n the lterature. The channel capacty and spectrum effcency have been estmated for a wdely establshed technology le GS/EDGE and an upcomng new technology such as Wa. It has been clearly stated that rrespectve of the rado technology under evaluaton the performance ndcators le channel capacty and spectrum effcency show sgnfcant dfference of % dependng on the traffc model. Future wor wll be focused on the evaluaton of an approprate mture of the generc traffc models to cope wth realstc user behavor n wreless networs. REFERENCES [] 3GPP TS , General Pacet Rado Servce (GPRS); oble Staton - Base Staton System Interface; Rado Ln Control/edum Access Control (RLC/AC) protocol. [2] 3GPP TS , General Pacet Rado Servce (GPRS); Overall descrpton of the GPRS rado nterface. [3] Draft IEEE Standard for local and metropoltan area networs, IEEE P802.6-REVd/D5-2004, Ar Interface for Fed Broadband Wreless Access Systems, [4] Draft IEEE Standard for local and metropoltan area networs, IEEE P802.6e/D4, Ar Interface for Fed and oble Broadband Wreless Access Systems; Amendment for Physcal and edum Access Control, [5] C.F. Ball, K. Ivanov, P. Stöcl, C. asseron, S. Parolar, R. Trvsonno, Ln Qualty Control Benefts from a Combned Incremental Redundancy and Ln Adaptaton n EDGE Networs, IEEE VTC Sprng, lan, [6] C.F. Ball, K. Ivanov, L. Bugl, P. Stöcl, Improvng GPRS/EDGE Endto-End Performance by Optmzaton of the RLC Protocol and Parameters, IEEE VTC Fall, Los Angeles, [7] T. Halonen, J. Romero and J. elero, GS, GPRS and EDGE Performance, Wley & Sons, [8] K. Ivanov, C.F. Ball, F. Treml, GPRS/EDGE Performance on Reserved and Shared Pacet Data Channels, IEEE VTC Fall, Orlando, [9] C.F. Ball, K. Ivanov, F. Treml, Contrastng GPRS and EDGE over TCP/IP on BCCH and non-bcch Carrers, IEEE VTC Fall, Orlando, [0] C.F. Ball, E. Humburg, K. Ivanov, F. Treml, Performance Analyss of IEEE802.6 based cellular AN wth OFD-256 n moble Scenaros, IEEE VTC Sprng, Stocholm, [] C.F. Ball, E. Humburg, K. Ivanov, F. Treml, Comparson of IEEE802.6 Wa Scenaros wth Fed and oble Subscrbers n Tght Reuse, 4 th IST oble & Wreless Communcatons Summt, Dresden, 2005.

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS 21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS

More information

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

VOLUME 5 BLAGOEVGRAD, BULGARIA SCIENTIFIC. Research ELECTRONIC ISSUE ISSN 1312-7535

VOLUME 5 BLAGOEVGRAD, BULGARIA SCIENTIFIC. Research ELECTRONIC ISSUE ISSN 1312-7535 VOLUME 5 007 BLAGOEVGRAD, BULGARIA SCIENTIFIC Research ISSN 131-7535 ELECTRONIC ISSUE IMPROVING FAIRNESS IN CDMA-HDR NETWORKS Valentn Hrstov Abstract. Improvng throughput and farness n Cellular Data Networks

More information

Efficient Bandwidth Management in Broadband Wireless Access Systems Using CAC-based Dynamic Pricing

Efficient Bandwidth Management in Broadband Wireless Access Systems Using CAC-based Dynamic Pricing Effcent Bandwdth Management n Broadband Wreless Access Systems Usng CAC-based Dynamc Prcng Bader Al-Manthar, Ndal Nasser 2, Najah Abu Al 3, Hossam Hassanen Telecommuncatons Research Laboratory School of

More information

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12 14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed

More information

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

More information

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong,

More information

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:

SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background: SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node

denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node Fnal Report of EE359 Class Proect Throughput and Delay n Wreless Ad Hoc Networs Changhua He changhua@stanford.edu Abstract: Networ throughput and pacet delay are the two most mportant parameters to evaluate

More information

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL

More information

Calculating the high frequency transmission line parameters of power cables

Calculating the high frequency transmission line parameters of power cables < ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

Frequency Selective IQ Phase and IQ Amplitude Imbalance Adjustments for OFDM Direct Conversion Transmitters

Frequency Selective IQ Phase and IQ Amplitude Imbalance Adjustments for OFDM Direct Conversion Transmitters Frequency Selectve IQ Phase and IQ Ampltude Imbalance Adjustments for OFDM Drect Converson ransmtters Edmund Coersmeer, Ernst Zelnsk Noka, Meesmannstrasse 103, 44807 Bochum, Germany edmund.coersmeer@noka.com,

More information

An Introduction to 3G Monte-Carlo simulations within ProMan

An Introduction to 3G Monte-Carlo simulations within ProMan An Introducton to 3G Monte-Carlo smulatons wthn ProMan responsble edtor: Hermann Buddendck AWE Communcatons GmbH Otto-Llenthal-Str. 36 D-71034 Böblngen Phone: +49 70 31 71 49 7-16 Fax: +49 70 31 71 49

More information

Traffic State Estimation in the Traffic Management Center of Berlin

Traffic State Estimation in the Traffic Management Center of Berlin Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D-763 Karlsruhe, Germany phone ++49/72/965/35, emal peter.vortsch@ptv.de Peter Möhl, PTV AG,

More information

How To Understand The Results Of The German Meris Cloud And Water Vapour Product

How To Understand The Results Of The German Meris Cloud And Water Vapour Product Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPP-ATBD-ClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller

More information

M3S MULTIMEDIA MOBILITY MANAGEMENT AND LOAD BALANCING IN WIRELESS BROADCAST NETWORKS

M3S MULTIMEDIA MOBILITY MANAGEMENT AND LOAD BALANCING IN WIRELESS BROADCAST NETWORKS M3S MULTIMEDIA MOBILITY MANAGEMENT AND LOAD BALANCING IN WIRELESS BROADCAST NETWORKS Bogdan Cubotaru, Gabrel-Mro Muntean Performance Engneerng Laboratory, RINCE School of Electronc Engneerng Dubln Cty

More information

DEFINING %COMPLETE IN MICROSOFT PROJECT

DEFINING %COMPLETE IN MICROSOFT PROJECT CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo. ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract

More information

The OC Curve of Attribute Acceptance Plans

The OC Curve of Attribute Acceptance Plans The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4

More information

Calculation of Sampling Weights

Calculation of Sampling Weights Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample

More information

Analysis of Energy-Conserving Access Protocols for Wireless Identification Networks

Analysis of Energy-Conserving Access Protocols for Wireless Identification Networks From the Proceedngs of Internatonal Conference on Telecommuncaton Systems (ITC-97), March 2-23, 1997. 1 Analyss of Energy-Conservng Access Protocols for Wreless Identfcaton etworks Imrch Chlamtac a, Chara

More information

Enabling P2P One-view Multi-party Video Conferencing

Enabling P2P One-view Multi-party Video Conferencing Enablng P2P One-vew Mult-party Vdeo Conferencng Yongxang Zhao, Yong Lu, Changja Chen, and JanYn Zhang Abstract Mult-Party Vdeo Conferencng (MPVC) facltates realtme group nteracton between users. Whle P2P

More information

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008

Risk-based Fatigue Estimate of Deep Water Risers -- Course Project for EM388F: Fracture Mechanics, Spring 2008 Rsk-based Fatgue Estmate of Deep Water Rsers -- Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn

More information

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange

More information

A Design Method of High-availability and Low-optical-loss Optical Aggregation Network Architecture

A Design Method of High-availability and Low-optical-loss Optical Aggregation Network Architecture A Desgn Method of Hgh-avalablty and Low-optcal-loss Optcal Aggregaton Network Archtecture Takehro Sato, Kuntaka Ashzawa, Kazumasa Tokuhash, Dasuke Ish, Satoru Okamoto and Naoak Yamanaka Dept. of Informaton

More information

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho

More information

Open Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1

Open Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1 Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal, 2014, 8, 115-121 115 Open Access A Load Balancng Strategy wth Bandwdth Constrant n Cloud Computng Jng Deng 1,*,

More information

Analysis of Premium Liabilities for Australian Lines of Business

Analysis of Premium Liabilities for Australian Lines of Business Summary of Analyss of Premum Labltes for Australan Lnes of Busness Emly Tao Honours Research Paper, The Unversty of Melbourne Emly Tao Acknowledgements I am grateful to the Australan Prudental Regulaton

More information

ivoip: an Intelligent Bandwidth Management Scheme for VoIP in WLANs

ivoip: an Intelligent Bandwidth Management Scheme for VoIP in WLANs VoIP: an Intellgent Bandwdth Management Scheme for VoIP n WLANs Zhenhu Yuan and Gabrel-Mro Muntean Abstract Voce over Internet Protocol (VoIP) has been wdely used by many moble consumer devces n IEEE 802.11

More information

Politecnico di Torino. Porto Institutional Repository

Politecnico di Torino. Porto Institutional Repository Poltecnco d Torno Porto Insttutonal Repostory [Artcle] A cost-effectve cloud computng framework for acceleratng multmeda communcaton smulatons Orgnal Ctaton: D. Angel, E. Masala (2012). A cost-effectve

More information

Analysis of the Delay and Jitter of Voice Traffic Over the Internet

Analysis of the Delay and Jitter of Voice Traffic Over the Internet Analyss of the Delay and Jtter of Voce Traffc Over the Internet Mansour J. Karam, Fouad A. Tobag Abstract In the future, voce communcaton s expected to mgrate from the Publc Swtched Telephone Network (PSTN)

More information

An Adaptive Cross-layer Bandwidth Scheduling Strategy for the Speed-Sensitive Strategy in Hierarchical Cellular Networks

An Adaptive Cross-layer Bandwidth Scheduling Strategy for the Speed-Sensitive Strategy in Hierarchical Cellular Networks An Adaptve Cross-layer Bandwdth Schedulng Strategy for the Speed-Senstve Strategy n erarchcal Cellular Networks Jong-Shn Chen #1, Me-Wen #2 Department of Informaton and Communcaton Engneerng ChaoYang Unversty

More information

Distributed Optimal Contention Window Control for Elastic Traffic in Wireless LANs

Distributed Optimal Contention Window Control for Elastic Traffic in Wireless LANs Dstrbuted Optmal Contenton Wndow Control for Elastc Traffc n Wreless LANs Yalng Yang, Jun Wang and Robn Kravets Unversty of Illnos at Urbana-Champagn { yyang8, junwang3, rhk@cs.uuc.edu} Abstract Ths paper

More information

Lecture 3: Force of Interest, Real Interest Rate, Annuity

Lecture 3: Force of Interest, Real Interest Rate, Annuity Lecture 3: Force of Interest, Real Interest Rate, Annuty Goals: Study contnuous compoundng and force of nterest Dscuss real nterest rate Learn annuty-mmedate, and ts present value Study annuty-due, and

More information

A Dynamic Load Balancing Algorithm in Heterogeneous Network

A Dynamic Load Balancing Algorithm in Heterogeneous Network 06 7th Internatonal Conference on Intellgent Systems Modellng and Smulaton A Dynamc Load Balancng Algorthm n Heterogeneous etwork Zhxong Dng Xngjun Wang and Wenmng Yang Shenzhen Key Lab of Informaton Securty

More information

Performance Analysis and Comparison of QoS Provisioning Mechanisms for CBR Traffic in Noisy IEEE 802.11e WLANs Environments

Performance Analysis and Comparison of QoS Provisioning Mechanisms for CBR Traffic in Noisy IEEE 802.11e WLANs Environments Tamkang Journal of Scence and Engneerng, Vol. 12, No. 2, pp. 143149 (2008) 143 Performance Analyss and Comparson of QoS Provsonng Mechansms for CBR Traffc n Nosy IEEE 802.11e WLANs Envronments Der-Junn

More information

Time Domain simulation of PD Propagation in XLPE Cables Considering Frequency Dependent Parameters

Time Domain simulation of PD Propagation in XLPE Cables Considering Frequency Dependent Parameters Internatonal Journal of Smart Grd and Clean Energy Tme Doman smulaton of PD Propagaton n XLPE Cables Consderng Frequency Dependent Parameters We Zhang a, Jan He b, Ln Tan b, Xuejun Lv b, Hong-Je L a *

More information

Performance Analysis of Time-of-Arrival Mobile Positioning in Wireless Cellular CDMA Networks

Performance Analysis of Time-of-Arrival Mobile Positioning in Wireless Cellular CDMA Networks Performance Analyss of Tme-of-Arrval Moble Postonng n Wreless Cellular CDMA Networks 437 1 X Performance Analyss of Tme-of-Arrval Moble Postonng n Wreless Cellular CDMA Networks M. A.Landols, A. H. Muqabel,

More information

Project Networks With Mixed-Time Constraints

Project Networks With Mixed-Time Constraints Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa

More information

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features On-Lne Fault Detecton n Wnd Turbne Transmsson System usng Adaptve Flter and Robust Statstcal Features Ruoyu L Remote Dagnostcs Center SKF USA Inc. 3443 N. Sam Houston Pkwy., Houston TX 77086 Emal: ruoyu.l@skf.com

More information

Properties of Indoor Received Signal Strength for WLAN Location Fingerprinting

Properties of Indoor Received Signal Strength for WLAN Location Fingerprinting Propertes of Indoor Receved Sgnal Strength for WLAN Locaton Fngerprntng Kamol Kaemarungs and Prashant Krshnamurthy Telecommuncatons Program, School of Informaton Scences, Unversty of Pttsburgh E-mal: kakst2,prashk@ptt.edu

More information

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Research Note APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES * Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC

More information

A User-Centric Approach for Dynamic Resource Allocation in CDMA systems based on Hopfield Neural Networks

A User-Centric Approach for Dynamic Resource Allocation in CDMA systems based on Hopfield Neural Networks A User-Centrc Approach for Dynamc esource Allocaton n CDA systems based on Hopfeld eural etworks. García. Agustí J. érez-omero Unverstat ompeu Fabra (UF) Unverstat oltècnca de Catalunya (UC) Barcelona

More information

MAC Layer Service Time Distribution of a Fixed Priority Real Time Scheduler over 802.11

MAC Layer Service Time Distribution of a Fixed Priority Real Time Scheduler over 802.11 Internatonal Journal of Software Engneerng and Its Applcatons Vol., No., Aprl, 008 MAC Layer Servce Tme Dstrbuton of a Fxed Prorty Real Tme Scheduler over 80. Inès El Korb Ecole Natonale des Scences de

More information

An Interest-Oriented Network Evolution Mechanism for Online Communities

An Interest-Oriented Network Evolution Mechanism for Online Communities An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne

More information

Data Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network *

Data Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network * JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 24, 819-840 (2008) Data Broadcast on a Mult-System Heterogeneous Overlayed Wreless Network * Department of Computer Scence Natonal Chao Tung Unversty Hsnchu,

More information

Load Balancing Based on Clustering Methods for LTE Networks

Load Balancing Based on Clustering Methods for LTE Networks Cyber Journals: Multdscplnary Journals n Scence and Technology Journal of Selected Areas n Telecommuncatons (JSAT) February Edton 2013 Volume 3 Issue 2 Load Balancng Based on Clusterng Methods for LTE

More information

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP) 6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes

More information

STATISTICAL DATA ANALYSIS IN EXCEL

STATISTICAL DATA ANALYSIS IN EXCEL Mcroarray Center STATISTICAL DATA ANALYSIS IN EXCEL Lecture 6 Some Advanced Topcs Dr. Petr Nazarov 14-01-013 petr.nazarov@crp-sante.lu Statstcal data analyss n Ecel. 6. Some advanced topcs Correcton for

More information

Dimming Cellular Networks

Dimming Cellular Networks Dmmng Cellular Networks Davd Tpper, Abdelmounaam Rezgu, Prashant Krshnamurthy, and Peera Pacharntanakul Graduate Telecommuncatons and Networkng Program, Unversty of Pttsburgh, Pttsburgh, PA 1526, Unted

More information

Luby s Alg. for Maximal Independent Sets using Pairwise Independence

Luby s Alg. for Maximal Independent Sets using Pairwise Independence Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent

More information

How To Calculate The Accountng Perod Of Nequalty

How To Calculate The Accountng Perod Of Nequalty Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.

More information

Efficient On-Demand Data Service Delivery to High-Speed Trains in Cellular/Infostation Integrated Networks

Efficient On-Demand Data Service Delivery to High-Speed Trains in Cellular/Infostation Integrated Networks IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. XX, NO. XX, MONTH 2XX 1 Effcent On-Demand Data Servce Delvery to Hgh-Speed Trans n Cellular/Infostaton Integrated Networks Hao Lang, Student Member,

More information

Risk Model of Long-Term Production Scheduling in Open Pit Gold Mining

Risk Model of Long-Term Production Scheduling in Open Pit Gold Mining Rsk Model of Long-Term Producton Schedulng n Open Pt Gold Mnng R Halatchev 1 and P Lever 2 ABSTRACT Open pt gold mnng s an mportant sector of the Australan mnng ndustry. It uses large amounts of nvestments,

More information

An RFID Distance Bounding Protocol

An RFID Distance Bounding Protocol An RFID Dstance Boundng Protocol Gerhard P. Hancke and Markus G. Kuhn May 22, 2006 An RFID Dstance Boundng Protocol p. 1 Dstance boundng Verfer d Prover Places an upper bound on physcal dstance Does not

More information

Self-Adaptive SLA-Driven Capacity Management for Internet Services

Self-Adaptive SLA-Driven Capacity Management for Internet Services Self-Adaptve SLA-Drven Capacty Management for Internet Servces Bruno Abrahao, Vrglo Almeda and Jussara Almeda Computer Scence Department Federal Unversty of Mnas Geras, Brazl Alex Zhang, Drk Beyer and

More information

Cooperative Load Balancing in IEEE 802.11 Networks with Cell Breathing

Cooperative Load Balancing in IEEE 802.11 Networks with Cell Breathing Cooperatve Load Balancng n IEEE 82.11 Networks wth Cell Breathng Eduard Garca Rafael Vdal Josep Paradells Wreless Networks Group - Techncal Unversty of Catalona (UPC) {eduardg, rvdal, teljpa}@entel.upc.edu;

More information

AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION

AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION The Medterranean Journal of Computers and Networks, Vol. 2, No. 1, 2006 57 AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION L. Bada 1,*, M. Zorz 2 1 Department of Engneerng,

More information

Brigid Mullany, Ph.D University of North Carolina, Charlotte

Brigid Mullany, Ph.D University of North Carolina, Charlotte Evaluaton And Comparson Of The Dfferent Standards Used To Defne The Postonal Accuracy And Repeatablty Of Numercally Controlled Machnng Center Axes Brgd Mullany, Ph.D Unversty of North Carolna, Charlotte

More information

BERNSTEIN POLYNOMIALS

BERNSTEIN POLYNOMIALS On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful

More information

Schedulability Bound of Weighted Round Robin Schedulers for Hard Real-Time Systems

Schedulability Bound of Weighted Round Robin Schedulers for Hard Real-Time Systems Schedulablty Bound of Weghted Round Robn Schedulers for Hard Real-Tme Systems Janja Wu, Jyh-Charn Lu, and We Zhao Department of Computer Scence, Texas A&M Unversty {janjaw, lu, zhao}@cs.tamu.edu Abstract

More information

Quantization Effects in Digital Filters

Quantization Effects in Digital Filters Quantzaton Effects n Dgtal Flters Dstrbuton of Truncaton Errors In two's complement representaton an exact number would have nfntely many bts (n general). When we lmt the number of bts to some fnte value

More information

Daily O-D Matrix Estimation using Cellular Probe Data

Daily O-D Matrix Estimation using Cellular Probe Data Zhang, Qn, Dong and Ran Daly O-D Matrx Estmaton usng Cellular Probe Data 0 0 Y Zhang* Department of Cvl and Envronmental Engneerng, Unversty of Wsconsn-Madson, Madson, WI 0 Phone: -0-- E-mal: zhang@wsc.edu

More information

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika.

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika. VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual

More information

Implementation of Deutsch's Algorithm Using Mathcad

Implementation of Deutsch's Algorithm Using Mathcad Implementaton of Deutsch's Algorthm Usng Mathcad Frank Roux The followng s a Mathcad mplementaton of Davd Deutsch's quantum computer prototype as presented on pages - n "Machnes, Logc and Quantum Physcs"

More information

Study on Model of Risks Assessment of Standard Operation in Rural Power Network

Study on Model of Risks Assessment of Standard Operation in Rural Power Network Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,

More information

Efficient Striping Techniques for Variable Bit Rate Continuous Media File Servers æ

Efficient Striping Techniques for Variable Bit Rate Continuous Media File Servers æ Effcent Strpng Technques for Varable Bt Rate Contnuous Meda Fle Servers æ Prashant J. Shenoy Harrck M. Vn Department of Computer Scence, Department of Computer Scences, Unversty of Massachusetts at Amherst

More information

A GENERIC HANDOVER DECISION MANAGEMENT FRAMEWORK FOR NEXT GENERATION NETWORKS

A GENERIC HANDOVER DECISION MANAGEMENT FRAMEWORK FOR NEXT GENERATION NETWORKS A GENERIC HANDOVER DECISION MANAGEMENT FRAMEWORK FOR NEXT GENERATION NETWORKS Shanthy Menezes 1 and S. Venkatesan 2 1 Department of Computer Scence, Unversty of Texas at Dallas, Rchardson, TX, USA 1 shanthy.menezes@student.utdallas.edu

More information

Packet Dispersion and the Quality of Voice over IP Applications in IP networks

Packet Dispersion and the Quality of Voice over IP Applications in IP networks acet Dsperson and the Qualty of Voce over I Applcatons n I networs Ham Zlatorlov, Hanoch Levy School of Computer Scence Tel Avv Unversty Tel Avv, Israel Abstract- Next Generaton Networs (NGN and the mgraton

More information

Network Services Definition and Deployment in a Differentiated Services Architecture

Network Services Definition and Deployment in a Differentiated Services Architecture etwork Servces Defnton and Deployment n a Dfferentated Servces Archtecture E. kolouzou, S. Manats, P. Sampatakos,. Tsetsekas, I. S. Veners atonal Techncal Unversty of Athens, Department of Electrcal and

More information

Network Aware Load-Balancing via Parallel VM Migration for Data Centers

Network Aware Load-Balancing via Parallel VM Migration for Data Centers Network Aware Load-Balancng va Parallel VM Mgraton for Data Centers Kun-Tng Chen 2, Chen Chen 12, Po-Hsang Wang 2 1 Informaton Technology Servce Center, 2 Department of Computer Scence Natonal Chao Tung

More information

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network

Forecasting the Demand of Emergency Supplies: Based on the CBR Theory and BP Neural Network 700 Proceedngs of the 8th Internatonal Conference on Innovaton & Management Forecastng the Demand of Emergency Supples: Based on the CBR Theory and BP Neural Network Fu Deqang, Lu Yun, L Changbng School

More information

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy 4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.

More information

Reducing Channel Zapping Time in IPTV Based on User s Channel Selection Behaviors

Reducing Channel Zapping Time in IPTV Based on User s Channel Selection Behaviors > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < Reducng Channel Tme n IPTV Based on User s Channel Selecton Behavors Chae Young Lee, Member, IEEE, Chang K Hong and

More information

IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS

IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS Chrs Deeley* Last revsed: September 22, 200 * Chrs Deeley s a Senor Lecturer n the School of Accountng, Charles Sturt Unversty,

More information

Nordea G10 Alpha Carry Index

Nordea G10 Alpha Carry Index Nordea G10 Alpha Carry Index Index Rules v1.1 Verson as of 10/10/2013 1 (6) Page 1 Index Descrpton The G10 Alpha Carry Index, the Index, follows the development of a rule based strategy whch nvests and

More information

One-Shot Games for Spectrum Sharing among Co-Located Radio Access Networks

One-Shot Games for Spectrum Sharing among Co-Located Radio Access Networks One-Shot Games for Spectrum Sharng among Co-Located Rado Access etwors Sofonas Halu, Alexs A. Dowhuszo, Olav Tronen and Lu We Department of Communcatons and etworng, Aalto Unversty, P.O. Box 3000, FI-00076

More information

Antenna and Propagation Parameters Modeling Live Networks

Antenna and Propagation Parameters Modeling Live Networks Antenna and Propagaton Parameters Modelng Lve Networks Arne Smonsson, Martn Johansson and Magnus Lundevall Ercsson Research, Sweden [arne.smonsson, martn.n.johansson, magnus.lundevall]@ercsson.com Abstract

More information

AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE

AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE Yu-L Huang Industral Engneerng Department New Mexco State Unversty Las Cruces, New Mexco 88003, U.S.A. Abstract Patent

More information

Fault tolerance in cloud technologies presented as a service

Fault tolerance in cloud technologies presented as a service Internatonal Scentfc Conference Computer Scence 2015 Pavel Dzhunev, PhD student Fault tolerance n cloud technologes presented as a servce INTRODUCTION Improvements n technques for vrtualzaton and performance

More information

How To Solve An Onlne Control Polcy On A Vrtualzed Data Center

How To Solve An Onlne Control Polcy On A Vrtualzed Data Center Dynamc Resource Allocaton and Power Management n Vrtualzed Data Centers Rahul Urgaonkar, Ulas C. Kozat, Ken Igarash, Mchael J. Neely urgaonka@usc.edu, {kozat, garash}@docomolabs-usa.com, mjneely@usc.edu

More information

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and

This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and Ths artcle appeared n a journal publshed by Elsever. The attached copy s furnshed to the author for nternal non-commercal research and educaton use, ncludng for nstructon at the authors nsttuton and sharng

More information

FINAL REPORT. City of Toronto. Contract 47016555. Project No: B000203-3

FINAL REPORT. City of Toronto. Contract 47016555. Project No: B000203-3 Cty of Toronto SAFETY IMPACTS AD REGULATIOS OF ELECTROIC STATIC ROADSIDE ADVERTISIG SIGS TECHICAL MEMORADUM #2C BEFORE/AFTER COLLISIO AALYSIS AT SIGALIZED ITERSECTIO FIAL REPORT 3027 Harvester Road, Sute

More information

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION

More information

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services

An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao

More information

Methodology to Determine Relationships between Performance Factors in Hadoop Cloud Computing Applications

Methodology to Determine Relationships between Performance Factors in Hadoop Cloud Computing Applications Methodology to Determne Relatonshps between Performance Factors n Hadoop Cloud Computng Applcatons Lus Eduardo Bautsta Vllalpando 1,2, Alan Aprl 1 and Alan Abran 1 1 Department of Software Engneerng and

More information

METHODOLOGY TO DETERMINE RELATIONSHIPS BETWEEN PERFORMANCE FACTORS IN HADOOP CLOUD COMPUTING APPLICATIONS

METHODOLOGY TO DETERMINE RELATIONSHIPS BETWEEN PERFORMANCE FACTORS IN HADOOP CLOUD COMPUTING APPLICATIONS METHODOLOGY TO DETERMINE RELATIONSHIPS BETWEEN PERFORMANCE FACTORS IN HADOOP CLOUD COMPUTING APPLICATIONS Lus Eduardo Bautsta Vllalpando 1,2, Alan Aprl 1 and Alan Abran 1 1 Department of Software Engneerng

More information

A generalized hierarchical fair service curve algorithm for high network utilization and link-sharing

A generalized hierarchical fair service curve algorithm for high network utilization and link-sharing Computer Networks 43 (2003) 669 694 www.elsever.com/locate/comnet A generalzed herarchcal far servce curve algorthm for hgh network utlzaton and lnk-sharng Khyun Pyun *, Junehwa Song, Heung-Kyu Lee Department

More information

Sketching Sampled Data Streams

Sketching Sampled Data Streams Sketchng Sampled Data Streams Florn Rusu, Aln Dobra CISE Department Unversty of Florda Ganesvlle, FL, USA frusu@cse.ufl.edu adobra@cse.ufl.edu Abstract Samplng s used as a unversal method to reduce the

More information

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

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,

More information

Practical Design Considerations for Next Generation High-Speed Data Wireless Systems

Practical Design Considerations for Next Generation High-Speed Data Wireless Systems Practcal Desgn Consderatons for ext Generaton Hgh-peed Data Wreless ystems ChngYao Huang and Hue Yuan u Wreless Informaton and Technology Lab Department of Electroncs Engneerng atonal Chao Tung Unversty

More information

Support Vector Machines

Support Vector Machines Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.

More information

Vasicek s Model of Distribution of Losses in a Large, Homogeneous Portfolio

Vasicek s Model of Distribution of Losses in a Large, Homogeneous Portfolio Vascek s Model of Dstrbuton of Losses n a Large, Homogeneous Portfolo Stephen M Schaefer London Busness School Credt Rsk Electve Summer 2012 Vascek s Model Important method for calculatng dstrbuton of

More information

RESEARCH DISCUSSION PAPER

RESEARCH DISCUSSION PAPER Reserve Bank of Australa RESEARCH DISCUSSION PAPER Competton Between Payment Systems George Gardner and Andrew Stone RDP 2009-02 COMPETITION BETWEEN PAYMENT SYSTEMS George Gardner and Andrew Stone Research

More information

Reporting Forms ARF 113.0A, ARF 113.0B, ARF 113.0C and ARF 113.0D FIRB Corporate (including SME Corporate), Sovereign and Bank Instruction Guide

Reporting Forms ARF 113.0A, ARF 113.0B, ARF 113.0C and ARF 113.0D FIRB Corporate (including SME Corporate), Sovereign and Bank Instruction Guide Reportng Forms ARF 113.0A, ARF 113.0B, ARF 113.0C and ARF 113.0D FIRB Corporate (ncludng SME Corporate), Soveregn and Bank Instructon Gude Ths nstructon gude s desgned to assst n the completon of the FIRB

More information