USER CLASS BASED QoS DIFFERENTIATION IN e WLAN

Transcription

1 USER CLASS BASED QoS DIFFERENTIATION IN e WLAN Amt Kejrwal, Ratan Guha School of Computer Scence Unversty of Central Florda Orlando, FL USA E-mal: {kejrwal, Manak Chatterjee Dept. of Electrcal and Computer Engneerng Unversty of Central Florda Orlando, FL USA KEYWORDS , e, QoS, WLAN ABSTRACT e s the new extenson to the famly of standards whch tres to provde QoS support to data servces over the wreless LAN. However, t does not provde any mechansm to dfferentate users whch becomes a bottleneck for provdng dfferentated servces to users from all sectons of the socety. In ths paper, we study the e MAC protocol and suggest some enhancements to the current standard that wll be able to provde QoS dependng on the class a user belongs to n addton to the traffc category used by the user/staton. Our algorthm takes nto consderaton the class of a user and the traffc category before any resource assgnment s made. The algorthm has the scope for varous tradeoffs that can be provded dependng on the mportance of the objectve functon: bandwdth utlzaton or prortzaton of staton s ablty to transmt. Smulatons were conducted to valdate our algorthms and test ther effcency. INTRODUCTION The need for computng on the move has generated a need for wreless LAN market, wth WLANs becomng more and more omn-resent. The mostly commercalzed WLAN products avalable today are based on the IEEE standard whch has become the most prevalng technology for ndoor broadband access for moble devces. Alongsde, the wdespread use of networkng multmeda applcatons has brought more requrements to the network and the servce provders creatng the need for end-to-end qualty of servce (QoS). The IEEE workng group s defnng a new supplement to the MAC called e whch ams at provdng toll-qualty voce and vdeo servces over WLANs [2]. However, e does not have the opton to allow the servce provders to dfferentate users based on ther prorty or subscrpton plans, and hence all users are stll treated equally. Classfyng users nto dfferent classes and tryng to retan them are becomng mportant strateges for the servce provders. Most servce provders have started offerng dfferentated servces to users through ther prcng plan for voce communcaton. The users are segmented and offered dfferent values for ther servces. As the provders start ntroducng ther wreless data servces, most lkely they wll offer smlar plans for the data servces. In ths context, the desgn of resource control should be based on the mutual benefts of the carrers and users. However, the bg queston s: what s the qualty of wreless data servces due to the new mpedments created n the wreless networks? Tradtonally, today's wreless voce network does not dfferentate the QoS among the customers and ther voce applcatons. In other words, the way the wreless network resources are shared between the dfferent voce customers today, does not reflect any bas to the customer's preference or customer's subscrpton status. The problem les n the fact that smlar desgn phlosophes cannot be used or extended for wreless data networks. In our opnon, the concept of dfferentated qualty of servce among customers of varous classes wll be an mportant parameter n the wreless data networks and servces. The objectve here s to create dfferent classes of customers based on the selected servce packages and provde dstncton between the QoS levels lke delay or throughput among these classes. In other words, the network must support dfferent customers wth dfferent contracts wth varyng QoS or servce level agreement (SLA). Ths motvated the work n ths paper. The rest of the paper s organzed as follows. In secton 2, we dscuss the concept of traffc categores used n e along wth the dfferent tmers used for channel access. In secton 3, we ntroduce the concept of user classes and dscuss possble scenaros that mght arse. Secton 4 presents the algorthms to tackle the dfferent scenaros. The smulaton s presented n secton 5 and conclusons are drawn n the last secton.

2 EDCF: ENHANCED DISTRIBUTIVE COORDINATION FUNCTION The dstrbuted coordnated functon (DCF) s the bass for the protocol. An enhanced DCF called EDCF [3] has been proposed for e whch provdes QoS based on traffc categores (TC) [3] e also ntroduces a concept of QoS-supportng basc servce set (QBSS) [3]. QBSS s a BSS that ncludes the statons that are e complant and can support QoS based servces. These statons operatng n the e mode are known as enhanced statons e allows up to eght traffc categores whch are used to dfferentate among dfferent traffc and hence prorty can be assgned [3]. The traffc category wth hgher prorty wll have more probablty to access the medum than the traffc category wth lower prorty [3]. Ths feature to support traffc prorty was mssng n the legacy Also the DCF nter frame spacng, called DIFS, has been replaced by Arbtraton nter frame space (AIFS) n e [3]. AIFS s dfferent for each traffc category, and depends on the prorty of traffc category. The traffc category wth the hghest prorty has the lowest AIFS perod and as the prorty decreases the AIFS perod ncreases as shown n Fgure 1. AIFS value s at least equal to DIFS (.e., AIFS DIFS =34 µs) perod for e to be backward compatble wth the legacy [2]-[3]. Each traffc category has ts own backoff nstance whch also depends on the prorty of the traffc category. EDCF statons wats for a perod of AIFS when the medum s dle before startng ther backoff functon. The contenton wndow (CW) never exceeds the parameter CWmax [TC], whch s the maxmum possble value for [2]-[3]. The mnmum value depends on the traffc category and can take values between 0 and 255, thus CW mn [TC]=0-255 [2]- [3]. AIFS[TC n ] AIFS[TC 2 ] AIFS[TC 1] SIFS ACK DATA Defer Access Lowest Prorty TC Traffc Category 2 Hghest Prorty TC Contenton Wndow Tme backoff backoff RTS SIFS CTS Fgure 1: AIFS Classfcaton for Dfferent TC A staton always wats for ts AIFS perod before t starts transmttng. However, t does not mean that a staton can always transmt when the backoff counter reaches zero because the medum can become busy. In that case, the backoff counter s frozen tll the next tme medum s free. The staton resumes decrementng backoff counter agan when the medum become free. If more than one traffc category s backoff counter becomes 0 at the same tme, t results n a vrtual collson [3]. Vrtual collsons are avoded by lettng the traffc category wth the hghest prorty to transmt. One of the bggest dfferences between legacy DCF and e s that n legacy the backoff counter s decremented by 1 after the frst tme slot of DIFS perod, whle n e the backoff counter s decremented by 1 from the last tme slot of AIFS perod [3]. Ths makes a bg dfference n the tme when a node chooses a backoff nstance. Legacy ncreases the range of backoff value by twce after each unsuccessful transmsson but n e the new backoff value s calculated usng a parameter called PF (Persstence Factor) whch takes dfferent values (1 through 16) for dfferent TC. Thus [3], newcw [TC] ((oldcw [TC] 1) PF) -1. Class 1 Class 2 Class 3 Fgure 2: User Class and Traffc Categores CLASS BASED QoS e does provde QoS by ntroducng traffc categores. Snce all the traffc categores can potentally be used by every users/statons, there s no scope to dfferentate among users. Let us assume that there are multple classes of users all usng the eght traffc categores. Fgure 2 shows only 3 classes, namely Class 1, Class 2 and Class 3. We propose that the user classes be takng nto consderaton whle decdng the tme for a staton to transmt. Normally, the total tme that each staton has to wat before tryng to transmt s AIFS plus the contenton wndow. We suggest that both the AIFS and the CW be made dependent on the class of the user and traffc category. Thus, for a staton to transmt, the tme to transmt (TT ) s gven by TT = AIFS [Class ] [TC ] + CW [Class ] [TC ].

3 Possble Scenaros Before we propose our algorthms, let us ntroduce the possble scenaros that mght arse due to the ntroducton of these multple classes. The algorthm used to calculate the tme for a staton to attempt a transmsson, must allow dfferent varatons n the prorty based on class and the data traffc category used by the staton. We consder that Class 1 has the hghest prorty and Class N has the lowest. In other words, the prorty schedule s as follows: Class 1 > Class 2 > Class 3 >.. > Class N Scenaro 1: Ths s a trval scenaro where though there are multple classes; there s no prorty dfferentaton amongst the classes. The prorty of a staton to transmt s only dfferentated by usng the traffc category, whch s essentally the same as supported by the current e. Fgure 3 shows how the dfferent classes are treated at par. traffc categores. Fgure 5 shows ths dfference as j. j represents the number of traffc categores for a class that have prorty over correspondng traffc categores n lower prorty class. Class1 j=2 Class2 ClassN Class 1 Class 2 Fgure 5: SCENARIO 3, WHEN j =2 Class 3 Fgure 3: SCENARIO 1 Scenaro 2: In ths scenaro, a hgher class has the prorty to transmt rrespectve of the traffc category as shown n Fgure 4. PROPOSED ALGORITHMS We frst deal wth the frst two scenaros before we dscuss the general scenaro. The generalzed algorthm for scenaro 3 wll encompass all the other scenaros just by changng the value of j. Class 1 Class 2 Fgure 4: SCENARIO 2 Class N Scenaro 3 (General Scenaro): In ths scenaro, only the correspondng traffc category wth hgher class has a prorty over correspondng traffc category n lower class. However, there s a possblty that the prorty dfference to vary. For example the prorty of TC 1 and TC 2 n class 1 may have prorty over the TC 1 and TC 2 of class 2 or prorty of TC 1, TC 2 and TC 3 n class 1 has prorty over the TC 1, TC 2 and TC 3 of class 2 and ths relatonshp contnue throughout all the classes and Algorthm for Scenaro 1 Ths scenaro s smlar to the one supported by the present e. In ths scenaro all users have same prorty (only one class exsts) but the dfference n prorty s among the traffc categores [3]. Ths case can be supported by allowng dfferent AIFS and CW for dfferent TC s prorty. If TC 1 has hghest prorty then t can be scheduled as: AIFS[TC ] AIFS[TC ]f j As the CW max s constant for a partcular TC, therefore the mean value for the CW wll be less for a traffc category wth hgher prorty [3]. Therefore, tme to transmt wll be TT AIFS[TC ] CW[TC ] Thus from the relatonshp between AIFS[TC ] and CW[TC ] we can say that TT [TC ] TT [TC ]f j. j j

4 Algorthm for Scenaro 2 In ths scenaro all traffc categores of a partcular class wll have more prorty over traffc categores of all other classes of lower prorty than that class. To acheve ths relatonshp, frst t s mportant to fnd out the tme each staton has to wat to transmt data dependng on ts class and traffc category. TT AIFS [Class] CW [TC] In ths scenaro, AIFS of the staton s dependent on the class and CW s dependent on traffc category, thus tme to transmt s dependent on both class and traffc category. CW [TC] can be found as t s suggested n e. To acheve the prorty as descrbed above, the relatonshp between th and +1 th class s: AIFS 1 AIFS CW TC CW[TC n ] s the maxmum value of contenton wndow produced by all the traffc categores. Thus, all traffc categores of a hgher prorty class wll have more prorty than all the traffc categores of a lower prorty class. Let P and Q represent the class of a user and the traffc category of the staton respectvely. Hghest prorty mples P=0 and hghest traffc category mples Q=0. As prorty decreases for both class and traffc category the value of P and Q ncreases by 1. Let us denote the tme to transmt for a user belongng to class P and wth traffc category Q by TT [P] [Q]. Ths scenaro wll mantan the followng relatonshps: TT TT P Q TT P Q 1 P Q TT P 1 Q The value for Q s n for TT[P][Q] and 0 for TT[P+1][Q]. In spte of these prortes, there s no way to elmnate the possblty of collsons, as ths algorthm s bascally collson avodance and not collson elmnaton. So the algorthm should also nclude the penalty for unsuccessful transmsson. When the number of unsuccessful transmssons reaches certan threshold, tme to transmt by a staton shall be ncreased as a penalty. Snce ths s a class based servce, even after unsuccessful transmsson, t may be preferable to have fewer penaltes for a staton wth hgher prorty. The downsde of havng lower penaltes for staton wth hgher prorty s that t mght delay the transmsson of data or starve the lower prorty statons. So to avod the delay, we do not penalze a staton wth hgher prorty untl a certan number of retransmssons, say Threshold. Thus, f the number of retransmssons s below Threshold the value of tme to transmt remans unaffected. If the number of retransmsson s hgher than Threshold the tme to transmt s ncreased by an n Increment Factor (IF). Increment factor depends on whether the algorthm needs to be far to all users or t needs to be favorable to the statons wth hgher prorty, and s always greater than 1. Therefore the algorthm can be defned as follows. f ( no.of retransmsson ) else TT AIFS class TT IF (AIFS CW class Threshold Traffccategory CW Traffccategory Algorthm for Scenaro 3 (General Scenaro) Wth the specal scenaros dscussed, we are n poston to dscuss the algorthm whch wll handle any scenaro. Both classes and traffc category are nterdependent, whle decdng tme to transmt. As use the same defnton for P and Q. The tme to transmt for user from class P havng traffc category Q s represented by TT[P][Q]. The general relatonshps can be descrbed as: TT[P][Q] TT[P][Q 1] TT[P][Q] TT[P 1][Q] TT[P][Q] TT[P -1][Q 1] Recall, j represents the number of traffc categores for a class that have prorty over correspondng traffc categores n the next lower class. In general, j can take values from 1 through n, where n s the number of traffc categores. For example, when j=2, the 2 consecutve traffc categores have prorty over the same traffc categores n the next lower class. Whle the same two traffc categores of that lower prorty class have hgher prorty over same traffc categores for the classes that have lower prorty than tself. In general form of equaton n the form of j the relatonshp can be expressed as: TT[P][Q j-1] TT[P 1][Q] TT[P][Q] TT[P -1][Q j] TT[P][Q j 1] TT[P -1][Q j] The above nequaltes explan the j relatonshp wth the classes and traffc category. Let us now calculate the contenton wndow. If Q s the prorty value of traffc category, r s the prorty value of class, and Dj = j. Intally the value of D s equal to D j, D s reset to D j once t reaches 0, p keeps track of TC, represent the class category for whch the algorthm s calculatng CW max and j represents the traffc category for whch functon s calculatng CW max. )

5 sum (r 1) ((j-1)/dj) ( (j-1)% Dj) f (D 0) { p p 1 category. Also the value of CW max for class 1 traffc category 3 should be greater than class 2 traffc category 1 & class 2 traffc category 2. CW' max D Dj } D D -1 sum r p Dj MF f(! 1) CW' max sum - (Dj-1) MF s the Man Factor, where MF >1, defned as the dfference n CW max value among the traffc categores whch are j apart wthn the same class. Greater value of MF wll ncrease the CW max value. The value of MF s a tradeoff between the bandwdth utlty and provdng hgher probablty to transmt to those statons that have hgher prorty. The hgher value of MF wll make sure that staton wth hgher prorty may have more probablty to access medum but ts bandwdth utlzaton may be very bad f the hgher prorty statons are not transmttng often. Ths wll happen because even though the medum s free the lower prorty statons have to wat for longer tme before they can try to transmt as ther tme to transmt wll be large. Value of CW max depends on class and traffc category and s related to CW max as CW RF max CW' max where RF s reducng factor to reduce the value of CW max as sometmes the functon may produce hgh values dependng on the trade-off. Thus, TT[P][Q] AIFS CW max [P][Q] AIFS can be kept at mnmum n ths case and that s equal to DIFS=34 µs. Value of AIFS wll reman same for all values of class and traffc category. The algorthm wll produce dfferent values of CW max dependng on class, traffc category and j. The value of CW max produced by above functon are as desred by the algorthm. Thus TT[P][Q] relaton wll be stored as desred by class, traffc category and j. SIMULATION MODEL AND RESULTS We smulated our proposed algorthm wth varyng parameters. We consdered 5 classes of users, 8 traffc categores, MF=1, RF=1and j=2. From Fgure 6 we see that the desred relatonshp s mantaned by the functon. Snce j=2, the value of CW max for class 1 traffc category 1 & class 1 traffc category 2 should be less than Class 2 traffc category 1 & class 2 traffc Fgure 6: VALUES OF CWmax; j=2, MF=1 Also, n case of j=3 the requred relatonshp s mantaned as can be seen from Fgure 7. Value of some class and traffc category s chosen to be near each other as to avod bandwdth loss f there s no transmsson from a hgh prorty staton. Fgure 7: VALUES OF CWmax; j=3, MF=1 The effect of a dfferent value of MF can be seen n Fgure 8, where MF was set to 2. The values of class 1 traffc category 3 & class 1 traffc category 4 were 24 and 25 respectvely n case of MF=1. But for MF=2 these values were 34 and 35 respectvely. Ths shows that ncrease n MF wll ncrease the value of CW max value for every class and traffc category across the system. Usng above shown algorthm the relatonshp as desred n Scenaro 2 can be acheved by puttng j=8.

6 once ts back off counter reaches 0 t wll be allowed to transmt rrespectve of whether a staton wth hgher prorty s watng to transmt and ths smple but dstrbutve approach wll save statons wth lower prortes from starvaton. Retransmssons e suggests that after an unsuccessful transmsson, a new contenton wndow usng persstence factor (PF) be calculated. It s suggested that the value of CW be ncreased as follows: newcw [TC] ((oldcw[tc] 1)*PF) -1 Fgure 8: VALUES OF CWmax; j=2, MF=2 Mean of CW max The value of CW max mantans the relatonshp as desred. Snce CW max gves the maxmum value, a staton can choose between 0 and CW max. The mean for unform dstrbuton wll be CW max /2 for all the dfferent value of CW max dependng on class and traffc category. In some cases there s a possblty that the mean may be too close for some values, n that case the probablty of collson mght ncrease. To reduce ths collson probablty nstead of choosng random values between 0 and CW max, a new functon can be defned as a functon of the user class, whch wll choose a random value between X and CW max. X wll be dependent on the class of the staton. In that case the mean for unform dstrbuton wll be (X+CW max )/2. X can be formally defned as X (P -1) j Ths way the mean value of CW can be changed. Starvaton Algorthm for calculatng CW max may ntally gve an mpresson that t mght produce starvaton for the statons that have lower class and traffc prorty. But n realty ths s not the case snce the algorthm s dstrbutve and once a staton chooses a value for CW max, t does not reset CW max n any case except collson. A new value s chosen for CW max n case of a collson rrespectve of staton s prorty. At any gven nstance of tme a staton wth a hgher prorty wll be gven lower value of CW max than lower prorty staton but once the value s chosen for any staton t s not reset even f a hgher prorty staton tres to clam the medum at some later nstance of tme. The value TT of lower prorty staton decreases every tme t found the medum to be dle for more than AIFS perod and thus In the soluton presented for the class based QoS nstead of ncreasng the value of the contenton wndow after each unsuccessful transmsson, we suggest that the value of CW s ncreased only after a certan number ( Threshold )of retransmsson s reached. Ths way a staton wll not be penalzed after each unsuccessful retransmsson but wll be penalzed only after t consstently results n unsuccessful retransmssons. Also the value of the Persstence Factor wll depend both on the class and the traffc category. To make sure that a staton whch has many consecutve unsuccessful retransmssons falure s not penalzed heavly, we propose another varable, max, whch counts the number of tmes the value of CW has changed consecutvely before makng a successful transmsson. Once that reaches a certan threshold value, maxthreshold, the value of CW s not ncreased any more but kept at the last ncreased value whch makes sure that no staton suffers from starvaton. f (no.of retransmsson < Threshold ) newcw=oldcw f(no. of retransmsson Threshold ) and f ( max < maxthreshold ) else newcw [TC] ((oldcw[tc] 1) PF) -1 newcw=oldcw The added beneft of usng max and maxthreshold s that these values can also be user class and traffc category dependent and thus dfferent values can be assgned to dfferent statons dependng on the class and data s traffc category. If the values of PF change dependng only on the traffc category the slope of the graph for each class wll almost reman same as shown n Fgure 10.

7 ACKNOWLEDGEMENT Ths work was partally supported by ARO under grant DAAD and NSF under Grant EIA CWmax Number of Retransmsson Class 1 Traffc Category 1 Class 2 Traffc Category 1 Class 3 Traffc Category 1 Class 4 Traffc Category 1 Class 5 Traffc Category 1 Fgure 9: CW MAX : PF IS DEPENDENT ON TC If the value of PF s dependent on class and traffc category, the value of CW max wll have greater slope for lower prorty class compared to the hgher prorty class as shown n Fgure 10. CWmax Class 1 Traffc Category 1 Class 2 Traffc Category 1 Class 3 Traffc Category 1 Class 4 Traffc Category 1 Class 5 Traffc Category 1 Number of Retransmsson Fgure 10: CW MAX : PF IS DEPENDENT ON CLASS AND TC CONCLUSIONS In ths paper, we proposed algorthms for class based QoS for e based WLAN servces. Dfferent aspects of algorthm can be tuned by controllng parameters lke MF and RF to acheve the desred level of system performance. We consdered dfferent scenaros ncludng the generalzed one. Algorthms are dstrbutve, smple and gve flexblty for trade-offs dependng on the demand for bandwdth or ncreasng probablty to transmt for hgher prorty class. The beneft of usng above suggested algorthm s that t provdes alternate and more flexble way of provdng QoS. Smulaton results demonstrate that our proposed algorthms do provde the dfferentaton among dfferent user classes. REFERENCES H.L. Truong and G. Vannuccn, The IEEE e MAC for Qualty of Servce n Wreless LANs n Proceedngs of SSGRR2003w, Telecom Itala Learnng Servces Internatonal Conference on advances on the Infrastructure n e-busness, e-scence and moble networkng, L'Aqula, January 8th Habetha, J. and Mangold, S. and Wegert, J., versus HperLAN/2 - a comparson of decentralzed and centralzed MAC protocols for multhop ad hoc rado networks," n Proc. 5 th World Multconference on Systemcs, Cybernetcs and Informatcs (SCI), Orlando, USA, July 2001, pp IEEE WG, Draft Supplement to STANDARD FOR Telecommuncatons and Informaton Exchange between Systems -LAN/MAN Specfc Requrements -Part 11: Wreless Medum Access Control (MAC) and Physcal Layer (PHY) specfcatons: Medum Access Control (MAC) Enhancements for Qualty of Servce (QoS). S. Mangold, S. Cho, P. May, G. Hertz IEEE e Far Resource Sharng between Overlappng Basc Servce Sets n proc. of the PIMRC 2002, Lsbon, Portugal, September 2002, pp D. Qao and S. Cho Goodput enhancement of IEEE a wreless LAN va Lnk adaptaton n proc. IEEE ICC 2001, Helsnk, Fnland, June 2001, vol. 7, pp Stefan Mangold, Sunghyun Cho, Peter May, Ole Klen, Gudo Hertz, Lothar Stbor IEEE e Wreless LAN for Qualty of Servce n proc. of the European Wreless, Vol. 1, Florence, Italy, February 2002, pp AUTHOR BIOGRAPHIES Amt Kejrwal s pursung hs PhD n computer scence at Unversty of Central Florda and s a Sr. Software Developer workng on Integrated Crmnal Justce System. Hs nterests nclude ad-hoc networks, network securty and wreless networks. Ratan Guha s a Professor n the School of Computer Scence at the Unversty of Central Florda. Hs research nterests nclude modelng and smulaton, dstrbuted computng and networkng, and network securty. Manak Chatterjee s an Assstant Professor n the Department of Electrcal and Computer Engneerng at the Unversty of Central Florda. Hs research nterests nclude resource management and qualty-of-servce provsonng n wreless and cellular networks, sensor networks, CDMA data networkng meda access control protocols, Internet traffc, and appled game theory.