Resource Reservation and Utility based Rate Adaptation in Wireless LAN with Slow Fading Channels

Transcription

1 Resource Reservatio ad Utility based Rate Adaptatio i Wireless LAN with Slow Fadig Chaels Floriao De Rago, Peppio Fazio 2 ad Salvatore Marao D.E.I.S. Dept, Uiversity of Calabria Via P.Bucci, cubo 42/c, Arcavacata di Rede (CS), 8736, Italy {derago, marao}@deis.uical.it, 2 [email protected] Abstract Recetly there is a growig iterest i the adaptive multimedia etworkig where the badwidth of a ogoig multimedia flow ca be dyamically adjusted. I this paper the attetio is focused o the maagemet of mobility idepedet services. The cosidered class of service has bee the MIP class, defied i Itegrated Services for mobile wireless eviromet. I order to offer a adaptive QoS (soft QoS) icreasig the total wireless system utilizatio, a rate adaptatio algorithm has bee cosidered. The valued algorithm is based o user utility fuctio ad its target is to maximize this fuctio. The mobility of host ca impact o umber of hadoff ad o chael states (fadig), so the rate adaptatio accouts the degradatio chael state coditios. A algorithm of admissio cotrol has bee cosidered too i order to regulate the access to wireless multimedia etwork. The admissio cotrol ca use the pre-reservatio phase amog the visited cells from mobile hosts for MIP. The performace evaluatios of the wireless system have bee evaluated i terms of total badwidth utilizatio for MIP services, average user utility perceived by mobile users ad system outage probability. Keywords Admissio cotrol, adaptive badwidth allocatio, utility fuctio, Markov model, fadig chaels, pre-reservatio. I. INTRODUCTION There has bee a rapid growth i popularity of wireless data services ad a icreasig maturity of wired multimedia etworks so, extedig multimedia services ito wireless etwork is ievitable. Wireless commuicatios pose special problems, such as limited badwidth ad high error rate, that do ot exist i wired etworks; i additio, the dyamics of physical chaels cause fluctuatios i received sigals; for these reasos, determiistic service guaratees ad badwidth allocatio, commoly used i wired etworks, become iadequate for dealig with wireless commuicatios. User mobility has a importat impact o QoS parameters of real-time applicatios ad the existig protocols, as proposed i [], must be exteded i order to maage host s mobility. This ca be hadled by usig the MRSVP protocol, which is based o active ad passive reservatios ad capable to pre-reserve a amout of badwidth for MIP flows to guaratee the desired QoS durig had-off evets. Sice the dyamics of the resources i mobile computig eviromets is much more severe tha i wirelie eviromets, it is perceived i the scietific commuity the eed to provide effective mechaisms for adaptatio at multiple badwidth levels There differet work i literature that accout the adaptatio of the resource i wireless eviromet ad base the criteria of the badwidth adaptatio o differet idexes as the mi-max fairess criteria, the protocol overhead or the degradatio degree of the flows [8,9]. These algorithms, however, do ot accout the coditio of wireless chael that ca affect the performace of the wireless system. I a etwork ca be preset situatio i which it is ot useful to give a particular amout of badwidth if the chael is i a bad coditio ad the error rate is so high. I this case ca be more useful to give the badwidth to flow that ca take advatage of a better state of the chael. Differet users may experiece differet lik capacities due to differet locatios, ad we believe that badwidth should be allocated i a adaptive ad lik-state depedet way. To cosider the heterogeeity of differet applicatios ad to have a cosistet performace measure, we adopt utility fuctios i our proposed adaptive QoS model. I this paper, we propose a utility-orieted badwidth allocatio scheme ad admissio cotrol policy, which accout for the users QoS requiremets ad actively adapts to the dyamics of the physical chael. There has bee much work o wireless resource maagemet, focusig o multiple access ad chael allocatio, however there is less research o addig a explicit adaptive mechaisms to badwidth allocatio schemes to deal with the variatios of wireless chaels. The rest of the paper is orgaized as follows. Sectio II discusses the user mobility effect ad the wireless variatios. I Sectio III the lik model ad the utility orieted adaptive QoS model are discussed. Sectio IV describes the simulatio results ad Sectio V cocludes the paper. II. DEALING WITH USER MOBILITY AND LINK VARIATIONS I order to offer a adaptive QoS or a better tha best-effort service due to the iheret time varyig evirometal coditios evidet i radio commuicatios (e.g. fadig), it is used a architecture capable to reserve badwidth levels ad to offer guarateed services. This last oe is the Itegrated Services Network [2] with mobile host ad Mobile Resource Reservatio Protocol (MRSVP) [3] is used for exchagig state iformatio of wireless etworks. This protocol ca offer soft QoS (adaptive QoS) for a class of services called Mobility Idepedet Predictive (MIP) ad users belogig to this class request service guaratees, regardig delay i packet delivery ad drop probability durig had-off evets. Accordig to adaptive multimedia wireless framework [4], MIP ca reserve a badwidth level that ca chage durig call holdig time. These behaviour ca guaratee a more flexible resource maagemet icreasig the system utilizatio. The MRSVP protocol esures the absece of flow droppig for MIP class whe the users chage their coverage areas by the passive reservatio policy: a active reservatio is made i the actual coverage access poit (where the coectio is bor) ad a certai amout of passive badwidth (depedet o the allocatio schemes used) is reserved i the remote access poits, that will be visited by user durig the coectio. I this way, MIP users caot fid a ew overloaded cell durig a had-off evet ad they ca be served i adequate maer to cotiue their data sessios. User mobility is also oe of the reasos which cause chael quality degradatios durig a coectio: we cosidered the multipath fadig pheomeo, as direct cosequece of user mobility ad time-varyig impulse respose of radio liks; i particular our work takes i accout the slow-fadig effect, which takes place whe the evolutio of lik chages ca be cosidered to be slower

2 tha symbol trasmissio time. I this way, we give more effectiveess to used rate adaptatio algorithm ad reservatio protocol, because the offered etwork service always guaratees the miimum delay requests made by users, by allocatig more resources to face trasmissio errors due to absece of ideality i radio chaels. To hadle physical lik variability, low level mechaisms, such as error correctio codig ad swappig trasmissio opportuities i packet schedulig, are usually used, but they become iadequate for slow lik variatios; we itroduced a high-level badwidth allocatio scheme that adjust the average badwidth share of each user as the lik quality chages. As we see, mobility ad fadig ca chage system coditios, so it is ecessary to use rate adaptatios algorithms for varyig badwidth levels, accordig to chael coditios ad host mobility. I this case, the used rate adaptatio algorithm is based o a utility fuctio associated to MIP class ad it tries to maximize the user profile satisfactio modelled by these target fuctios [5]. III. SYSTEM MODELING A. Modelig the Time-varyig Lik I our work we employed a Markov chai model to describe the behavior of a radio-lik betwee users ad access-poits, as proposed i [6]. We eeded to itroduce the chai model to cosider the absece of ideality i wireless commuicatios ad the fluctuatios i the received sigal level, due to the various propagatio pheomea durig a geeric coectio (shadowig, refractio, fadig, etc.). As we will see, each chai state has a associated ratio, which represets the received percetage of corrupted bits. The model ca oly be used uder the assumptio of slow fadig. Let S = {s, s,, s K- } deote a fiite set of states ad {S }, =,,2, be a costat Markov process, with the property of statioary trasitios, the the trasitio probability is idepedet of the time idex ad ca be writte as t = P S + = s S = s ), () j, k r ( k j for all =,,2, ad j,k {,,2,,K-}; we ca defie a KxK state trasitio probability matrix T, with elemets t j,k. Moreover, with the statioary trasitio property, the probability of state k without ay state iformatio at other time idices ca also be defied as p k = Pr (S = s k ), where k {,,2,,K-}, so a Kx steady probability vector p ca be defied with its elemet p k. To complete the descriptio of the chai model, we require additioal iformatio o the chael quality for each state, so we ca defie a Kx crossover probability vector e with its elemets e k, k {,,2,,K-}. Now the FSMC is completely defied by T, p ad e. Uder the hypothesis of a received sigal evelope Rayleigh distributed, we ca derive a relatioship betwee physical chael ad its fiite-state model, by partitioig the rage of the received SNR ito a fiite umber of itervals. Fig. 2. SNR ad BER for some digital modulatio schemes Let = A < A < A 2 < < A k = be the thresholds of the received sigal to oise ratio, the the Rayleigh fadig chael is said to be i state s k, k =,,2,,K- if the received SNR is i the iterval [A k,a k+ ). Associated with each state there is a crossover probability e k ad, give a specific digital modulatio scheme, the average error probability is a fuctio of the received sigal to oise ratio (the value of e k is the average error probability o trasmittig a bit whe the received SNR falls i the k-th iterval). The elemets of p ad e ca be writte as follows: pk = Ak + Ak a ρ e da, ρ Ak a ek = e Pe ( a) da / pk, A + ρ ρ k where P e (a) depeds o the digital modulatio scheme chose. I our simulatios we cosidered the CCK modulatio (as i the stadard IEEE82.b) [7], ad P e ( CCK ) ) 2 ( ( a = Q 2 a ). (4) Due to the o liearity betwee SNR ad e k, the SNR itervals may have to be o-uiform to be useful. Figure 2 illustrates the course of BER versus SNR for some kid of useful digital modulatio schemes (Biary Frequecy Shift Keyig, Biary Phase Shift Keyig ad Complemetary Code Keyig). The thresholds A k, with k =,, K-, ca be calculated by choosig the desired values of cross-over probabilities, directly depedet from the degradatio percetage of each state by a etropy fuctio, ad solvig the previous expressio for e k (i our work we proceeded i umerical way). Figure 3 shows the geeral partitioig method of SNR values. The etire modellig techique is based o the kowledge of chael state iformatio (CSI): we assumed that, give the chael capacity, we ca obtai the related values of crossover probabilities by usig a etropy fuctio I particular, whe the CSI is available, the chael capacity is the average capacity over all the states: (2) (3) K = pk [ h( e k )] k = C (5) Fig.. A fiite state Markov chai

3 where h(.) is the biary etropy fuctio defied as: h( e) = e log + ( e) log. (6) e e Fig. 4. A example of utility fuctio Fig. 3. Relatio betwee SNR, BER ad chai states To calculate the trasitio probabilities t j,k we first assumed that the Rayleigh fadig chael is slow eough that the received SNR remais at a certai level for the time duratio of a chael symbol; furthermore, the chael states associated with cosecutive symbols are assumed to be eighborig states. If f d is the maximum Doppler shift itroduced by the user mobility ad T the symbol trasmissio time, the we say that the slow-fadig coditio is verified if f d *T<<. B. Adaptive QoS Model ad Badwidth Allocatio Scheme We used a utility-orieted algorithm for rate-adaptatio ad admissio cotrol, cosiderig the time-varyig ature of liks, betwee hosts ad access poits [5]. I our case, we used mootoically o-decreasig utility fuctios, describig how the perceived utility chages with the amout of effective badwidth received by the user. I our service model, each user i ca sigal its utility fuctio U i (r) to the etwork, where r is the amout of effective badwidth received by the user ad the badwidth allocated to a flow ca take its discrete value from the set B={l,l 2,,l }, where l i <l i+ for i=,.., -. It is assumed that the calls ca belog to MIP class ad all of them take (varyig) badwidth values from the same set B. The etwork tries to dyamically allocate badwidth such that each user's istat utility is maitaied above the miimum level ad, i the log ru, the badwidth is allocated fairly ad utilized efficietly. As described earlier, the commuicatio lik of each user ca be modelled by a k-state Markov chai: we ca idicate the average state-holdig time of each state m with t m ad the badwidth degradatio ratio of the state with D m, where D m <, m k. If, at a particular time istace, r i is the amout of badwidth that the etwork is allocatig to user i, we defie the received istat utility as u i = U i ((-D i,m )*r i ). Oe of the objectives of the badwidth allocatio scheme is to guaratee the miimum utility level for each user i; if we defie utility outage as the evet that user i s istat utility level falls below the miimum, the scheme should guaratee that the probability of a utility outage is smaller tha a certai threshold p outage. I additio, the fairess criterio should also be based o utility: cosiderig users i ad j with average utility u i,avg ad u j,avg respectively, we ca defie the ormalized gap of the average utility received ad the miimum level u *,mi as: G i =(u i,avg -u i,mi )/u i,mi, so we wat all users to have the same ormalized gap i the log ru (G i G j, i,j). Whe a user s lik degrades, it may surreder some badwidth to aother user, with a smaller ormalized gap; whe a lik upgrades the user may receive some badwidth from aother oe, with a larger ormalized gap; i this way there is a et gai i the combied istat utility. If at a particular time user i s lik state chages to state p, the followig steps are performed: ) all users average utility level ad ormalized gap are updated; 2) users are sorted i icreasig order of ormalized gap; 3) if the istat utility level of user i is below the miimum, some users badwidth will be reduced ad reallocated to user i to meet its ui,mi; 4) if there is o step three, user i may give up part of its badwidth to aother user if the lik degrades, whereas it may receive some badwidth if the lik upgrades. We call the user who gives up part of its badwidth to others the beefactor, ad the user who receives badwidth from others the beeficiary. I the third step, to satisfy user i s u i,mi, the scheme searches for beefactor(s) startig from the user with the largest ormalized gap. Suppose the user with the largest ormalized gap is user j, whose lik is curretly i state q ad it is above u j,mi. User j will yield ri,mi rj,mi mi( ri, rj ) Di, p D j, q amout of badwidth to user i, where r i ad r j are the badwidth allocated to users i ad j, respectively, before the lik state trasitio. This procedure will be repeated util u i,mi is reached or all the users have bee checked. Whe user i s lik degrades, the scheme will search for a appropriate beeficiary, checkig the users i icreasig order of ormalized gap; whe the beeficiary is foud, the scheme decides the amout of badwidth to trasfer betwee the users, tryig to maximize the combied utility of them. This procedure is repeated util oe beeficiary is foud or all users with smaller ormalized gap tha user i s have bee checked. Similarly, whe user i s lik upgrades, user i becomes the beeficiary ad users with larger ormalized gap are the cadidates for beefactor. The scheme checks the cadidates i decreasig order of ormalized gap ad, whe the beefactor is foud, the scheme decides the amout of badwidth to exchage, maximizig the combied utility of the two users. Besides the lik state chages, adjustmets i badwidth allocatio are also eeded whe a user arrives (ew user) or departs. If r is the amout of badwidth which eeds to be collected from curret users because of a user arrival, user j with largest ormalized gap G j is to give up (7)

4 mi(max(, r j rj,mi ), r) (8) D j, q amout of badwidth, where q is the curret lik state of user j. This procedure will be repeated util eough badwidth has bee collected or all the curret users have bee serched. If after searchig all the curret users, the collected badwidth is still ot eough, the scheme will start a secod roud of collectio, agai startig from the user with the largest ormalized gap, but, this time, each chose user will be dropped out from the etwork. Similarly, if there is surplus badwidth, the users with the first k smallest ormalized gap are chose to receive the surplus badwidth. Each user ca icrease its effective badwidth up to the maximum effective badwidth level. To guaratee users miimum utility level, a admissio cotrol policy should be eforced to limit the umber of users i the system. Recallig that whe a user s istat utility falls below its miimum utility level there is a utility outage for the user, the probability p of such evet at ay time is: p ri = Pr D i= i,mi, mi > R, where m i is user i s lik state at the time istace, p mi is the probability of the user i s lik to beig i state m at a particular time, is the total umber of users icludig the ew oe ad R represets the badwidth associated to the wireless cell c. Modellig the wireless chael through a FSMC, it is possible to kow the value of p i the worst case, accoutig the chael state coditios i the followig way: rl, p = pm, A = { m, m2,..., m m,..., m k, > R}. i () Dl, m A l i The admissio cotrol algorithm works differetly for two classes of service (MIP, MDP). For MIP class, the flow is admitted if: C p, c C poutage, c= (9) () where C = umber of cells that mobile host will visit ad p outage is the outage probability of the wireless system (for MDP class, the coditio must be verified oly for the curret cell). So, whe a ew user arrives, the scheme calculates p,c as described ad if p,c p outage for each cell, the ew user is admitted, otherwise it is rejected. If a user j is admitted, it is iitially allocated r j,mi /(-D j,q ), where q is user j s curret lik state. The assiged amout of badwidth to j is cotributed by the users curretly i the etwork followig the algorithm we described previously. IV. SIMULATIONS Our simulated et cosists of 5 wireless cell, each oe covered by a access poit (as illustrated i figure 5) with badwidth capacity of 5.5Mbps; the access poits are wired coected, by a switchig subet, to the et-seder. I our model, each mobile host moves ahead i circular way: a user that is receivig data i cell 5 will visit cell, after a had-off. Each wireless lik is described by a 4-states Markov chai, with the followig parameters: Tab.. Values for the Markov chai model p i e i D i (%) t mi (s) e-5. Fig. 5. The simulated et The protocol used i the simulatios has bee the MRSVP [3] with MIP ad MDP services. The MIP services have the capability to make advace reservatio o the potetially visited cells offerig a adaptive QoS with the host mobility. The MDP services ca reserve the resources oly o the curret cell ad for this reaso they are ot able to guaratee a adaptive QoS with host mobility. The MIP services are evaluated for differet outage probabilities fixed o the CAC algorithm. The set of possible discrete badwidth levels (Kbps) is: B = {52, 64, 768, 896} ad the utility fuctio is the same of figure 4, so the set of istat utility values is: U = {,2,3,4} for all users. I our simulatios the traffic load is composed by MIP ad MDP flows, as provided i ISPNs: i particular, there are 8% MIP ad 2% MDP flows. The badwidth is maaged by the policies illustrated i Sectio III ad the outage threshold is the same for both flow classes (cojuctive badwidth maagemet). The mobile host ca move with average speed selected uiformly i rage [5,75] Km/h. The followig curves illustrates the performaces of the utility-orieted algorithm for differet values of outage threshold ad mobile host speed. From figure 6 it ca be observed that the allocated badwidth for MIP users is ear the maximum level for every host s speed ad decreases by icreasig the outage threshold: the admissio cotrol becomes less selective if the p outage value is icreased, so more MIP users ca eter the etwork; i this way, the available badwidth is shared amog a higher umber of cocurret flows, which receive a lower amout of resources. For the same reasos, the perceived utility from MIP users (figure 7) assumes differet values, depedig o the fixed threshold; higher p outage values imply lower perceived utility values. I figure 8 we ca see that the system utilizatio does ot exceed the 85% percetage ad decreases for higher speed or higher threshold values. As the user s speed icreases, the physical radio lik chages its state with higher frequecy, so more badwidth reallocatio are made by the system ad this implies a resource wastage; i additio, if a high threshold value (like ) is fixed, more users ca access the system, which tries to avoid outage evets more frequetly; this is aother reaso of badwidth wastage, which causes a uder-utilizatio of the etwork. The

5 absece of a high system utilizatio values derives from the presece of high percetage of MIP traffic (8%): there is a lot of badwidth wastage, due to the passive reservatios made by system (MIP flows reserve the maximum badwidth level i their remote cells). Figure 9 shows the average umber of admitted MIP flows ad, as discussed above, it ca be observed that there is a visible icrease for higher values of outage threshold: the system admits a larger umber of users, but gives smaller guaratees about the outage evets bw (Kbps) Fig. 6. Allocated badwidth to MIP services for differet outage probability p ad speed values Fig. 9. Admitted MIP flows for differet outage probability p ad speed values V. CONCLUSIONS I this paper we aalyzed the performaces of a proposed utility-orieted algorithm ad we also see that there is eed to cosider the physical lik variability, i order to give more effectiveess to badwidth allocatio schemes ad to take i accout the absece of ideality durig radio coectios. From simulatio results we observed that the chael degradatio becomes more evidet for high speed values ad the had-off umber icreases, but the pre-reservatio of MIP classes guaratees a full compliace to QoS parameters (outage probability ad maximized user utility fuctio) for low values of outage threshold, so the mobility effects are miimized. u Fig. 7. MIP received utility for differet outage probability p ad speed values u Fig. 8. System utilizatio (*) for MIP services for differet outage probability p ad speed values REFERENCES [] R. Brade, L. Zhag, Resource ReSerVatio Protocol (RSVP) - Versio Message Processig Rules, September 97. [2] Clark, D.D. Sheker, S. ad Zhag, Supportig Real-Time Applicatios I A Itegrated Services Packet Network: Architecture ad Mechaism., Proc. SIGCOMM 92, 92. [3] Talukdar A. K., Badriath B.R. ad Acharya A., MRSVP: A Reservatio Protocol for a Itegrated Services Packet Network with Mobile Hosts. [4] V.Bharghava, K-W.Lee, S.Lu, S.Ha, J-R.Li, D.Dwyer, The TIMELY Adaptive Resource Maagemet Architecture, IEEE Persoal Commuicatios Mag., pp.2-3, Aug.998. [5] Y.Cao, Victor O.K.Li, Utility-orieted Adaptive QoS ad Badwidth Allocatio i Wireless Networks, IEEE It. Cof. O Commuicatios (ICC22). [6] H.S.Wag, N.Moayeri, Fiite-State Markov Chael-A Useful Model for Radio Commuicatio Chaels, IEEE Tras. O Vehicular Techology, vol.44, o., pp.63-7, Feb.995. [7] Part:Wireless LAN Medium Access Cotrol (MAC) ad Physical Layer (PHY) specificatios: Higher-Speed Layer Extesio i the 2.4GHz Bad, IEEE Std 82.b-999. [8] F. De Rago, G. Aloi, S. Marao, A Efficiet Rate Adaptatio Scheme i Wireless Mobile Networks, to appear o Wireless Telecommuicatios Symposium (WTS24), Pomoa, Califoria, USA, May 24. [9] A.K.Talukdar, B.R.Badriath, A.Acharya, Rate Adaptatio Schemes i Networks with Mobile Hosts, Proc. Of ACM/IEEE MOBICOM,998