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 Unversty Dubln, Ireland {bogdan, munteang}@eeng.dcu.ee Keywords: Wreless broadcast networks, load balance, moblty management. Abstract Wreless local-area networks represent a vable broadband Internet access soluton for enterprse, resdental and publc areas. Due to ts short range rado, multple wreless access ponts are necessary to cover a certan physcal area. The tendency of moble users to group n certan areas of nterest and of moble devces to connect to the access pont wth the hghest sgnal strength determnes the overall network load to be hghly unbalanced. To overcome ths ssues whch drastcally affects user bandwdth share as well as the effcency of network resource utlzaton, specal load balancng technques has to be employed. Ths paper presents the Multmeda Moblty Management System (M3S), a qualty orented moblty management framework whch ams at maxmzng user perceved multmeda qualty by effcently dstrbutng the traffc load over all the communcaton resources avalable. Smulaton based testng results are presented, outlnng the performance of M3S aganst other load balancng technques whch rely on moble devce re-assocaton wth least congested access ponts. 1 Introducton Usng wreless technologes as the last lnk n the Internet access networks provde uncountable advantages ncludng user moblty and ubqutous servce provdng. Unlke the wred communcaton technologes where each lnk uses a dedcated transport medum, wreless moble devces have to share the common rado spectrum whch s a scarce and consequently hghly valuable resource. Wreless local-area networks (WLAN) defned by IEEE 802.11 standard represent a vable soluton for wreless broadband access for enterprse, resdental and publc areas. Due to ts short range rado, multple wreless access ponts are necessary to cover a certan area. As dfferent studes has shown [1, 3] moble users tend to group n certan areas of nterest (hot-spots) determnng an uneven dstrbuton of traffc load among network access ponts (AP). Traffc load unbalance n hot-spots s usually determned by the fact that moble devces scan the wreless channels to fnd the nearby APs and connect to the AP wth the strongest sgnal (RSSI). Selectng the AP only based on sgnal strength correlated wth moble users nclnaton to group n certan areas wll determne the AP closest to the hot-spot to be hghly loaded whle the other APs to be lghtly or totally unloaded. Ths load unbalance affects drastcally the bandwdth share that the user s allocated as well as the optmum network resource utlzaton. The network load unbalance can be reduced by usng specal user assocaton control algorthms [4]. Selectng the AP to whch a moble devce wll assocate when enterng the network, based on AP load metrcs, can sgnfcantly mprove the effect on other users bandwdth share and consequently user perceved qualty-of-servce (QoS). As user QoS demands are hghly dynamc related to both tme and locaton, smply by controllng the users admsson to the network does not optmze the network resource allocaton on a long term bass. To overcome traffc load varatons due to user moblty and dynamc demands, load balancng algorthms needs to be mplemented. The man goals of assocaton control and load balancng technques s to guarantee a mnmum user bandwdth share and QoS level whle effcently explotng network resources. In ths paper the Multmeda Moblty Management System (M3S) s presented. M3S s a moblty management framework for multmeda applcatons amng at mprovng user perceved multmeda qualty whle usng wreless networks for content delvery. M3S effcently dstrbutes the overall multmeda traffc over multple smultaneous connectons, each connecton usng a dfferent AP to exchange data packets. Load balancng s performed usng M3S s core handover management component, Smooth Adaptve Soft-Handover Algorthm (SASHA) whch s a qualty orented handover management system. SASHA gradually transfers the load from one connecton

(communcaton channel) to another, based on a Qualty of Multmeda Streamng (QMS) metrc. QMS s a comprehensve qualty metrc used to asses the capacty of each communcaton channel to provde a certan level of qualty for multmeda content delvery n the context of an overall QoS demand. By usng multple smultaneous connectons M3S can provde better user bandwdth share and QoS provsonng then a load balancng soluton whch rely on re-assocaton wth a less loaded AP when the current AP s overloaded. The remander of ths paper s as follows. Secton 2 presents the related work regardng load balancng technques. M3S archtecture s presented n Secton 3 whle the smulatonbased testng envronment and performance evaluatons are dscussed n Secton 4 and 5. In Secton 6 conclusons and future work are presented. 2 Related Work Load balancng n wreless access networks have already receved sgnfcant attenton, several solutons beng proposed n the lterature. Varous wreless network equpment manufacturers have already ncorporated load balancng features n ther products [12, 13]. In these mplementatons the wreless APs broadcast load nformaton wthn the beacon messages nformng the potental canddates for assocaton about ther level of congeston. Based on ths nformaton wreless moble devces can chose to assocate wth the least congested AP then wth the closest one, whch presents the hghest RSSI. To acheve maxmum effcency, load metrcs represent a very mportant component of assocaton control and load balancng technques. Dfferent metrcs are proposed n the lterature [10], typcally relyng on the number of moble devces currently assocated wth an AP, the RSSI of users currently connected to the AP or the bandwdth a new user can get f t s assocated wth a certan AP. Network load balancng technques can be developed as centralzed or dstrbuted algorthms. Some of the proposed solutons can be used n both centralzed and dstrbuted systems. Balachandran et al. present a centralzed load balancng soluton n [2]. To access the network, moble users have to submt to the admsson control server a servce level specfcaton request whch contans the mnmum and maxmum bandwdth requred. Based on the overall network load nformaton the central coordnaton server can grant access to the currently assocated AP or can advse the moble devce to swtch the rado channel and assocate to another, least congested AP. To mprove network resource allocaton on a larger scale the central coordnaton server may advse the moble user to change ts locaton wthn the range of other APs whch are very lghtly loaded and can provde a better QoS. Another centralzed soluton s presented n [4]. The proposed algorthm runs on a network operaton centre (NOC) and decdes on the optmum user-ap assocaton to mprove resource fare-shearng. Due to user moblty and network dynamcs, NOC perodcally reassesses the network load and recalculates the optmal user-ap assocaton. The man drawbacks of a centralzed approach to assocaton control and load balancng s the reduced scalablty, sngle pont of falure represented by the centralzed coordnaton unt and also hgh mantenance costs nvolve by the central unt. A completely dstrbuted load balancng soluton s presented n [11]. In ths approach, agents runnng at each wreless AP, montor the congeston level of ts host. These agents communcate over the wred backbone nfrastructure, used to connect the APs to the core network, broadcastng and recevng load nformaton to and from other agents resdng on neghbour APs. Based on ths nformaton each agent can determne locally the dstrbuton of network resources. Each agent wll estmate the load level of ts AP, whch can be under-loaded, balanced and overloaded. Under-loaded APs wll accept new moble statons whle overloaded APs wll determne some of the already connected moble devces to handoff to other least loaded APs. Dstrbuted load balancng based on cell-breathng technque s dscussed n [9]. The man drawback of dstrbuted load balancng technques s the autonomous decson makng performed by each network devce whch can nvolve unpredctable behavour for the network, leadng to suboptmal resource allocaton or even servce qualty degradaton. The work n [6] presents a load balancng algorthm whch can be used both as centralzed and dstrbuted soluton. Ths algorthm consders tme and channel allocaton n an nteractve manner amng at optmzng network resource allocaton n the context of heterogeneous farness and servce requrements. 3 M3S System Archtecture Most of the load balancng technques reles on determnng the optmal user-ap assocaton and routng the whole traffc through the selected AP. In certan areas when the network s hghly loaded the nfrastructure may not be able to accommodate a new user wth ts requred bandwdth share only by assocatng t wth a sngle AP. In ths stuaton a mult-connecton load balancng technque has to be employed. Such a soluton s mostly approprate for multmeda applcatons where mult-stream transport solutons are already proposed [8]. 3.1 Multmeda Moblty Management System Multmeda Moblty Management System s a qualty orented moblty management framework for multmeda applcatons. M3S ams at maxmzng user perceve multmeda qualty by dstrbutng effcently the traffc load over multple smultaneous connectons (communcaton channels). Fgure 1 generally descrbes the prncple of usng multple smultaneous connectons to delver multmeda content to moble users. In the context of M3S multple

Fgure 1: Mult-Connecton Multmeda Moblty Management System. Multmeda Applcaton M3S QMS1 QMS2 QMS3 DCCP or UDP DCCP or UDP DCCP or UDP Fgure 3: Smooth Adaptve Soft-Handover Algorthm. 802.21 802.21 WF WMax GPRS M3S Multmeda Moblty Management System QMS Qualty of Multmeda Streamng Fgure 2: Multmeda Moblty Management System Archtecture. smultaneous connectons refers only to the wreless lnks, assumng that the APs are connected to the core network va wred hgh-speed backbone nfrastructure whch s capable of provdng the requred bandwdth and QoS. Also t s assumed that the moble devce s capable of parallel communcaton over multple channels. Ths can be acheved by usng multple nterfaces or possbly the more flexble concept of software rado [5]. As presented n Fgure 1 M3S consst of a clent sde module and a server sde module. Fgure 2 shows a more detaled archtectural representaton of M3S. The clent-sde module scans the wreless medum determnng the avalable APs whch have a suffcent RSSI level to sustan a communcaton channel to the server. The clent opens a connecton wth the server mostly for each of the wreless resource avalable (AP). The traffc allocaton to these connectons s performed by the server based on the Qualty of Multmeda Streamng metrc whch s assessed for each ndvdual connecton and perodcally updated to montor and react to user and network dynamcs. To provde the nformaton requred by the server to assess QMS, the clent montors QoS parameters on each connecton and also harvest nformaton related to user preferences, wreless nterfaces power consumpton and data transfer servce costs. As depcted n Fgure 2, IEEE 802.21 Meda Independent Handover (MIH) may be used to harvest network related nformaton. 3.2 Qualty of Multmeda Streamng The QMS metrc s represented by the formula n equaton (1) and s manly composed of a QoS (throughput, loss, delay and jtter) and a qualty-of-experence (QoE) whch s bascally assessed by PSNR. To maxmze effcency, cost (Cost), power effcency (PEff) and user preferences (UPref) s are also ncluded. More detals about QMS and ts components are presented n [7]. QMS = w * QoS w * Cost 3 1 + w * PEff 4 + w * QoE 2 + w * U Pr ef 5 + For maxmum effcency and flexblty weghts are assocated wth each component. Weghts normalzaton s requred, so the condton from equaton (2) has to be respected. 5 1 (1) w = 1 (2) 3.3 Smooth Adaptve Soft-Handover Algorthm SASHA s a novel qualty orented handover management and s the core component of M3S. SASHA performs handover from one AP to other by gradually transferrng the load from one connecton to the other based on QMS scores. Fgure 3 presents an example of load dstrbuton between two APs performed usng SASHA n the stuaton of a moble devce movng wthn the overlappng area of the two APs. In stage 1 the moble node s closer to AP1, all the traffc beng routed through AP1 due to better QMS scores of AP1 connecton determned by the AP2 lnk fadng. In stage 2 the moble node s postoned n between the two APs, QMS scores beng smlar for both lnks. In ths stuaton the traffc s dstrbuted evenly among the two connectons. In stage 3 the moble

Clent Phase 1 Scan avalable APs Phase 2 Select some of the APs Establsh Connectons Server Phase 3 For Each Connecton Compute QMS Fgure 5: Smulaton topology Phase 4 Dstrbute Traffc YES Mn QoS provded NO Fgure 4: SASHA load balancng algorthm. node moves closer to AP2 determnng AP1 lnk to fade and consequently the QMS scores of AP1 to drop. In ths stuaton the whole traffc wll be routed through AP2. For smplcty, the example n Fgure 3 was presented n three dstnct stages. In a real scenaro the QMS scores wll be contnuously updated followng the dynamcs of the network determnng the traffc to be contnuously balanced between the avalable communcaton lnks. The same traffc dstrbuton algorthm, as descrbed above n case of node moblty, can be appled when an AP became congested, requrng the load to be partally or totally transferred to a new AP. Fgure 4 descrbes the load dstrbuton algorthm used by SASHA. Ths algorthm s dstrbuted over the M3S clent and server modules and conssts on several phases. The frst phase s to scan the wreless medum and determnng the avalable networks. In the second phase some of the networks are selected, based on user preferences, power consumpton or cost, and the correspondng connectons wth the server are establshed. These two phases are performed by the clent module. The next two phases, phase 3 and 4 are performed by the server. In phase 3 the QMS scores are computed for each ndvdual connecton. In phase 4 the traffc s dstrbuted over the exstng connectons accordng to the QMS scores. Each connecton wll transport a share of the overall traffc load, proportonal wth ts QMS score. To provde the user wth at least the mnmum level of QoS, whch n ths case represents bandwdth, the total throughput provded by the exstng connectons s checked aganst a threshold negotated wth the user. If the total bandwdth s close to the threshold or n the worst case below the threshold Fgure 6: Constant bt rate background traffc phase 1 and phase 2 of the algorthm are ntated at the clent module. 4 Smulaton-based Testng Envronment M3S performance was evaluated by smulatons conducted usng NS-2 Network Smulator [14] enhanced by Marco Fore s realstc rado patch [15]. Fgure 5 presents the smulaton scenaro whch s based on two access ponts connected to a common router through wred nfrastructure. The router s further connected to a multmeda streamng server. The moble devce s postoned between the two APs wthn ther rado coverage overlappng area. As the performance of M3S s assessed from the pont of vew of load balancng due to network congeston and not user moblty the moble devce s consdered to have a fxed poston. The background traffc s generated by four wreless nodes. Two of the traffc generator nodes are wthn AP1 coverage area and are assocated wth t and the other two are wth AP2 coverage area and consequently are assocated wth ths AP. The constant bt rate background traffc used for M3S performance evaluaton s presented n Fgure 6. Four load levels are consdered for each AP. Totally unloaded (0Mbps), lghtly loaded when the background traffc s 2.5 Mbps, fully loaded when 3.5 Mbps background traffc s generated and overloaded when 4.5 Mbps background traffc s consdered. As t can be seen n Fgure 6 the sequence of lght and hgh traffc load perods are complementary to avod the stuaton

Fgure 7 Throughput, Loss and PSNR for load balancng usng M3S when both APs are overloaded, makng mnmum QoS provsonng mpossble. To mplement M3S on NS-2 the wreless node was changed to allow multple smultaneous connectons over dfferent wreless channels. M3S was deployed n an applcaton whch s capable of sendng a constant bt rate multmeda content (1.5 Mbps). A re-assocaton based load balancng technque, referred n ths paper as RLB, s mplemented by swtchng the traffc from one AP to the other accordng to the nduced level of congeston. The RLB mplementaton s optmstc as the tme requred to assess AP load s not consdered. For the stuaton when no load balancng technque s used the traffc s constantly routed through one of the APs. 5 Performance Evaluaton and Result Analyss The performance of the load balancng technque based on M3S was evaluated usng Throughput, Loss as QoS metrcs and PSNR as a user perceved qualty metrc. The smulatonbased testng results for M3S load balancng, re-assocaton load balancng (RLB) and the stuaton when no load balancng s used (NO LB) are presented n Fgure 7, 8 and 9. As presented n Fgure 6 three network loadng stuatons were consdered. In the frst stuaton, one of the APs s overloaded (4.5Mbps background traffc) whle the other one s totally unloaded (0 Mbps background traffc). In the second case one AP s overloaded (4.5 Mbps background traffc) whle the other s lghtly loaded (2.5Mbps background traffc). In the last case both APs are fully loaded (3.5 Mbps Fgure 8 Throughput, Loss and PSNR for load balancng usng RLB background traffc). These loadng condtons are sequental n tme and repettve. As outlned n Fgure 7, M3S performs well n all these stuatons presentng nsgnfcant loss rates exceptng the perod when both APs are fully loaded (100s 150s) when a 0.08 Mbps loss rate s encountered. From the pont of vew of PSNR the average values are constantly above 51db wth a maxmum of 70db. The re-assocaton-based load balancng technque performs well when at least one AP s lghtly loaded or unloaded. As t can be seen n Fgure 8, the throughput s maxmum (1.5Mbps) for all network load stuatons except the one when both AP are fully loaded (100s 150s) when the throughput drops to 1Mbps. The same behavour can be observer by analyzng loss and PSNR n Fgure 8. When no load balancng technque s used, as presented n Fgure 9, the QoS drops dramatcally when the AP s overloaded as the moble devce remans connected to ths AP. When the background traffc decreases, the AP becomes lghtly loaded or totally unloaded determnng a QoS ncrease to the maxmum as t can be seen n Fgure 9 (150s 250s). In Table 1 the average values of Throughput, Loss and PSNR are presented for three ndvdual load stuatons (phases). In Phase 1 AP1 has 4.5 Mbps background traffc (overloaded) and AP2 has 0Mbps background traffc (unloaded). In Phase 2, AP1 has 4.5 Mbps background traffc (overloaded) and AP2 gets 2.5 Mbps background traffc (lghtly). In Phase 3 both APs have fully loadng background traffc (3.5 Mbps). As t can be seen n the table the performance of M3S load

several smultaneous connectons explotng all the communcaton resources avalable. As SASHA dstrbutes shares of the overall applcaton traffc on several connectons usng dfferent APs the user bandwdth share mproves wth 51% and the user perceved qualty mproves by 157% compared to load balancng technques based on user-ap reassocaton. Future works wll asses the performance of SASHA wth more background traffc patters ncludng varable bt-rate traffc. Varous network loadng scenaros wll be used as well as dfferent network topologes. Heterogeneous wreless envronments wll also be consdered. Acknowledgements The support of Mcrosoft Research and Irsh Research Councl for Scence, Engneerng and Technology s gratefully acknowledged. References Fgure 9 Throughput, Loss and PSNR obtaned wthout load balancng Throughput Loss PSNR Phase (Mbps) (Mbps) (db) 1 1.50 0.00 57.6 SASHA 2 1.50 0.00 56.8 3 1.46 0.08 51.0 1 1.50 0.00 55.3 RLB 2 1.50 0.00 55.5 3 0.99 0.51 19.8 1 0.69 0.80 11.9 NO LB 2 1.10 0.39 23.55 3 1.29 0.20 33.16 Table 1: Throughput, Loss and PSNR for three dstnct load phases. balancng and re-assocaton (RLB) load balancng are smlar when at least one AP s capable of provdng the requred QoS. The performance of M3S load balancng mproves wth 51% n terms of throughput and 157% n terms of PSNR when both APs are fully loaded. 6 Conclusons and Future Work Load balancng represents a key element n provdng hgh qualty wreless broadband access whch s mostly requred by the users accessng multmeda content over the Internet. Ths paper presents the Multmeda Moblty Management System (M3S) whch performs load balancng usng the novel qualty orented handover management system, Smooth Adaptve Soft-Handover Algorthm (SASHA). M3S mproves user bandwdth share and the overall network resource allocaton by dstrbutng the applcaton traffc over [1] A. Balachandran, G. M. Voelker, P. Bahl, and P. V. Rangan, Characterzng user behavor and network performance n a publc wreless LAN, n Proc. of ACM SIGMETRICS, pp 195 205, (2002). [2] A. Balachandran, P. Bahl and G.M. Voelker, "Hot-spot congeston relef n publc-area wreless networks," n Proc. Fourth IEEE Workshop on Moble Computng Systems and Applcatons, pp. 70-80, (2002). [3] M. Balaznska, P. Castro, Characterzng moblty and network usage n a corporate wreless local-area network, n Proc. of USENIX MobSys, (2003). [4] Y. Bejerano, S. Han and L. L, Farness and load balancng n wreless LANs usng assocaton control n Proc. 10th Annual nternatonal Conference on Moble Computng and Networkng, MobCom '04, (2004). [5] E. Buracchn, "The software rado concept," IEEE Communcatons Magazne, vol.38, no.9, pp.138-143, (2000). [6] J.K. Chen, T.S. Rappaport, G. de Vecana, "Iteratve Water-fllng for Load-balancng n Wreless LAN or Mcrocellular Networks," n Proc. 63 rd IEEE Vehcular Technology Conference, vol.1, pp.117-121,( 2006). [7] B. Cubotaru, G. -M. Muntean, SASHA - A Qualty- Orented Handover Algorthm for Multmeda Content Delvery to Moble Users, submtted to Specal Issue on IPTV n Multmeda Broadcastng, IEEE Transactons on Broadcastng, (2009). [8] S. Mao, S. Ln, Y. Wang, S. S. Panwar, Y. L, Multpath vdeo transport over wreless ad hoc networks, IEEE Wreless Communcatons, Specal Issue on Advances n Wreless Vdeo, Vol. 12, No. 4, pp. 42 49, (2005). [9] G. Nunz, S. Schuetz, M. Brunner, "Desgn and Evaluaton of Dstrbuted Load-Balancng for Wreless Networks", n Proc 10th IFIP/IEEE Internatonal Symposum on Integrated Network Management, pp.478-486, (2007).

[10] I. Papankos and M. Logothets, A study on dynamc load balance for IEEE 802.11b wreless LAN, n Proc. COMCON, (2001). [11] H. Velayos, V. Aleo and G. Karlsson, "Load balancng n overlappng wreless LAN cells," n Proc. IEEE Internatonal Conference on Communcatons, vol.7, pp. 3833-3836,(2004). [12] Proxm Wreless Networks. ORINOCO AP-600 data sheet, 2004. [13] Csco Systems Inc. Data sheet for Csco Aronet 1200 seres, 2004. [14] Network Smulator-2, http://www.s.edu/nsnam/ns. [15] http://www.tlc-networks.polto.t/fore.