vskyconf: Cloud-assisted Multi-party Mobile Video Conferencing

Transcription

1 vskycof: Cloud-assisted Multi-party Mobile Video Coferecig ABSTRACT Yu Wu Dept. of Computer Sciece The Uiversity of Hog Kog Bo Li Dept. of Computer Sciece ad Egieerig, Hog Kog Uiversity of Sciece ad Techology As a importat applicatio i today s busy world, mobile video coferecig facilitates people s virtual face-to-face commuicatio with frieds, families ad colleagues, via their mobile devices o the move. However, how to provisio high-quality, multi-party video coferecig experieces over mobile devices is still a ope challege. The fudametal reaso behid is the lack of computatio ad commuicatio capacities o the mobile devices, to scale to large coferecig sessios. I this paper, we preset vskycof, a cloud-assisted mobile video coferecig system to fudametally improve the quality ad scale of multi-party mobile video coferecig. By ovelly employig a surrogate virtual machie i the cloud for each mobile user, we allow fully scalable commuicatio amog the coferece participats via their surrogates, rather tha directly. The surrogates exchage coferecig streams amog each other, trascode the streams to the most appropriate bit rates, ad buffer the streams for the most efficiet delivery to the mobile recipiets. A fully decetralized algorithm is desiged to decide the best paths of streams ad the most suitable surrogates for video trascodig alog the paths, such that the limited badwidth is fully utilized to deliver streams of the highest possible quality to the mobile recipiets. We also carefully tailor a bufferig mechaism o each surrogate to cooperate with efficiet stream distributio. We have implemeted vskycof based o Amazo EC2 ad verified the excellet performace of our desig, as compared to the widely adopted uicast solutios. Categories ad Subject Descriptors J. [Computer Applicatios]: Geeral Keywords Cloud computig, Video coferecig, Mobile computig Permissio to make digital or hard copies of all or part of this work for persoal or classroom use is grated without fee provided that copies are ot made or distributed for profit or commercial advatage ad that copies bear this otice ad the full citatio o the first page. Copyrights for compoets of this work owed by others tha ACM must be hoored. Abstractig with credit is permitted. To copy otherwise, or republish, to post o servers or to redistribute to lists, requires prior specific permissio ad/or a fee. Request permissios from Permissios@acm.org. MCC 13, August 12, 213, Hog Kog, Chia. Copyright 213 ACM /13/8...$15.. Chua Wu Dept. of Computer Sciece The Uiversity of Hog Kog cwu@cs.hku.hk Fracis C.M. Lau Dept. of Computer Sciece The Uiversity of Hog Kog fcmlau@cs.hku.hk 1. INTRODUCTION Video coferecig has bee widely deployed for virtual, faceto-face commuicatio amog separate parties, as a greeer solutio to replace may of the eergy-expesive coferece travels. Beefitig from the advaces i mobile ad wireless commuicatio techologies, a umber of mobile video coferecig applicatios [1] have emerged. May of them rely o expesive, dedicated architectures, e.g., multiple cotrol uits (MCU), to process sigalig messages, trascode igress sessio streams ad dissemiate multiple streams to each ed device. Alteratively, distributed peerto-peer (P2P) based mobile video coferecig systems have also sprug up, e.g., Skype mobile leverages itermediate super odes for sessio relays. I order to fid out how well the the existig mobile video coferecig systems support multi-party video coferecig over mobile devices, we have coducted a survey of the seve represetative applicatios, with results give i [1].We observe that applicatios with ifrastructure support ca support more cocurret users i each sessio (but still typically o more tha 4), at the cost of expesive up-frot ivestmet which may prohibit their wide adoptio by small or medium istitutios; P2P-based solutios are reluctat to allow group video calls for a fear of compromisig call qualities, (e.g., Skype oly supports two-way visual commuicatio o mobile phoes), ad most of them stick to a sigle flat streamig rate, or a limited umber of bit rates (e.g., 2).A fullyadaptive, multi-party mobile video coferecig solutio is still pedig to achieve. We summarize the key challeges as follows: (1) The workload o each ode i a video coferecig sessio, i terms of both processig ad trasmissio, scales quadratically to the umber of participats i the sessio, leadig to sigificat challege whe usig mobile devices for multi-party video coferecig. (2) Mobile users are equipped with differet devices ad dowlik speeds; a high-quality solutio should eable differetiated call qualities to differet users, istead of a homogeeous video broadcast quality eforced by the low-ed users, as i a traditioal solutio. I this paper, we preset vskycof, a cloud-assisted mobile video coferecig solutio to fudametally eable high-quality, multiparty video coferecig over heterogeeous mobile devices. The cloud computig paradigm offers ubiquitously accessible computig resources, with o-demad resource provisioig at the modest cost. The paradigm particularly compesates well for the iheret 33

2 resource deficiecies of mobile devices, ad catalyzes the udergoig evolutio i the burgeoig mobile computig idustry. I vskycof, we dyamically provisio a virtual machie i the cloud as the exclusive surrogate for a dialed-i mobile user. Each mobile device dissemiates/receives the video streams to/from its surrogate; the surrogates exchage coferecig streams amog each other, trascode the streams to the most appropriate bit rates, ad buffer the streams for the most efficiet delivery to the mobile recipiets. By leveragig the more powerful processig capabilities ad stable wired etwork badwidths, mobile users shift those otherwise o-device tasks to the cloud, yieldig superior power reductio ad quality ehacemet, as well as achievig fully scalable commuicatio amog the coferece participats. To realize such a solutio, we desig a fully decetralized, efficiet algorithm to decide the best delivery paths of streams amog the surrogates (possibly distributed i differet cloud data ceters), ad the most suitable surrogates for video trascodig alog the paths. We also carefully tailor a bufferig mechaism o each surrogate to cooperate with the efficiet stream distributio. Together they guaratee bouded, small ed-to-ed latecies ad smooth stream playback at the mobile devices at the highest possible qualities, i each video coferecig sessio. We have implemeted a prelimiary versio of vskycof based o Amazo EC2, ad coducted experimets i the real-world settigs. The results reveal the high scalability, full adaptability, ad excellet video coferecig qualities achieved by our desig, as compared to the widely adopted uicast solutios. The remaider of this paper is orgaized as follows. We itroduce related literature i Sec. 2, preset uique challeges ad the system architecture i Sec. 3, ufold desig details i Sec. 4, itroduce our prototype implemetatio ad evalutio i Sec. 5, ad fially coclude the paper i Sec RELATED WORK Despite extesive studies durig the past decades, video coferecig (VC) has recaptured people s iterest i this ew smartphoe era, with a series of works ad systems sprigig up recetly [9][2] [4][7], which ca be categorized ito Server-to-Cliet (S/C) based ad Peer-to-Peer (P2P) based solutios. Compared to the S/C-based structure, P2P has bee deemed as a more promisig ad scalable solutio. Both Poec et al. [9] ad Che et al. [2] formulate utility maximizatio problems ad eable multi-party VC by buildig multi-rate multicast trees. They focus more o the streamig rate allocatio over physical liks, but do ot ivestigate much the trascodig flexibilities. Liag et al. [7] leverage the upload capacities of helpers from differet swarms, i similar ways as adopted by Skype (ot Skype mobile). Though promisig, these solutios are difficult to achieve i practice amog mobile users, who are reluctat to cotribute resources to stragers due to costraied batteries ad expesive cellular data fees. The domiat P2P-based solutio i the real world is still pair-wise uicast (e.g., Frig, Tago, etc.[1]), where a user directly exchages streams with each of the other users i the same coferecig sessio. I this way, the limited uplik badwidths of mobile devices sigificatly restrict the sessio size. Cloud computig, as a agile solutio, compesates well for the deficiecies of mobile devices for media streamig i terms of both processig ad badwidth supports. Traditioal players i the VC market have recetly claimed their support for mobile users via their private clouds. But their solutios are mostly cetralized i a private cloud with abudat ifrastructure resources to support eterprise users. For example, Vidyo [1] provides its cloud-based solutio by provisioig virtual MCUs o top of their Iitiator First/Last-mile Streams Cotrol Sigals Video Streams Participator Participator Figure 1: The architecture of vskycof. Participator VidyoRouters, bearig similar flavors to their traditioal dedicated ifrastructures. I cotrast, our desig ovelly provisios a VM surrogate for each mobile user i a public cloud i a more affordable maer, caterig for the eeds of ordiary mobile users i their daily life. A recet work by Feg et al. [3] optimally leverages iter-dataceter etwork badwidths to maximize the overall throughput of all coferecig sessios, based o itra-sessio etwork codig. vskycof cosiders both dyamic sessio routig ad adaptive sessio trascodig, ad exploits surrogates i a cloud ifrastructure for scalable video coferecig amog mobile devices. Huag et al. [4] leverage clouds to ecode videos ito layered rates usig scalable video codig (SVC), to eable differetiated streamig qualities to users with differet available badwidths. We do ot cosider SVC ecodig i this work, sice the ecodig complexities ievitably icur itolerable delays for a time-sesitive applicatio like video coferecig. 3. ARCHITECTURE vskycof eables efficiet, peer-to-peer fashioed, multi-party mobile video coferecig via a IaaS cloud, with the architecture preseted i Fig. 1. We refer to a video coferece call amog multiple mobile users as a sessio. The user which starts the coferece call is the iitiator of the sessio. A surrogate, i.e., a virtual machie (VM) istace, is created i the IaaS cloud for each mobile user. The IaaS cloud cosists of disparate data ceters i differet geographic locatios, ad the surrogate for each mobile user is assiged i a data ceter proximate to the user. As a proxy for the mobile device, a mobile user s surrogate is resposible for the followig: (i) sessio maiteace, by exchagig cotrol messages with other surrogates i a timely ad efficiet maer; (ii) video stream dissemiatio ad trascodig, by receivig the video stream its correspodig mobile user produces, trascodig it ito appropriate format(s), distributig it to other users surrogates, ad the other way roud as well; (ii) efficiet video stream bufferig for its mobile user, for timely, smooth ad robust streamig to the correspodig mobile device. A mobile user just eeds to sed the stream it geerates ad receive streams other users produce to ad from its surrogate, ad is effectively freed from power-cosumig stream processig ad itra-sessio commuicatio. A gateway server i vskycof loosely keeps track of participatig users ad their surrogates, which ca be implemeted by a stadaloe server or VMs i the IaaS cloud. Fig. 2 depicts the key modules implemeted o a sigle surrogate, which ca be divided ito two parts: Cotrol Plae is the brai of the surrogate, resposible for cotrol sigalig betwee this surrogate ad eighborig surrogates. It measures the latecies ad badwidths o the coectios from/to eighborig surrogates, ad all the collected iformatio is stored i the peer table, which costructs a partial view of the video coferecig topology from this surrogate s poit of view. Utilizig the collected iformatio, the surrogate computes routig paths for 34

3 Data Plae Data I/O paths, trascodig, jitter maagemet Jitter Mask I-gress Queue Trascoder E-gress Queue Cotrol Plae Resource allocatio, sessio maiteace ad call routig Route Computig Flow Request Lik Measuremet Heartbeat Other surrogates Peer Table Path Broadcast Figure 2: The key modules of a surrogate. streams from its correspodig mobile user to other mobile users, ad participates i the costructio of optimal video dissemiatio trees. It also moitors the call qualities ad determies the best video ecodig parameters (codecs, bitrates, etc.) for streams from/to its mobile device. Data Plae is resposible for processig i/out video streams, i terms of both trascodig ad forwardig, as directed by the cotrol plae. The video stream from its mobile user is captured cotiuously ad dissemiated to other surrogates after ecessary trascodig. I the reverse directio, all video streams from other mobile users, via their respective surrogates, are trascoded ito appropriate rates (if ecessary) ad delivered to the mobile user by a key module jitter mask, which deals with radom jitters caused by fluctuatios of processig ad etwork latecies, as well as ay aomalies alog the dissemiatio paths. Our desig of vskycof observes the followig priciples. Decetralized Cotrol. Except ecessary bootstrappig from the gateway server, each sessio is to be maitaied by the surrogate of the iitiator of a coferece sessio, i order to provide good scalability ad flexibility. The video routig ad trascodig decisios are to be made i a fully distributed fashio by collaboratios amog surrogates. Self-Evolvig Routig Topology with Full Adaptivity. We seek to build a best routig topology amog the surrogates for dissemiatig the stream from each participat, which achieves a small ed-to-ed latecy ad fully exploits the available badwidths amog the surrogates. Trascodig decisios to covert the origial stream to acceptable formats/bit rates of the recipiets are dyamically made at the best poits alog the dissemiatio paths, accordig to differet computatio capacities of the surrogates ad eeds of dowstream mobile devices. Robust, Smooth Video Streamig. To guaratee smooth stream playback at each mobile user eve i cases of iaccurate route computatio (e.g., due to iaccurate estimates of lik badwidths ad latecies), we seek to desig a advaced error correctio mechaism to search for better routig paths before the call quality drops, by moitorig a carefully desiged jitter buffer at each surrogate. 4. DETAILED DESIGN 4.1 Sessio Maiteace Establishmet: Whe a mobile user logs i to the vskycof system via the gateway server, it is assiged a surrogate VM. The gateway ca maitai iformatio o a pool of available, pre-iitiated VMs i the IaaS cloud, ad assig oe from the pool to a mobile user based o geographic proximity of the two, to expedite the service. The surrogate of the sessio iitiator fids out IP addresses of surrogates of the other olie users from the gateway server, which it wishes to ivite to joi the video coferecig sessio. The iitiator the cotacts ad ivites the iterested participats through their surrogates directly, ad maitais a list of IP addresses of all active surrogates i the sessio. Tear-dow: Whe a mobile user leaves the system, its surrogate VM is released ad retured to the pool of available VMs i the IaaS cloud. If the iitiator of a sessio departs, its hostig role is haded over to aother substitute surrogate i the participat list. 4.2 Routig Computatio I a video coferecig sessio with S users, there are S streams, each produced by oe of the mobile users, to be delivered to all the other users. We model a mathematical optimizatio problem for costructig efficiet dissemiatio topologies of all streams i a sessio ad decidig the optimal trascodig locatios. We the desig efficiet, fully distributed heuristic to approach the optimal solutio i a dyamic system. For trascodig, we practically oly cosider dow-samplig of a stream, i.e., the reductio of streamig bit rate, but ot the reverse, sice up-samplig provides o quality improvemet but cosumes uecessary badwidth. We also focus o trascodig due to mismatched bit rates of streams of the same format, while the case of trascodig from oe format to aother ca be readily addressed with similar efforts Optimizatio Formulatio Let graph G =(S, E) represet the etwork of surrogates i a sessio, where S is the set of surrogates ad E is the set of directed coectios amog the surrogates. For each surrogate m 2 S, let ˆm represet the correspodig mobile user. Let S = S. Suppose C ij is the maximum available badwidth o lik (i, j) 2E, ad d ij deotes the lik latecy. We refer to the stream from a surrogate m 2Sas flow m, with source rate R (m) ˆm, which is the rate of icomig stream from mobile user ˆm to surrogate m, determied by the source capturig rate by the user s mobile camera ad the uplik rate from the mobile user. Let R (m) ˆ be the maximum acceptable bit rate of flow m at mobile user ˆ, as decided by the last-mile dow-lik badwidth from surrogate to ˆ, ad the allocatio of this dow-lik badwidth amog streams from differet users, e.g., if user ˆ sizes playback widows of streams from S 1 1 S other coferece participats equally o its device scree, of 1 the dow-lik badwidth should be allocated to each stream. The multicast flow m from surrogate m to all other surrogates ca be viewed as cosistig of S 1 coceptual uicast flows [6], from m to each of the other surrogates, respectively. These coceptual uicast flows co-exist i the etwork without cotedig for lik badwidths, ad the multicast flow rate o a lik is the maximum of the rates of all the uicast flows goig alog this lik. For ease of trascodig implemetatio, we restrict each uicast flow from m to to be a itegral flow alog oe path with the ed-to-ed rate r (m), ad the multicast topology is the overlap of all the S 1 uicast flow paths. Let biary variable Iij m idicate whether the coceptual uicast flow from m to traverses lik (i, j) 2E, ad c (m) ij deote the actual rate of the multicast flow m o lik (i, j). Let fuctio ' (r 1,r 2) give the trascodig latecy at surrogate, if the rate r 1 of a igress flow received by is higher tha the rate r 2 of the egress flow from. ' (r 1,r 2) = if r 1 apple r 2. Typical trascodig steps are to decode the source stream of rate r 1 to a itermediate format, ad the re-ecode the stream from the itermedia format to the destiatio rate r 2 [8]. Hece, trascodig delay ' (r 1,r 2) is mootoously icreasig o both r 1 ad r 2, ad depeds o computatio capacity of the surrogate VM : the more powerful the VM is, the faster the trascodig ca be accomplished. The quality of service i the coferecig sessio relies o two aspects: (i) the ed-to-ed latecy ad (ii) the flow rate received by each participat for each flow. We boud the ed-to-ed latecy, 35

4 from the time a source surrogate m emits flow m to the time a receiver surrogate is ready to push the stream to its correspodig mobile user, by L (m), whose value is dyamically set as discussed i Sec Let U( r(m) R (m) ˆ ) be a icreasig, cocave utility fuctio o the rate of flow m received by surrogate, r (m). We maximize the aggregate utility of all receivers i all flows as our objective. The optimizatio problem is formulated i (1). subject to: Iij m i:(i,j)2e where (i,j)2e max m2s 2S,6=m I m k:(j,k)2e U( r(m) R (m) ˆ ) (1) = b m j, 8j, m, 2S,m6=, (2) Iij m r (m) apple c (m) ij, 8(i, j) 2E,m,2S,m6=, (3) c (m) ij apple C ij, 8(i, j) 2E, (4) I m ij d ij + m2s (i,j)2e k:(j,k)2e +' ( I m ij I m Ij m c (m) j,r(m) ˆ j:(j,)2e ' j(c (m) ij,c (m) ) ) apple L(m), 8m, 2S,m6=, (5) Iij m 2{, 1}, 8m, 2S,m6=, (i, j) 2E, (6) 8 >< b m j = >: apple r (m) apple r (m) 1, j = m 1, j =, otherwise apple R (m) ˆm, 8m, 2S, (7) apple R (m) ˆ, 8m, 2S, (8) Costraits (2) ad (6) eforce a sigle path for the uicast flow from surrogate m to, ad esures flow coservatio alog the path. Costrait (3) implies that the uicast flow from m to with is coceptual, hidde i the actual multicast flow m with rate c (m) ij, o each lik (i, j). Costrait (4) requires that the overall rate of actual flows from differet sources should ot exceed the capacity of each lik. Costrait (5) bouds the ed-to-ed delay alog the path from source surrogate m to receiver surrogate, which cosists of three parts: (i) the overall lik delay alog the rate r (m) d ij; (ii) the sum of potetial trascodig delay path, P (i,j)2e Im ij at itermediate surrogates j s alog the path, i.e., P (i,j)2e Pk:(j,k)2E Im ij I m ' j(c (m) ij,c (m) ), where a surrogate j is o the path if there exist eighborig liks (i, j) ad (j, k),. such that Iij m = 1 ad I m = 1, ad a trascodig delay occurs if the flow rate o (i, j), c (m) ij, is larger tha the flow rate o (j, k), c (m) ; (iii) the potetial trascodig delay at surrogate, ' P ( j:(j,)2e Im ), to trascode the received stream j c (m) j,r(m) ˆ to the maximum receivig rate allowed at mobile user ˆ, if eeded. Costraits (7) ad (8) restrict the ed-to-ed rate of virtual uicast flow from surrogate m to to be o larger tha the maximum sedig rate from mobile user ˆm ad the maximum receivig rate at mobile user ˆ. The solutios to the optimizatio problem, r (m), c (m) ij, I m ij, 8m, 2S, 6= m, (i, j) 2E, give us (i) the rate at which each mobile user ˆm should sed its stream to its surrogate m, which is the maximum of all coceptual uicast flow rates from m to the other surrogates, max 2S,6=m r (m) ; (ii) the delivery rate of flow m alog each lik (i, j) ad hece the flow routig topology amog the surrogates (c (m) ij =idicates flow m is ot to be routed over lik (i, j)); ad (iii) where the trascodig of each flow m should happe, i.e., a surrogate j where a egress flow rate c (m) is smaller tha the igress rate c (m) ij alog the same coceptual uicast path, should trascode flow m to the lower rate Distributed Heuristic The optimizatio problem (1) is o-covex with iteger variables.we desig a efficiet heuristic algorithm, as give i Alg. 1 ad Alg. 2, to decide flow routig, rate assigmet ad trascodig locatios i a fully distributed fashio. Algorithm 1 Flow Routig ad Rate Allocatio 1: Costruct shortest-path trees from each surrogate m, T (m) ; 2: if 9m, 2S,! (m) >L (m) the 3: No feasible solutio exists; retur ; 4: ed if 5: N ij := Number of dissemiatio trees o (i, j); 6: 8(a, b) 2 T (m),c (m) a,b := mi k2s,(i,j)2t (m) {R(m), C ij }; ˆk N ij 7: Search for better routig paths, followig Alg. 2; represets the overall latecy (icludig both lik ad ecessary trascodig latecies) for flow m from surrogate m to surrogate. A shortest-path tree is costructed from surrogate m to all the other surrogates, usig a distributed Bellmaford algorithm (Lie 1 i Alg. 1). If the overall lik latecy o the We first decide a basic, feasible dissemiatio topology for each flow m, o which the ed-to-ed delay costrait for each receiver, costrait (5), is satisfied. Though the optimizatio problem (1) does ot restrict the topologies ito trees, we seek to costruct a dissemiatio tree for each flow for ease of practical implemetatio. For cociseess,! (m), we kow that this pre-set ed-to-ed latecy boud is by o meas satisfiable, ad should be adjusted to a more reasoable value (Lies 2-4). We the decide a basic, ed-to-ed rate of flow m o this shortest path tree, from surrogate m to all the other surrogates: the capacity C ij of each lik (i, j) is evely divided by the (actual) flows geerated by differet surrogates, that pass through this lik; the ed-to-ed rate of each flow m is set to the rate allocated to this flow o the bottleeck lik its shortest-path tree spas (Lies 5-6). path from surrogates m to is larger tha L (m) Algorithm 2 Self-Evolvig Route/Rate Adjustmet at i Flow m 1: while 9(j, ) 2 T (m), c (m) j <R(m) do 2: if 9(i, k) 2 T (m), mi{c m ik, C k } >c (m) j the 3: :={} S {q :(, q) 2 T m }; 4: if 8p 2,! (m) p apple L (m) p the 5: T (m) := T (m) (j, )+(k, ); 6: ed if 7: ed if 8: ed while Based o the basic dissemiatio topology, each surrogate the carries out dyamic edge ad rate adjustmets by followig Alg. 2, to maximally utilize the available capacity to stream high-quality streams, without violatig the latecy costraits. For each flow 36

5 Mobile Device m m D = + + m Network Mobile Device B (m) Time Figure 3: A illustratio of the ed-to-ed delay for flow m. m, suppose surrogate j is the paret to surrogate o the curret dissemiatio tree of flow m. cotacts other eighborig surrogates i the flow, to discover if there is a better path from source surrogate m with higher capacity via aother paret k. It compares from j with the potetial receivig rate from k, mi(c (m) ik, C k ), where we suppose surrogate i is the paret of k i the curret tree, ad C k is the remaiig available badwidth o lik (k, ) (Lie 2 i Alg. 2). If the potetial receivig rate via k is larger, eeds to further evaluate the icreased latecy alog the ew path, due to chages of lik latecies ad potetial trascodig latecies at k ad. Oly if the latecy of the curret receivig rate c (m) j the ew path from m to, i.e.,! (m), is still withi L (m), ad the updated latecy to each of the descet surrogates from o the tree is still withi the respective delay boud, ca safely chage its paret from j to k (Lies 3-6). 4.3 Jitter Maskig I multi-party video coferecig, sychroizatio amog streams received at all users is crucial to users perceived quality of experiece. It is much desired that the video frames captured at all users at the same time, are played at all the recipiet user devices at the same time. We desig a effective bufferig mechaism, which collaborates with the routig algorithms, for this purpose. maitais a buffer B (m) for each stream m 2S/{} from each of the other surrogates. The buffer holds video packets of flow m, ready to be delivered to mobile device. vskypecof eforces a ed-to-ed delay of D, from whe a video frame is captured at oe mobile device, to the time it is sychroously played at all the other mobile devices. The value of D ca be set based o reasoable estimatio of the maximum delay betwee two mobile users i the system, ad should fall i the acceptable delay rage for real-time commuicatio. Let m idicate delay betwee mobile device ˆm ad its surrogate m, 8m 2S. For a frame i buffer B (m), which is produced at t at the source ˆm, it will be pushed out from the buffer o earlier tha t + L (m), where L (m) = D m, i order to guaratee playback of the frame at the mobile device ˆ at t + D (Fig. 3). If there were o jitter i the cloud, we could set the delay boud i optimizatio (1), used to fid the routig path from surrogate m to surrogate, to L (m) = L (m), ad rest assured that the buffer will ever starve. However, i a practical system, jitter may occur due to various reasos, e.g., variatio of trascodig delay at surrogates, iaccurate estimate of lik delay ad badwidth whe L (m) ruig our routig algorithm, etc. Hece, L (m) i the optimiza-, i order to absorb the iaccuracy ad jitter. A series of measuremet work [5] have show that jitter o a etwork path approximately follows a ormal distributio [11]. Let tio for route selectio should be set smaller tha L (m) be a radom variable, represetig the path delay from surrogate m to surrogate, such that J (m) N(µ, 2 ), where µ J (m) is the mea ad is the stadard deviatio. For a ormal distributio, we ca derive that 99.97% of the samples fall withi the rage of ( 1,µ +3.4 ). If we set L (m) to the mea µ i the path delay distributio while allowig L (m) = µ +3.4, we derive L (m) = L (m) 3.4. Usig this L (m) i solvig optimizatio (1), we ca make sure that 99.97% of the video packets, followig the path selected, ca be set out from surrogate by L (m), ad catch their playback deadlies at the mobile device ˆm. I vskycof, each surrogate dyamically estimates the delay variace alog the path from m to, based o iter-packet latecies of flow m it receives. It also observes the curret queueig delay i buffer B (m), ad adjusts L (m) used i path selectio accordig to L (m) = L (m) 3.4. That is, if there are less packets i the buffer caused by larger delay variace, it tues L (m) dow to be more striget o the latecy requiremet i the path selectio; otherwise, it tues L (m) up to explore paths with better badwidths. I this way, this bufferig mechaism at the surrogates collaborates with the routig algorithm, to deal with radomess i the system ad iaccuracy i the computatio, while maximally guarateeig sychroized playback of all streams at all the mobile devices. 5. PERFORMANCE EVALUATION We implemet a prototype of vskycof ad deploy it i Amazo Elastic Compute Cloud (EC2). s are provisioed from ap-southeast-1a (Sigapore), eu-west-1a (Irelad), us-west- 1b (Califoria) ad us-east-1a (Virgiia), for users located ear the respective regio. Each mobile user is emulated by a machie ear its assiged EC2 istace (withi 5 ms), where video frames are geerated at a costat rate aroud 768 kbps. We implemet a applicatio-layer packet cotroller to limit the uplik ad dowlik badwidths of each user withi the rage of [1.5, 2] Mbps the same as those o regular 3G cellular coectios. We apply the cocave fuctio log(x) as the utility fuctio i our routig computatio. Each surrogate dyamically measures the lik delays to its eighborig surrogates. The trascodig latecies are pre-evaluated o the VM istaces ad used i our routig computatio, for trascodig from 768kbps to 256kbps, from 768kbps to 128kbps, from 256kbps to 128kbps, respectively. At each user, the stream from oe of the other coferece participats is displayed i a large scree (correspodig to a maximal acceptable streamig rate of 768 kbps), ad streams from other participats are displayed usig smaller screes (correspodig to maximal acceptable streamig rates of 128 kbps or 256 kbps). A fixed 4 ms ed-to-ed delay (D i Sec. 4.3) is cofigured, ad the buffer for each flow at each surrogate is set to a size correspodig to 4ms stream playback. 5.1 Adaptive Flow Rates We test a video coferecig sessio amog 1 participats: 5 from Hog Kog, 1 from Europe, 2 from US West ad 2 from US East. As a potetial bottleeck for scalability, the surrogate of the sessio iitiator is resposible for sessio maiteace by exchagig messages with the other surrogates i the sessio. We therefore ivestigate the coferecig performace at the iitiator s surrogate: if its performace is satisfactory, the the performace at the other surrogates should be eve better. Fig. 4 plots the flow rates of streams from 3 out of the other 9 participats. Flow-b is the flow with a maximum streamig rate of 768kbps; flow-a ad flow-c correspod to a maximum streamig rate of 128kbps ad 256kbps respectively, with the user of the latter joiig the sessio at a later time. We ca see that each flow goes through a fast start stage, whe the basic stream dissem- 37

6 iatio topology is beig costructed (as itroduced i Sec. 4.2), ad the evolve towards their maximal acceptable rates. Fig. 5 presets the load i the jitter buffer for flow-b at the iitiator s surrogate, where we see that the bufferig level varies sigificatly whe flow-b takes a path with large delay jitters. Whe our routig algorithm redirects flow-b through a better path, a more stable bufferig level is achieved later o. Fig. 6 shows the latecy experieced by each flow, from the correspodig source surrogate to the iitiator s surrogate. We observe that latecies oly vary slightly wheever the routig paths are adjusted, ad ca well meet the ed-to-ed latecy required (4ms). Bitrates (kbps) Buffer Load (%) 1 5 Flow a Flow b Flow c Time (secods) Figure 4: Flow rates at the iitiator s surrogate. 1% 5% Time (secods) Figure 5: Load of flow-b s buffer at the iitiator s surrogate. Latecy (ms) Flow a Flow b Flow c Time (secods) Figure 6: Flow latecies at the iitiator s surrogate. 5.2 Compariso with a Uicast Solutio We ext evaluate the performace of vskycof agaist a uicast scheme typically applied i P2P video coferecig, where each flow is directly trasmitted from the source to the destiatio via the etwork. We establish a 3-user video coferecig sessio, ad emulate a 5-miute log coferecig sessio with oe user comig from each of the regios, Hog Kog, Europe ad west US. Fig. 7 shows the perceived ed-to-ed latecies of the two flows received at the Hog Kog user, where eu stads for Europe ad usw stads for west US. We ca see that the ed-to-ed latecy achieved with vskycof is geerally smaller, ad much more stable tha that achieved by the uicast solutio, verifyig the smooth stream playback experieced by vskycof users. This validates that our cloud-assisted desig is suitable to achieve high-quality video coferecig amog multiple mobile participats. 6. CONCLUSION AND FUTURE WORK This paper presets vskycof, a cloud-assisted mobile video coferecig solutio, desiged to fudametally improve the quality Latecy (ms) 1 5 uicast eu uicast usw vskycof eu vskycof usw Time (secods) Figure 7: Ed-to-ed delay at the Hog Kog user. ad scale of multi-party mobile video coferecig. We employ a virtual machie i a cloud ifrastructure as the proxy for each mobile user, to sed ad to receive coferecig streams, ad to trascode the streams ito proper formats/rates. We desig a fully decetralized, efficiet algorithm to decide the best paths of stream dissemiatio ad the most suitable surrogates for video trascodig alog the paths, ad tailor a bufferig mechaism o each surrogate to cooperate with efficiet stream distributio. We have implemeted the vskycof prototype o Amazo EC2 ad verified its excellet performace. I our ogoig work, we are implemetig vskycof o real mobile devices ad evaluatig its performace uder more dyamic settigs. 7. ACKNOWLEDGMENTS The research was supported i part by a grat from Hog Kog RGC uder the cotract HKU E. 8. REFERENCES [1] Survey o mobile video coferecig apps, [2]. Che, M. Che, B. Li, Y. Zhao, Y. Wu, ad J. Li. Celerity: a low-delay multi-party coferecig solutio. I Proceedigs of the 19th ACM iteratioal coferece o Multimedia, New York, NY, USA, 211. [3] Y. Feg, B. Li, ad B. Li. Airlift: Video coferecig as a cloud service usig iter-dataceter etworks bibtex. I Proceedigs of IEEE ICNP, 212. [4] Z. Huag, C. Mei, L. E. Li, ad T. Woo. Cloudstream: Deliverig high-quality streamig videos through a cloud-based svc proxy. I Proceedigs of INFOCOM, 211. [5] M. J. Karam ad F. A. Tobagi. Aalysis of delay ad delay jitter of voice traffic i the iteret. Computer Networks, 4(6): , Dec. 22. [6] Z. Li, B. Li, D. Jiag, ad L. C. Lau. O achievig optimal throughput with etwork codig. I Proceedigs of IEEE INFOCOM, 25. [7] C. Liag, M. Zhao, ad Y. Liu. Optimal badwidth sharig i multiswarm multiparty p2p video-coferecig systems. IEEE/ACM Tras. Netw., 19(6): , 211. [8] J. L. Ozer. Video Compressio for Flash, Apple Devices ad HTML5. Doceo Publishig, USA, 211. [9] M. Poec, S. Segupta, M. Che, J. Li, ad P. A. Chou. Optimizig multi-rate peer-to-peer video coferecig applicatios. IEEE Trasactios o Multimedia, 211. [1] Y. Wu, C. Wu, B. Li, ad F. C. Lau. vskycof: Cloud-assisted Multi-party Mobile Video Coferecig. Techical report, [11] E. R. Ziegel. Probability ad Statistics for Egieerig ad the Scieces (8th Ed.), by Jay L. Devore. America Statistical Associatio, eight editio,