On the Interactions between Non-Cooperative P2P Overlay and Traffic Engineering Behaviors

Transcription

1 On the Interctions between Non-Cooertive P2P Overly nd Trffic Engineering Behviors Chojiong Wng, Ning Wng, Michel Howrth University of Surrey Guildford, United Kingdom {C.Wng, N.Wng, George Pvlou University College London London, United Kingdom Abstrct Emerging Peer-to-Peer (P2P) technologies hve enbled vrious tyes of content to be efficiently distributed over the Internet. Most P2P systems dot selfish eer selection schemes in the liction lyer tht in some sense otimize the user qulity of exerience. On the network side, trffic engineering (TE) is deloyed by ISPs in order to chieve overll efficient network resource utiliztion. These TE oertions re tyiclly erformed without distinguishing between P2P flows nd other tyes of trffic. Due to inconsistent or even conflicting objectives from the ersectives of P2P overly nd networklevel TE, the interctions between the two nd their imct on the erformnce for ech is likely to be non-otiml, nd lso hs not yet been investigted in detil. In this er we study such non-cooertive interctions by modeling best-rely dynmics, in which the P2P overly nd network-level TE otimize their own strtegies bsed on the decision of the other lyer in the revious round. According to our simultions results bsed on dt from the ABILENE network, P2P overlys exhibit strong resilience to dverse TE oertions in mintining end-to-end erformnce t the liction lyer. In ddition, we show tht network-level TE my suffer from erformnce deteriortion cused by greedy eer (re-)selection behvior in recting to revious TE djustments. I. INTRODUCTION Tody, P2P flows ccount for some 50%-70% of the overll Internet trffic, ccording to recent trffic mesurements [1, 2]. Under such circumstnces, network ccity for other tyes of services, such s conventionl webbsed lictions, my be imcted due to resource cometition with this lrge volume of P2P trffic. In the literture, trffic engineering (TE) techniques hve been roosed for ISPs to otimize customer trffic in order to imrove overll network erformnce, for exmle by erforming lod blncing nd network cost reduction. It should be noted tht, in generl, TE solutions do not distinguish between P2P flows nd conventionl Internet trffic, which mens tht trffic otimiztion is erformed in n ggregte fshion, regrdless of secific tyes of flows. In P2P overly networks, the current imlementtion of eer selection rdigms re often bsed on liction-lyer otimiztion for enhncing the qulity of exerience by end users. For instnce, rel-time multimedi P2P systems usully select rtner eers tht re ssocited with low dely in order to chieve fst lybck t the user side. On the other hnd, the objective of TE is to imrove the overll erformnce t the network side, insted of focusing on individul users. As such, there is n obvious mislignment between the TE objectives nd the selfish P2P eer selection in the liction lyer. As for the two utonomous entities the P2P overly nd the network-level TE the decisions tht re mde by ech one of them my influence the erformnce of the other. Such interctions my dversely imct the relevnt erformnce on both sides due to conflicting behvior. For instnce, TE my djust the underlying routing decisions in order to re-otimize network erformnce, but such chnge my lso shift some P2P trffic to lterntive ths with subotiml user-erceived QoS erformnce (e.g. higher end-toend dely due to longer ths). As result, the P2P overly my rect to such dynmics by re-selecting rtners in ech P2P session in order to regin the originl erformnce t the liction lyer. Such behvior will once gin chnge the overll trffic condition so tht the underlying TE mechnisms need to rect ccordingly once gin. This djustment of network configurtions my further trigger re-selection of eers in the P2P overly. In this er we investigte the interction between selfish eer selections nd otimized routing configurtions in non-cooertive environments. In the literture, number of ers [3, 4, 5, 6] hve investigted the interction between TE nd overly network oertions. We cn clssify these works into two ctegories. The first ctegory focuses on the interctions between networklyer routing configurtions decided by TE nd logicl overly routing on to [3, 4]. In this scenrio, TE nd the overly resectively djust their own routing strtegies in turn, bsed on ech other s decisions. Comred with this tye of interction, the key difference from our work is s follows: we focus on the P2P overly side which only considers how to select the best rtner eers (i.e. the other endoint of individul P2P connection sessions), rther thn chnging the routing configurtion in the overly. The other ctegory [5, 6] focuses on CDN (Content Distribution Network) like rdigms, nd considers the interction between networklyer routing decisions mde by TE nd liction-lyer content server selections. Our work differs from this ctegory in the following three fetures. Firstly, in P2P overly networks, eers, s both content roducers nd consumers, hve highly dynmic join/derture tterns, while in the CDNs of [5, 6] content servers re stticlly rovisioned in the network for roviding content delivery services. Secondly, we consider symmetric content exchnge tterns: in P2P overlys eer

2 not only requests dt from, but lso rovides content to other eers; this differs from the revious studies in which secific set of clients only downlod dt from number of dedicted content servers. Finlly, in P2P overlys ech eer needs to simultneously fetch chunks of content from set of rtners, while in conventionl CDNs client tyiclly requests content from one secific server t time. Figure 1: Dynmic interction between TE nd P2P overly In this er we model TE nd P2P overly s two rtionl lyers resectively who ly the best-rely dynmics [4]: one lyer chooses the best resonse bsed on the other lyer s decisions in the revious round. As shown in Figure 1, TE ims to otimize the overll network erformnce (e.g. lod blncing) through djusting routing decisions for customer trffic (including both P2P nd non-p2p bckground flows) in the network lyer. The outcome of th selection chnges by TE for the P2P trffic is then tken s inut by the P2P overly to re-select rtner eers in order to regin the originl liction-level erformnce (e.g. minimize end-to-end dely between individul eering rtners) in cse of dverse imcts from TE. Such eer reselection further influences the overll trffic distribution in the network, requiring further TE oertions, nd so on. Note tht TE nd the P2P overly my otimize their own objectives t different timescles, but here we follow the ssumtion mde in [5] tht ech lyer runs its otimiztion until the other hs finished its oertions in ech round. With such interctions, both TE nd P2P overly djust their own decisions in turn ccording to ech other s revious behviorl chnges. Bsed on this model, we investigte how well TE nd P2P overly my rect to ech other in such non-cooertive environment. As fr s TE is concerned, tody s solutions cn be clssified into IP-bsed TE nd Multi- Protocol Lbel Switching (MPLS-bsed) TE. The ltter is more flexible thn the former, in the sense tht it llows exlicit routing nd rbitrry slitting of trffic cross multile ctive lbel switched ths (LSPs), even t short time-scles. In this er we secificlly focus on the interction between MPLS-bsed TE nd P2P overlys, since MPLS-bsed TE is idel for online trffic djustment tht is gile to short timescle trffic dynmics. In our study, we im to nswer the following questions: 1) Is there n equilibrium oint in this interction between TE nd P2P overly behviors? 2) If the nswer is yes, then does this equilibrium oint converge to n imroved oint? 3) Wht is the otentil imct on the erformnce of the P2P overly nd the network erformnce under such interctions? We believe tht good understnding of such interctions will offer significnt insight into the future develoment of intelligent Internet P2P trffic mngement rdigms in dynmic environments. II. TRAFFIC ENGINEERING & PEER SELECTION In this section we first describe the modeling of the interctions between MPLS-bsed TE nd selfish eer selection in P2P overlys. After this, best-rely dynmics model between the two lyers is resented for nlyzing behviorl interctions between them. Let s first consider hysicl Point-of-Presence (PoP) network toology tht is modeled s unidirectionl grh G = (N, A), where N is set of PoP nodes nd A is the set of inter- PoP links. Ech hysicl link A hs bndwidth ccity C. The tule <i, j> is defined s PoP node ir where i, j N refer to source nd destintion PoP node resectively. In our model, ech eer is ssocited with one of the PoP nodes in the PoP-level network toology. The routing of both P2P trffic nd conventionl bckground trffic is determined by TE, nd the two trffic tyes re not distinguished. Let P reresent set of exlicit LSPs between PoP nodes i nd j, with ech LSP consisting of one or multile inter-pop links. In common rctice of ISP network design, bndwidth resources within single PoP re usully highly over-rovisioned, so we only focus on bndwidth resources on inter-pop links in A. This mens if multile eering neighbors re clustered within the sme PoP, then the ssocited bndwidth consumed by their locl eering connections is ignored. According to common MPLS-bsed TE roches, multile LSPs re estblished between ech PoP node ir in order to llow dtive slitting of the overll trffic demnd cross them for chieving dynmic lod blncing. Let t 2 nd n2 t denote resectively the overll P2P trffic demnd nd the overll non-p2p bckground trffic demnd from PoP node i to j. Let 2 n2 t be the overll trffic demnd t = t + t, nd x (0 x 1) be the trffic slitting rtio on ech secific LSP P. A. Trffic Engineering TE oertions re normlly lied by ISPs in order to otimize the overll network erformnce, such s lod blncing nd network cost reduction. In our model, we consider the objective of TE to be minimizing the mximum link utiliztion (MLU), since this hs been widely used s TE erformnce metric in the literture. Once gin, we emhsize tht TE ims to otimize the overll network erformnce rther thn ny secific tye of trffic, nd in our model, TE does not differentite between P2P trffic nd non-p2p bckground trffic. As reviously mentioned, m (m>1) disjoint LSPs re reestblished between ech PoP node ir in our nlysis. We introduce binry ming coefficient Y to indicte the

3 reltionshi between LSP nd hysicl link : Y equls 1 if hysicl link is on hysicl LSP P, nd 0 otherwise. The overll trffic lod T = x * t * Y, ( x = 1) i N j N\{ i} P P on the hysicl link A is the sum of ll demnds of flow over this link, including both P2P trffic nd non-p2p trffic. With demnd mtrix (t, i, j N), the objective of TE is to comute n otimized vlue x (slitting rtio) cross LSPs between ech source-destintion PoP node irs in order to minimize the overll MLU cross the network, i.e.: T min mx( ) (1) A C t, z = j s.t. x * t * Y x * t * Y = t, z = i d : ( ) = z s : ( ) = z 0, otherwise where z, i, j N, where s() nd d() re source node nd destintion node of link resectively. An dtive MPLS-bsed TE is considered, which cn be oerted t short vrible time-scle (e.g. t the scle of minutes). To llow for fst rections to chnging trffic conditions (e.g. due to frequent eer reselections in P2P overly), we consider n online heuristic solutions without involving globl otimiztions ech time (i.e. only locl djustments re lied). Similr to [6], we consider the generic TE strtegy s follows: set of hysicl links with high link lod is first identified nd TE tries to itertively shift some trffic demnd wy from them in order to better blnce the overll trffic distribution. More secificlly, TE identifies the to k inter-pop links with the highest utiliztion cross the entire network, nd then some trffic currently trversing those links needs to be shifted wy from them. To chieve this, TE needs to re-configure the trffic slitting rtio for m LSPs between some node irs <i, j> tht involve those highlyloded links. The shifting ction is chosen so tht it does not introduce ny new hot sots with higher link lod thn the originl lods before the djustment. This trffic shifting through re-otimizing slitting rtios t individul source PoPs cn be recursively erformed until no further imrovement is chieved. B. Selfish Peer Selection in the P2P Overly The P2P overly ims to otimize the erformnce exerienced by end users, for exmle by reducing the end-toend dely between individul eers. This is tyiclly done in the liction lyer by loclized rtner eer selection In the modeling of the P2P overly behvior, ech eer is ssocited with one of the PoP nodes in the network toology. We consider multile simultneous P2P sessions running over the network, with ech session contining distinct set of ctive eers shring the sme content. If one end-user rticites in multile sessions, it is treted s n indeendent eer in ech of them. More secificlly, let V denote set of ctive eers hysiclly ttched to network G. Ech client eer in P2P session t needs to connect to set of rtner eers from ll vilble eers in the session (denoted by V(t)), nd downlod content from them t certin trnsmission rtes. In this cse the ctul rtner set for secific client eer u (denoted by V u (t)) is effectively subset of ll the vilble eers in session t, i.e., V u (t) V(t). In ddition, let D be the dely of hysicl link A, nd let the dely between PoP node ir be the sum of the dely ssocited with ech link constituting the LSP between tht node ir. While intr-pop dely is ignored, the forml objective in eer selection is to minimize the dely between ech single client eer u nd ech of its selected rtner eers i.e.: min ( D* Yu, v) (2) < uv, >, v Vu ( t) uv A where Y, is binry ming coefficient, equl to 1 if link constitutes the LSP from PoP node u to v, nd is equl to 0 otherwise. With such selfish eer selection rdigm with ltencylocliztion, the P2P overly my dynmiclly redjust the rtnershi connections for every client eer bsed on own mesurements. As we mentioned reviously, both non-p2p trffic nd P2P trffic re shifted by TE without distinction so s to imrove the overll network erformnce. For the P2P trffic, the end-to-end dely from some current rtner eers to the client eer my become higher if the trffic is shifted from shorter dely LSP to longer one. In this cse, in the following round, the P2P overly hs the oortunity to reselect some new rtners elsewhere with lower dely. Such chnge t the P2P side then chnges the trffic condition inut for TE, which my in turn mkes further djustment ctions. C. TE nd P2P Overly Interction Anlysis We consider such interction s best-rely dynmics where ech of the two rtionl lyers decides its own best strtegy in resonse to the chnge of behvior of the other lyer in the revious round. The MPLS-bsed TE nd P2P overly tke turns to otimize their own objectives resectively in this interction. In our nlysis, the strtegy sce tht is lied by MPLS-bsed TE cn be described s set of fesible trffic P slitting rtios cross m distinct LSPs { x,..., m x } between ech PoP node ir <i, j>. This cn be exressed s: P S...{,..., m TE =< x x }... > (3) Trffic slitting in MPLS-TE is erformed on er-flow bsis insted of er-cket [7], nd therefore the P2P flow between ech eering rtner lwys follows one single th t ny time. On the other hnd, the strtegy sce of P2P overly is set of rtner eers V u (t) of every single client eer u tht re selected from ll vilble eers V(t) in ech session t. By selecting the best rtner eers, the end-to-end dely mong eers cn be mintined s minimum for ech client eer in the session. SP2 P=<... V () u t... > (4) Bsed on the bove secifictions, we now consider the cse where TE otimizes the th selection decisions for both non-p2p trffic nd P2P trffic without distinction. Since the

4 P2P trffic ths re chnged by the TE oertion, the dely erformnce from rtner eer to client eer my chnge. As described bove, if some P2P trffic is shifted from one LSP to nother longer th, the corresonding eers my exerience higher end-to-end dely fter such chnge. In order to ttemt to mintin the originl qulity of service, the P2P overly my then rectively select lterntive rtner eers within individul sessions, bsed for exmle on mesured dely, in resonse to the chnged MPLS ths by TE. Due to such reshuffling in eer connections in the P2P overly following the revious TE oertion, the overll trffic condition within the network chnges gin. It should be noted tht, given the fct tht P2P trffic domintes the overll Internet trffic tody, behviorl chnges in the P2P overly my hve significnt imct on the overll network trffic tterns. As such, MPLS-bsed TE my need to further redjust trffic slitting rtios in order to mintin its own objective. Generlly, MPLS-bsed TE nd the P2P overly tke turns to otimize their own oertionl erformnce, djusting to the revious decision of the other lyer. This cn be modeled s: Pm { x,..., x } = rg min TE( Vu ( t) ) ( k + 1) ( k ) (5) Pm V ( t) = rg min P2 P( { x,..., x }) u ( k+ 1) ( k ) Using our model of TE nd P2P overly behvior, we investigte whether best-rely dynmics converge to n equilibrium oint in this interction between non-cooertive behviors. If there is converging equilibrium oint, we my further investigte whether it is globlly otiml oint such s Preto oint [5], or bised one in fvor of either side. In ddition to convergence, we lso study the imct on the relevnt erformnce of the P2P overly nd TE resectively. Through this nlysis, cler icture cn be drwn on whether P2P overly cn synergisticlly interct with TE in current network environments, nd useful guidnce cn be further derived on how to mutully imrove the erformnce of both P2P overly nd TE rdigms in order to otentilly chieve win-win sitution between the two rtionl lyers. III. PERFORMANCE ANALYSIS In this Section we consider the erformnce of the TE nd P2P overly interctions. We first describe our simultion environment, including the network toology nd the setu of the P2P overly. The simultion scenrios nd rmeters re then resented. Following this, we resent results for the erformnce metrics ssocited with the TE nd P2P overly. A. Simultion setu We use the rel ABILENE network toology [8] t the Point-of-resence (PoP) level. The ABILENE network consists of 11 nodes nd 28 unidirectionl inter-pop links. Ech link hs its ctul link ccity nd IGP link weight configurtion. According to [9], in the ABILENE network the IGP link weight setting is bsed on end-to-end ltency, nd hence customer trffic is effectively routed on the lowest dely ths. In ddition, the ABILENE trffic trces tht re mesured through NetFlow re used (with scling) s bckground trffic in our simultion. The P2P trffic used in our exeriments is syntheticlly generted bsed on the mesured ttern of tody s oulr rel-time multimedi bsed P2P lictions [10]. We consider 20 concurrent P2P chnnel sessions, with ech chnnel ttrcting u to 1000 eers. Hence ltogether we consider u to 20,000 eers tht re distributed cross the 11 PoP nodes in the ABILENE network. The overll distribution of these eers in ech PoP node is determined ccording to the ctul oultion of ech city (PoP), where lrger PoP nodes hve more eers ssigned. The chnnel session selected by ech eer is rndomly determined. Without loss of generlity, there re both oulr chnnels nd unoulr chnnels on the P2P overly side. In ddition, we follow the observtion tht ech client eer hs on verge 40 eering connections in order to stisfy the overll downloding rte requirement for stble lybck (1Mbs, [10]). For ech requesting eer, there is one to eer rtner tht rovides on verge three times s much content s the other (uxiliry) ones. B. Simultion Scenrios To mke the nlysis more comrehensive, we use three scenrios to nlyze the interction between MPLS-bsed TE nd P2P overly. Following [4, 5], we set the overll P2P trffic demnd s low, medium or high roortion of the overll network trffic volume, i.e. the P2P trffic ccounts for 40% (low), 60% (medium), or 80% (high) of overll network trffic. Such configurtions re resonble, s it hs been observed tht the ctul roortion of P2P trffic in the Internet vries significntly nd it my ek t 80%. C. Performnce Anlysis Figure 2: Rtio of dely of the longest th to the shortest th As fr s trffic slitting in MPLS-bsed TE is concerned, we first show in Figure 2 the end-to-end dely rtio cross rllel LSPs, i.e. the rtio of the longest dely LSP to the shortest dely LSP between ech ir of PoP nodes in the ABILENE network. This rtio effectively indictes the ctul chnge of dely exerienced by the eers whose flows re shifted by TE trffic slitting djustments from the longest dely LSP to the shortest dely LSP. From Figure 2 we cn see tht the mximum dely rtio is 13:1, minimum rtio is 1:1, nd the verge is round 2.6:1. Such difference between the ths my esily result in selfish rtner reselections by some

5 ffected eers whose flows re shifted from the shorter th to the longer one. bckground trffic my become less stble, with some oscilltion observed (Figure 4). The reson is tht lrge number of eer reselections erformed by the P2P overly cuse TE to unilterlly djust the trffic slitting rtio cross multile LSPs. Since TE otimizes P2P nd non-p2p bckground trffic without distinction, the non-p2p trffic is imcted by the TE otimiztion in resonse to P2P reselection behvior. Figure 3: Reltive chnge of MLU for overll trffic Figure 3 indictes the ttern of the overll MLU erformnce chnge reltive to the initil stte (round 1) on er round bsis (we consider 100 rounds in our exeriments), i.e. MLU () t,(1 < t 100) MLU (1) We cn clerly see tht different roortions of P2P trffic hve yielded distinct erformnce curves. Secificlly, the low scenrio converges to n equilibrium oint which hs 8% decrese comred with the MLU vlue of in the initil stte (100%). Similrly, in the medium scenrio we cn lso observe the convergence towrds n equilibrium oint, but interestingly, the finl converged erformnce hs 5% increse comred with the initil stte. Bsed on the bove results, we cn see tht even if secific equilibrium exists, it is not lwys the cse tht the overll TE erformnce will converge to n imroved erformnce. The reson is tht, fter the djustment of TE, the P2P overly my selfishly reselect new rtner eers which my led to significntly worse network erformnce comred with the sitution before the TE oertion, nd the next round of TE oertion might not be ble to chieve further better erformnce thn the revious round. By investigting the high scenrio in Figure 3, we cn clerly see some oscilltion tterns on the MLU erformnce s the number of rounds increses, nd more imortntly there is no secific equilibrium nd indeed the MLU erformnce becomes worse with time. As we mentioned bove, P2P overly selfishly re-selects the eering rtners if the originl ones exerience higher dely following the djustment of TE. It cn be inferred tht such selfish eer reselection behvior my hve some significnt (negtive) imct on the TE erformnce in the non-cooertive environment, esecilly when P2P flows dominte network trffic. In ddition to the overll MLU erformnce, we lso show how the interctions between TE nd P2P overly imct the erformnce of bckground non-p2p trffic. Figure 4 indictes the chnge of non-p2p trffic utiliztion comred to the initil stte. We cn see tht in both low nd medium scenrios, the bckground trffic condition is not significntly imcted by the interction. However, if P2P flows substntilly dominte the overll trffic (high scenrio), the utiliztion of non-p2p Figure 4: Reltive chnge of MLU for non-p2p trffic Figure 5: Reltive chnge of dely We now consider the P2P network dely erformnce. For the P2P overly, we first show in Figure 5 the chnge of endto-end dely erformnce between individul eers uon the comletion of eer reselections fter ech round. We only consider the eer rtners whose connections hve been ctully ffected by the TE oertion. We recll tht the verge dely rtio, i.e. the rtio of the longest LSP dely to the shortest LSP dely, between ech PoP node ir is 2.6. In the Figure we cn see tht for ll the three scenrios the end-to-end dely is not significntly negtively imcted by the TE djustment for most of the eriod, nd sometimes such erformnce cn be even imroved comred with the initil stte. This is due to the P2P overly s greedy rections to the chnged ths lterntive rtners cn be often identified without significnt extr dely s comred to the initil stte. In Figure 5, the low nd medium scenrios finlly converge to equilibrium oints tht hve 10% nd 7% increse in dely resectively comred with the initil stte. The medium scenrio hs regulr oscilltion ttern in the lst 40 rounds, oscillting between 5% increse nd 20% decrese comred to the initil stte. This observtion indictes tht the

6 P2P overly hs generlly high resilience cbility in mintining end-to-end erformnce ssurnce ginst the chnge of underlying th selections by TE oertions, thnks to the selfish eer selection behviors t the liction level. Figure 6: Reltive chnge of rtner eer churn rtio Finlly we investigte how the P2P connection stbility erformnce is ffected by the TE. We define the eer churn rtio metric to nlyze the relevnt erformnce t the P2P overly side. As mentioned before, due to the exeriences of higher dely following the djustment of TE, set of ffected eers my need to re-select some of their rtners to relce the originl ones whose end-to-end dely erformnce becomes higher. We define requesting eer tht hs ny ffected rtners (s result of TE oertion) to be n in-churn eer. This metric for the whole system stbility cn be defined s: No. of requesting eers tht need to find new rtner eers Totl No. of requesting eers The reson for evluting such metric is tht the trnsient time eriod during reselections my led to erceivble service disrution for rel-time P2P services, nd this is in rticulr the cse if lrge number of existing rtners need to be relced for the requesting eer. According to Figure 6, we cn see tht the high scenrio hs the lowest eer churn rtio mong ll the three scenrios. The low scenrio hs lower churn rtio thn first ste nd cn converge to n equilibrium oint (60% of the initil stte). We lso find tht medium scenrio hs significnt oscilltions fter 56 th round, but the eer churn rtio is mximum of 40%. D. Generl Observtions Bsed on these simultion results we now discuss the issues we rised in Section I. First of ll, we cn see tht it is not lwys the cse tht n equilibrium oint cn be reched between the two rtionl lyers. Even if such equilibrium oint exists, it is not lwys Preto oint. According to the MLU erformnce tterns, we find tht in the noncooertive environment, TE does not seem to be ble to drive the overll network erformnce to n imroved sitution when intercting with selfish P2P overlys. This is rticulrly the cse when P2P flows dominte the overll network trffic. On the other hnd, the P2P overly exhibits high resilience cbility nd is ble to void end-to-end dely degrdtion following TE djustments. Nevertheless, high roortion of rtner re-selection my led to erceivble service disrution for rel-time P2P services. IV. CONCLUSIONS In this er we use best-rely dynmics to model the noncooertive interctions between the P2P overly nd network-level TE behviors, ech of which hs distinct otimiztion objectives the P2P overly ims to imrove the exerienced qulity in terms of dely for individul eers, while TE ims to otimize the overll network resource utiliztion. The decision mde by ech hs significnt imct on the erformnce of the other when they otimize otentilly conflicting objectives simultneously. Through the nlysis of such interctions bsed on our simultions, we show tht in the non-cooertive network environment TE does not seem to be efficient in otimizing network erformnce when intercting with selfish P2P overly. On the other hnd, the P2P overly is generlly resilient ginst otentilly dverse TE oertions in terms of end-to-end dely erformnce. However, with the P2P-bsed rel-time streming lictions being more nd more oulr, high roortion of eer rtner re-selection in rection to TE oertions my introduce service disrutions, nd this henomenon needs to be further investigted. We intend to investigte relevnt interctions in more detil in our future work. V. ACKNOWLEDGEMENT This work ws rtilly funded by the EU FP7 COMET Project (248784). REFERENCES [1] V. Aggrwl et l., Cn ISPs nd P2P Users Cooerte for Imroved Performnce?, ACM CCR, Vol. 37, No. 3, , July, 2007 [2] The IETF ALTO WG: htt:// [3] L. Qiu et l., On Selfish Routing in Internet-Like Environments Proc. ACM SIGCOMM 2003 [4] Y. Liu et l., On the Interction Between Overly Routing nd Trffic Engineering, Proc. IEEE INFOCOM 2005 [5] W. Jing et l., Cooertive Content Distribution nd Trffic Engineering in n ISP Network, Proc. ACM SIGMETRICS 2009 [6] D. DiPlntino et l., Trffic Engineering vs. Content Distribution: A Gme Theoretic Persective, Proc. IEEE INFOCOM 2009 [7] S. Kndul et l., Wlking the Tightroe Resonsive Yet Stble Trffic Engineering, Proc. ACM SIGCOMM 2005 [8] ABILENE network, htt:// [9] S. Uhlig et l., Providing Public Intrdomin Trffic Mtrices to the Reserch Community, ACM CCR, Vol. 36, No. 1, , Jn [10] X. Hei et l., A mesurement study of lrge-scle P2P IPTV system, IEEE Trns. on Multimedi, Vol. 9, No. 8, , Dec. 2007