How To Plan A Network Wide Load Balancing Route For A Network Wde Network (Network)

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1 Network-Wde Load Balancng Routng Wth Performance Guarantees Kartk Gopalan Tz-cker Chueh Yow-Jan Ln Florda State Unversty Stony Brook Unversty Telcorda Research Abstract As wde-area network connectvty becomes commodtzed, network servce provders are offerng premum servces that generate hgher revenues by supportng performance senstve traffc (such as voce, multmeda, and onlne tradng). An emergng example s a vrtual prvate network path wth qualty of servce (QoS) guarantees, or QVPN. The man techncal challenge n offerng the QVPN servce s how to allocate a physcal route for each QVPN so as to maxmze the total number of QVPNs that a gven physcal network nfrastructure can support smultaneously. We make the case that the key to addressng ths challenge s to mantan network-wde load balance when selectng QVPN routes. By ensurng that dfferent parts of the network are evenly loaded, no sngle crtcal lnk wll tend to become a bottleneck resource. Ths paper descrbes a Lnk Crtcalty Based Routng (LCBR) algorthm, whch acheves hgh network resource utlzaton effcency whle supportng QVPNs wth end-to-end delay and bandwdth guarantees. Usng a smple yet effectve metrc that accurately quantfes network-wde load balance, LCBR sgnfcantly mproves the total number of supported QVPNs when compared to exstng traffc engneerng approaches. I. INTRODUCTION As Internet connectvty becomes a commodty, large enterprses ncreasngly want hgh levels of performance and relablty guarantees for ther performance senstve traffc (such as voce, multmeda, onlne fnancal tradng or electronc commerce). Carrers and network servce provders are respondng to such demands wth QoS-guaranteed VPN (or QVPN) servce. Technologes such as Mult-Protocol Label Swtchng (MPLS) can meet the QoS requrements of QVPNs by mappng each QVPN nto a Label Swtched Path (LSP). However, a major challenge that carrers face today s how to map each QVPN nto a physcal network path such that as many QVPNs as possble can be supported on ts network nfrastructure, thus maxmzng the revenue base for the carrer. We make the case that key to ths problem s to mantan network-wde load balance durng the route selecton process. Wthout network-wde load balance, t s possble that crtcal lnks become saturated much earler than others, renderng large number of routes unusable. Whle a number of QoS routng [1] [8] and traffc engneerng approaches [9] [14] exst, none of them have attempted to explctly quantfy the noton of network-wde load balance under QoS constrants. Wthout a quanttatve metrc, t becomes dffcult, f not mpossble, to evaluate varous load balancng routng algorthms. In ths paper, we propose the Lnk Crtcalty Based Routng (LCBR) algorthm that explctly mantans network-wde load balance n the route selecton process. LCBR s the frst algorthm to explctly quantfy the noton of network-wde load balance and to use t systematcally n the selecton of routes for QVPNs. LCBR ncorporates a smple and yet effectve measure of lnk crtcalty that helps to capture the mportance of a lnk wth respect to ts current resdual capacty and expected future load. Lnk crtcalty s then used as the bass to derve a network-wde load balancng metrc that characterzes the degree of load balance across the network and encourages the selecton of less crtcal lnks n the routng process. LCBR routes ncomng QVPNs n an onlne fashon. In contrast to offlne schemes, onlne algorthms do not possess apror knowledge of future QVPN arrvals and employ ntellgent heurstcs to adapt to future resource demands. We develop upon an earler verson of LCBR algorthm that was frst brefly ntroduced n [15]. Ths paper s addtonal contrbutons nclude the detaled development and performance evaluaton of a comprehensve set of LCBR algorthms that provde bandwdth guarantees alone, bandwdth-delay guarantees, and relablty. We consder the wde-area physcal network managed by a carrer that has complete admnstratve control of resources n the network. Each customer s QVPN spans from one pont of presence of the carrer s network to another and, once actvated, lasts for several days, weeks, or months. A network management system montors the traffc matrx and per-lnk traffc load n real-tme and uses ths feedback to route QVPNs. II. QUANTIFYING NETWORK-WIDE LOAD BALANCE Consder the smple example n Fgure 1. We need to select a route for a QVPN F 1 between nodes S 1 and D 1. There are two canddate routes: (S 1, E, B, C, D, D 1 ) and (S 1, E, F, G, D, D 1 ). Whch of these two routes s better from perspectve of long-term network resource usage effcency? Suppose t s lkely that future QVPN requests may arrve between (S 2, D 2 ) and (S 3, D 3 ) as well, but we do not know the exact QoS requrements of these QVPNs. Then the better route to select for F 1 would be (S 1, E, F, G, D, D 1 ) because t leaves the resources along the lnks (B, C) and (C, D) free for future QVPN requests between (S 2, D 2 ) and (S 3, D 3 ). Hence, the routng algorthm should, as far as possble, avod overloadng the lnks whch are crtcal to a large number of source-destnaton pars, so that no sngle lnk becomes a bottleneck for the whole network. The fundamental challenge here s the followng: Wthout precse knowledge of future QVPN request pattern, how exactly can we determne the mportance of a network lnk and ts mpact on network-wde load balance? In ths secton, we answer ths queston by quantfyng the notons of lnk crtcalty,

2 S3 S2 S1 Fg. 1. A E Route 1 B F C D3 G Route 2 An example of load balancng route selecton problem. expected load and network-wde load balance. A. Lnk Crtcalty and Expected Load The mportance of a lnk n LCBR s measured by the future expected load on each lnk,.e. the expected amount of traffc between dfferent source-destnaton pars to be carred over each lnk. A lnk that carres hgher amount of traffc between dfferent source-destnaton nodes s consdered more crtcal than one that carres less. More formally, assume that a total of x network routes are possble between a source-destnaton par (s, d) and y of these routes pass through a lnk l. Then the crtcalty φ l (s, d) of the lnk l wth respect to sourcedestnaton par (s, d) s defned as the fracton y/x. The total expected load φ l on lnk l s defned as the fractonal sum of expected bandwdth demands on the lnk from all possble source-destnaton pars n the network. Snce φ l represents a future expected load on the lnk, we need to begn wth an ntal estmate of φ l and then refne t ncrementally at run-tme as successve QVPNs are admtted. The ntal estmate of φ l s computed usng a matrx of expected bandwdth demands B(s, d) between each source-destnaton par (s, d) n the network. B(s, d) can be obtaned from measured daly traffc profles and/or servce-level agreements. If B(s, d) were to dstrbute equally over each possble route between s and d, then the ntal estmate of φ l can be calculated as φ l = (s,d) φ l(s, d)b(s, d). Of course, the ntal estmate of φ l may not be accurate because (1) actual bandwdth demands may devate from the B(s, d) values and (2) equal-load dstrbuton assumpton may not hold at run-tme. Secton III descrbes how the ntal φ l values are ncrementally corrected at run-tme wth each new QVPN. Another mportant consderaton n computng φ l s that the total number of routes between any source-destnaton par grows quckly wth network sze and connectvty. In practce, we can tackle ths ssue as follows. (1) Snce only a small subset of all the n nodes n the network are typcally possble sources or destnatons for QVPN traffc, computng φ l does not nvolve an exhaustve computaton of all the n 2 possble values of φ l (s, d). (2) Between a gven source-destnaton par, we can restrct the choce of routes to k-shortest canddate routes (or dsjont route pars), where k s typcally small (around 5 n our evaluatons). (3) Fnally, the lnk crtcalty φ l (s, d) tself s largely a statc metrc that changes only when the topology tself changes. Thus the values of φ l can be perodcally precomputed (such as on a daly bass) and kept ready for use. D D1 D2 Lnk 2 Cost cost(2) Ideal Trajectory Current Operatng Pont (cost(1), cost(2) ) X ^ φ 2/C 2 ( φ 1/C φ 1, 2/C 2 ) cost = ^ X = (cost(1) φ 1/C1 ) ( cost(2) φ 2/C 2 ) φ 1/C1 cost(1) Lnk 1 Cost Fg. 2. Cost of a smple 2-lnk network. An n-dmensonal plot would represent a network wth n lnks. B. Metrc for Network-wde Load Balancng Let C l be the total bandwdth capacty of a lnk and R l be ts resdual capacty at any tme. We begn by defnng the dynamc cost of each lnk, cost(l) = φ l /R l, as the expected load per unt of avalable lnk capacty. Thus, a lnk wth smaller resdual capacty R l or larger expected load φ l wll be consdered more expensve n routng QVPNs. Networkwde load balancng depends upon the cumulatve mpact of not only the magntude of ndvdual lnk costs but also the varatons among them. Fgure 2 geometrcally llustrates ths relatonshp for a smple network wth two lnks that have expected loads φ 1 and φ 2. The term φ l /C l represents the mnmum value of the lnk cost when the resdual capacty s maxmum at R l = C l. For deal load balance, resdual lnk capactes R 1 and R 2 should deally evolve towards zero such that (cost(1), cost(2)) ndeed stays along the deal load-balance trajectory. At the same tme, n order to mnmze the amount of resources consumed, t may not always be possble to follow the deal trajectory. The next best alternatve s to select routes that mnmze the dstance between the current operatng pont of the network (cost(1), cost(2)) and dle-state operatng pont (φ 1 /C 1, φ 2 /C 2 ). We defne the extent of load balance n a network G as the squared magntude of the dstance vector between the actual and the dle-state operatng pont. cost(g) = ( cost(l) φ ) 2 l (1) C l l G III. LOAD BALANCING ROUTE SELECTION We now present the Prmary LCBR () algorthm that selects a sngle prmary route for a QVPN F N between source s and destnaton d that mnmzes the load balance metrc cost(g). F N requres two forms of QoS guarantees: (a) longterm bandwdth requrement ρ N of F N must be satsfed at each lnk along the route, and (b) end-to-end delay encountered by packets of F N should be smaller than D N. A. Wth Bandwdth Guarantees In ths secton, we consder the QVPNs that requre bandwdth guarantees alone. When we select any route for a QVPN F N, that requres a long-term bandwdth guarantee of ρ N, the resdual capacty R l of each lnk l n the selected route would decrease by ρ N. The contrbuton of each lnk to the network-wde metrc cost(g) s gven by (φ l /R l φ l /C l ) 2.

3 Correspondngly, cost(g) ncreases due to smaller resdual capacty R l along the selected lnks. In order to fnd the route whch produces the smallest ncrement n cost(g), we can frst elmnate lnks wth avalable bandwdth smaller than ρ N and then apply Djkstra s shortest path algorthm on the reduced network graph, where the weght of each lnk s defned as follows: w l = ( φl R l ρ N φ l C l ) 2 ( φl φ ) 2 l (2) R l C l The term w l represents ncrease n lnk l s contrbuton to cost(g) when F N s routed through l. It s straghtforward to see that the route X N wth the mnmum value of l X N w l s the one whch produces the least ncrease n cost(g). Every tme bandwdth ρ N s reserved along a route for a new QVPN F N, the expected load φ l of each lnk n the network needs to be dynamcally updated because (1) the actual traffc profle mght devate from orgnally expected traffc profle B(s, d) and (2) the orgnal φ l values were computed under the assumpton of equal traffc dstrbuton among all canddate routes. Ths update can be performed ncrementally and wth low overhead, wthout recomputng each φ l from scratch. For each lnk l, ts φ l value s ncrementally updated as follows: φ l = φ l + (1 φ l (s, d))ρ N l X N φ l = φ l φ l (s, d)ρ N l / X N (3) B. Wth Bandwdth and Delay Guarantees Consder a QVPN F N that requres an end-to-end delay guarantee of D N, n addton to a bandwdth guarantee of ρ N. Each lnk l s capable of supportng a range of queung delay bounds for F N dependng upon the amount of bandwdth reserved for F N at the lnk l. Ths rases a number of possbltes for parttonng the end-to-end delay budget of a QVPN among the ndvdual lnks of a route [8], [16], [17]. However, n order to perform the delay parttonng, we need to know the complete set of lnks along the selected route. Snce the classcal shortest path algorthm ncrementally bulds the route one lnk at a tme, t cannot handle the end-to-end delay parttonng problem mentoned above. At the same tme, t s also mpractcal to examne the delay parttonng along every possble canddate route between a gven source and destnaton because the number of routes between any source-destnaton par grows quckly wth network sze. In practce, shorter routes typcally tend to utlze fewer network resources n comparson to longer routes and hence t s more lkely that the route whch best mnmzes the network-wde cost metrc s one among the k-shortest canddate routes. The algorthm for bandwdth-delay guaranteed route selecton apples ths nsght to narrow down the set of canddate routes that can mnmze cost(g) to those havng fewer lnks. performs route selecton n two phases - offlne and onlne. In the offlne phase, performed once for the entre network, pre-computes the set of k- shortest canddate routes between each source and destnaton and computes the expected load φ l for each lnk based on the computed canddate routes. A set of k-shortest canddate routes can be pre-computed usng well known algorthms such as [18]. Fortunately, as results n Secton V-C wll demonstrate, a small value of k s suffcent n practce to acheve good network-wde load balance, whch also lowers the computaton overhead. The onlne phase of executes upon the arrval of each new route set up request. The algorthm frst computes cost(l) = φ l /R l for each lnk l n network usng the precomputed value φ l and current resdual capacty R l. For each pre-computed canddate route X between s and d, performs the followng sequence of three operatons. (1) It checks f the QoS requrements (D N, ρ N ) of F N can be satsfed by the avalable resources along route X. (2) If there are suffcent resources, then parttons the end-toend delay D N among the lnks of route X. Specfc delay parttonng algorthms are descrbed n detal n [8], [16], [17]. The result of delay parttonng s a bandwdth reservaton value ρ Nl ρ N for each lnk l along route X that guarantees a perlnk delay budget D Nl such that l X D Nl D N. (3) Next, recomputes the per-lnk remanng capacty R l and the projected value of cost(g) that would result f the route X s assgned to F N. The route set up request for F N s rejected f ether (a) no route X has suffcent resources to satsfy F N s QoS requrements or (b) the mnmum projected value of cost(g) for any route X s greater than a pre-defned cost threshold α. If these two checks do not reject the QVPN F N, then assgns F N to that route X N whch yelds the mnmum ncrement n value of cost(g). The φ l values are correspondngly updated as follows. φ l = φ l φ l (s, d)ρ N + ρ Nl l X N φ l = φ l φ l (s, d)ρ N l / X N (4) IV. PRIMARY-BACKUP ROUTE SELECTION Gven a new QVPN request F N, the goal of Prmary-Backup LCBR (PB-LCBR) algorthm s to select a dsjont prmarybackup route par (X N, Y N ) that mnmzes cost(g). The dsjont backup route Y N guarantees that, f at most one network element (a lnk or a node) fals and the faled element les on the prmary route X N, then F N s traffc would be dverted to Y N wth the same QoS guarantees on bandwdth ρ N and endto-end delay bound D N. The PB-LCBR algorthm smultaneously examnes both prmary and backup components of canddate route pars. The algorthm s smlar n structure to algorthm, although wth mportant varatons that deserve menton. When a QVPN F N requres only a bandwdth guarantee of ρ N, then PB-LCBR fnds the shortest path-par, rather than the shortest path, that ncreases cost(g) by the smallest margn. Specfcally, PB- LCBR selects the path-par (X N, Y N ) wth mnmum value of l (X N Y N ) w l, where w l s gven by Equaton 2. Correspondng to Djkstra s shortest path algorthm, [19] descrbes a shortest path-par algorthm. When F N requres an end-toend delay bound of D N n addton to bandwdth guarantee of ρ N, usng the shortest path-par algorthm s not feasble due to reasons mentoned earler n Secton III-B. In ths case,

4 PB-LCBR follows the framework of n Secton III-B wth two major varatons. The frst varaton s that the offlne phase of PB-LCBR pre-computes a set of k = k 1 k 2 canddate prmary-backup route pars for every source-destnaton par (as opposed to just k 1 canddate prmary routes n the case of P- LCBR). The second varaton s that the nput to the onlne phase conssts of route pars (X, Y ) that were pre-computed durng the offlne phase. The dfference from the onlne phase of s that for each canddate route par (X, Y ) (1) both prmary route X and backup route Y are checked to ensure that suffcent resources are avalable to satsfy new QVPN F N s QoS requrements and (2) the end-to-end delay requrement D N s parttoned along both X and Y. Fnally, the canddate route par (X N, Y N ) that yelds mnmum cost(g) s chosen for F N. In order to maxmze resource usage effcency along backup routes, we now ntroduce the noton of backup resource aggregaton whch attempts to share QVPN reservatons along common backup lnks. Backup resource aggregaton was frst proposed n the RAFT approach [20] n the context of QVPNs that requre bandwdth guarantees alone. Our addtonal contrbuton here s the applcaton of the resource aggregaton concept to both bandwdth guaranteed as well as delay-bandwdth guaranteed QVPNs wthn the comprehensve admsson control and resource allocaton framework of the LCBR algorthm. Two QVPNs are sad to ntersect wth each other at a network element e f both ther prmary routes pass through element e. Every lnk l has one prmary set, P rmary(l), that contans the IDs of all QVPNs whose prmary routes pass through the lnk l. In addton, each lnk has a total of (m + n) backup sets of QVPN reservaton, where each set corresponds to one network element; m s the number of lnks and n s the number of nodes n the entre network. The backup sets at any lnk l are represented by Backup(l, e), 1 e (m + n), where each backup set corresponds to one network element e. Recovery from falure of a sngle network element occurs as follows. Durng normal operatons, each lnk scheduler operates wth the reservatons for QVPNs n ts prmary set P rmary(l). Whenever a network element e fals, ts correspondng backup sets, Backup(l, e), are actvated at all the lnks l and the respectve lnk schedulers start operatng wth reservatons n prmary set P rmary(l) plus those n backup set Backup(l, e). In the meantme, the route selecton mechansm would attempt to recover completely by redscoverng new prmary and/or backup routes of those QVPNs that are affected by the falure of network element e. V. PERFORMANCE EVALUATION We now compare the performance of LCBR aganst two earler traffc engneerng based approaches the Wdest Shortest Path (WSP) [2] based algorthm and the Mnmum Interference Routng Algorthm (MIRA) [11] that were orgnally proposed for bandwdth guaranteed prmary route selecton. The prmary route selecton verson of WSP (P- WSP) works as follows. For QVPNs that requre bandwdth guarantees alone, selects that route whch has maxmum Prmary-Backup Route Selecton PB-WSP PB-MIRA PB-LCBR 3000 Fg. 3. Number of QVPNs admtted wth bandwdth guarantees alone. ρ avg = 10Mbps, k = Prmary-Backup Route Selecton PB-WSP PB-MIRA PB-LCBR 1000 Fg. 4. Number of QVPNs admtted wth bandwdth-delay guarantees. ρ avg = 10Mbps, D = 10ms, k = 5 resdual bottleneck lnk capacty from among all the feasble routes havng mnmum length. The prmary-backup WSP (PB- WSP), selects that feasble route par wth mnmum-length prmary path whch has maxmum bottleneck lnk capacty. For bandwdth-delay guaranteed route selecton, (PB- WSP) examnes a set of k canddate routes (route pars) and select the mnmum length canddate wth maxmum bottleneck capacty. MIRA defnes the weght of a lnk l as the number of source-destnaton pars whose mncuts nclude l. For bandwdth guaranteed route selecton, (PB-MIRA) selects the route (route par) wth mnmum sum of lnk weghts, as defned above. For bandwdth-delay guaranteed route selecton, (PB-MIRA) examnes a set of k canddate routes (route pars) and selects the one wth mnmum sum of lnk weghts. We developed a smulaton tool to compare the resource usage effcency of the three algorthms. In ths paper, we present smulaton results over the AT&T natonwde backbone topology wth 41 nodes and 64 lnks. Due to space constrants, the results for two other topologes the North Amercan IP backbone topology of Sprnt and a 5 5 Grd topology are presented n [21]. Lnk capactes are chosen as a mx from 5 Gbps to 20 Gbps and sources-destnaton pars are selected unformly. Bandwdth demand profle B(s, d), s unformly dstrbuted between 5 Gbps and 20 Gbps. New QVPNs request an average bandwdth guarantee of 10Mbps. Excludng sgnal propagaton delays, whch can typcally range anywhere around ms, the end-to-end queung delay budget of up to 20ms can be requested by each QVPN. QVPNs are constantly admtted tll the network saturates. Intra-path delay parttonng s performed usng LSS algorthm [16] and backup resource aggregaton s appled to all the three PB-* algorthms.

5 Std. Devaton n Lnk Loads (%) Fg. 5. Comparson of standard devaton n lnk loads for WSP, MIRA and LCBR. ρ avg = 10Mbps, D = 10ms, k = 5. Average number of flows admtted A. Effectveness of LCBR Algorthm Canddate Set Sze (k) Fg. 6. Number of QVPNs admtted vs. canddate set sze k. ρ avg = 10Mbps, D = 10ms. We frst provde a snapshot comparson of the performance of LCBR aganst WSP and MIRA. Fgure 3 and 4 plot the number of QVPNs admtted wth bandwdth guarantees and bandwdthdelay guarantees respectvely by dfferent algorthms for 20 smulaton runs, where each run uses a dfferent random seed to controls lnk capactes. The fgures demonstrate that n all scenaros, LCBR consstently admts more QVPNs than WSP and MIRA algorthms snce t bases routng decsons on a network-wde load balancng crtera. On the other hand, WSP performs only lmted load balancng by selectng wdest shortest route among all canddates. The performance of MIRA and WSP are n general close to each other. There are notceable dfferences n the relatve performance of algorthms wth and wthout delay guarantees. Specfcally, we fnd that performance of LCBR s sgnfcantly better compared to WSP and MIRA n the presence of delay requrement than wthout delay requrement. Ths s explaned by the fact that tght delay requrements of a QVPN F N would requre a bandwdth reservaton ρ Nl at each lnk l that s larger than ts average bandwdth requrement ρ N. Thus wth delay-guaranteed QVPNs, there s a tendency towards hgher network-wde load mbalance and the benefts from LCBR s load balancng approach become more evdent. Another notceable trend s that the relatve dfference n performance of LCBR compared to WSP and MIRA s smaller for prmarybackup route selecton. The dsjonted-ness requrement on each prmary-backup route pars reduces the number of good qualty canddates avalable for LCBR to choose from. B. Network-Wde Load Balance We now show that LCBR ndeed mantans better networkwde load balance. Fgure 5 shows that the standard devaton n fnal percentage loads among all the lnks n the network s ndeed consstently smaller for LCBR compared to MIRA and WSP. The reason for LCBR s smaller load devaton s that t explctly mnmzes the load-balance metrc cost(g). Whle the cost(g) values of WSP and MIRA saturate after admttng fewer QVPNs, LCBR contnues to admt more QVPNs. C. Canddate Set Sze Fgure 6 shows that, wth ncreasng canddate set sze k, the number of QVPNs admtted wth bandwdth-delay guarantees ncreases rapdly for LCBR and then quckly saturates. Increasng k mples more choces for selectng a route leadng to more admtted QVPNs. However, for larger k values, the canddate set now ncludes longer routes whch can consume more resources and hence are rarely selected. WSP and MIRA are hardly affected by varyng k. Ths shows that LCBR mproves performance wthout devatng too much from the shortest route t tends to choose among 4 or 5 shortest canddates. WSP does not examne the entre canddate set; ncreasng k helps WSP only f t results n ncluson of more feasble routes wth shortest path length. Smlarly, ncreasng k helps MIRA only f t results n ncluson of routes wth fewer lnks that mpact the maxflow between varous source-destnaton pars. D. End-to-end Delay Fgure 7 shows that, wth ncreasng end-to-end delay, number of QVPNs admtted ncreases ntally and then tends to saturate for all the algorthms. Intally, each QVPN s delay-derved bandwdth requrement s tghter than the average rate requrement and hence delay s the tghter requrement. For larger delay requrement, the Average number of flows admtted End-to-end Delay (ms) Fg. 7. Effect of end-to-end delay on average number of admtted QVPNs. delay-derved bandwdth becomes smaller than the average rate requrement. In the saturaton regon, QVPNs are essentally beng servced at ther average rates. Also, LCBR admts more QVPNs than WSP and MIRA across all delay ranges. E. Computaton Cost The computaton cost for LCBR on a typcal operatonal network s qute small. For algorthm, offlne computaton tme, on a 1.8GHz Pentum 4 machne, vares from 3ms to 18ms as k ncreases from 2 to 10. For PB-LCBR, the correspondng varaton s from 10ms to 50ms. The onlne computaton cost s less than 2ms for and less than 4.5ms for PB- LCBR. The computaton cost s more for PB-LCBR because route selecton and QoS parttonng are performed for both prmary and backup routes. VI. RELATED WORK Tradtonal hop-by-hop shortest path (SP) algorthms [22] for best-effort traffc gnore the fact that lnks along a selected route mght already be congested whle non-congested alternatves may never be consdered. Wdest Shortest Path (WSP) [2] and several varatons [3], [22], [23] perform lmted load balancng and congeston management but fnally suffer the same fundamental problems as SP. QoS routng algorthms attempt to fnd a feasble short term route that satsfes ether sngle [1] [3] or multple [4] [8], [18], [24] QoS requrements, but not to optmze for long term traffc engneerng consderatons. On the other hand, traffc engneerng (TE) solutons attempt to acheve long term

6 network-wde resource management objectves. A class of TE schemes [13], [25], [26] manpulate lnk weghts to mantan load balance and mnmze congeston wth best-effort traffc, but do not support explct QoS guarantees. Mnmum Interference Routng Algorthm (MIRA) [11] s one of the frst explct routng TE schemes that selects the entre route for a QVPN n advance. MIRA uses a noton of mncut-based lnk crtcalty (descrbed n Secton V) whch s useful n avodng lnks that mpact the carryng capacty between large number of ngress-egress pars, but does not dentfy mportant lnks that may not be part of any mncuts. Profle-Based Routng (PBR) [14] uses measured traffc profles to solve a mult-commodty network flow problem and provde bandwdth guarantees. The key feature that dstngushes LCBR from the earler explct TE approaches s that LCBR s network cost metrc quantfes the mpact of all lnks on the networkwde load balance, whether or not they are part of any mncuts. VII. CONCLUSIONS In ths paper, we made the case that the key to maxmze network resource usage effcency under performance constrants s to acheve network-wde load balance every step of the way n the route selecton process. We have proposed the Lnk Crtcalty Based Routng (LCBR) algorthm, whch can select QoS guaranteed routes for wde-area QVPNs. To the best of our knowledge, our work s the frst to explctly quantfy the noton of network-wde load balance and use t systematcally n developng algorthms for traffc engneerng route selecton wth QoS guarantees. LCBR defnes a smple and yet effectve network-wde load balancng metrc that encourages the selecton of less crtcal lnks n the routng process. In our evaluatons, LCBR consstently supports more QVPNs under the same nput workloads, when compared aganst exstng traffc engneerng approaches. [12] H. Smt and T. L, IS-IS extensons for traffc engneerng, Internel Draft, August [13] A. Srdharan, R. Guern, and C. 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