Supporting Consistency Management in Dynamic Content Distribution Overlays

Transcription

1 Supportng Consstency Management n Dynamc Content Dstrbuton Overlays Zhou Su, Jro Katto, Yasuhko Yasuda Faculty of Scence and engneerng, Waseda Unversty Contact E-mal: suzhou@waseda.p Abstract Content Dstrbuton Overlays mproves end-user performance by replcatng Web contents on a group of geographcally dstrbuted stes nterconnected over the Internet. However, wth the development whereby overlay systems can manage dynamcally changng fles, an mportant ssue to be resolved s consstency management, whch means the cached replcas on dfferent stes must be updated f the orgnals change. In ths paper, based on the analytcal formulaton of obect freshness tme, web access dstrbuton and network topology, we derve a novel algorthm as follows: () For a gven content whch has been changed at ts orgnal server, only a lmted number of ts replcas nstead of all replcas are updated. (2) After a replca has been selected for update, the latest verson wll be sent from an algorthm-decded ste nstead of from ts orgnal server. Smulaton results verfy that the proposed algorthm provdes much better consstency management than conventonal methods wth the reduced update overhead and network traffc.. Introducton Wth the growth n popularty of the Internet and the wde avalablty of streamng applcatons, how to effcently dstrbute the stored content has become a maor concern n the Internet communty. Some content dstrbuton networks (CDN) []~[5],[7],] have emerged, and they work drectly wth content provders to cache and replcate the provders content close to the end users by usng geographcally dstrbuted edge servers. More recently, some other researchers have also advocated usng an overlay CDN structure composed of dedcated transt nodes to dstrbute the large content [2]]~[4], [9]. Although both CDN and ts mproved verson (Overlay CDN) facltate statc fle sharng, newlydeveloped applcatons, such as onlne aucton and remote collaboraton, demand that they should be able to manage dynamcally-changng fles. There has been some research on ths problem, whch s called consstency management. However, most of these studes treat dfferent replcas of the same content to be managed for Web consstency n the same manner. Furthermore, how to optmally select a surrogate nstead of an orgnal server to update the content has not been dscussed. In ths paper, we therefore propose an optmal algorthm for controllng Web consstency n Content Dstrbuton Overlay, whch ncludes both conventonal CDN and the mproved Overlay CDN. Frstly, we carry out a theoretcal analyss of the Web access and the freshness tme of obects. Based on ths analytcal result, we then propose a consstency prorty and assgn dfferent prortes to dfferent replcas of the same content. When a gven content s changed at ts orgnal server, nstead of all ts replcas over the whole overlay network, only ts replcas wth hgh prortes wll be updated. Secondly, f one replca of a gven content s selected to be updated, the latest verson of ths content wll be sent from a surrogate wth the lowest update prorty, whch s proposed based on the network topology and bandwdth. Therefore, the latest verson wll be sent from an algorthm-decded ste nstead of from ts orgnal server to reduce the network traffc. Fnally, through smulatons we check the performance of our proposal when the related parameters are changed, and fnd that our proposal can effcently mprove the ht rato and overhead aganst the prevous algorthms. We also show that the necessary parameters n our proposed algorthm can be obtaned from the nformaton readly avalable n the local overlay. 2. Related Work In the Propagaton method, the updated verson of a document s delvered to all copes whenever a change s made to the document at the orgn server. Although the copes always keep the latest verson of Proceedngs of the Jont Internatonal Conference on Autonomc and Autonomous Systems and Internatonal Conference on Networkng and Servces (ICAS/ICNS 2005)

2 the orgnals by the Propagaton, ths method may generate sgnfcant levels of unnecessary traffc f documents are updated more frequently than accessed. Some Web servces employ the tme to lve (TTL) mechansm [8] to refresh ther replcas. However, how to decde the proper value of TTL s stll not resolved. In the Invaldaton [6], an nvaldaton message s sent to all copes when a document s changed at the orgn server. Ths method does not make full use of the dstrbuton network for content delvery and each replca needs to fetch an updated verson ndvdually at a later tme. Therefore, the user-delay may get worse f a frequently accessed document can t be updated on tme. [9] addressed a set of models that capture the characterstc of dynamc content at the sub-document level n terms of ndependent parameters such as the dstrbuton of obects sze, ther refresh tmes and reusablty across tme. Cluster Lease [6] was desgned to mantan data consstency by propagatng server notfcatons to a cluster of proxes n the content dstrbuton networks. However, how to reduce the network traffc caused by the propagaton between server and proxes s not mentoned. [8] proposed a hybrd approach that can generate less traffc than the propagaton approach and the nvaldaton approach. The orgn server makes the decson of usng ether the Propagaton or the Invaldaton method for each document, based on the statstcs about the update frequency at the orgn server and the request rates collected by replcas. However, the algorthm only takes the request frequency nto consderaton. Dscusson should be contnued. MONARCH [2] dvded Web obects nto several dfferent groups based on obect relatonshps and obect-change characterstcs. Furthermore, t dentfes the relatonshps among obects composng a page and used relatonshps to keep all obects consstent. However, how to cooperatvely keep the consstency among replcas stored n dfferent stes has not been resolved. We ourselves proposed an ntegrated pre-fetchng and replacng algorthm for the herarchcal mage based on a cooperatve proxy-server model, n whch the metadata of the herarchcal mage was used to keep the data consstency wth user-satsfacton [23]. We also presented a scheme for stream cachng by usng herarchcally dstrbuted proxes wth adaptve segments assgnment, n whch segment meant a group of pctures [24]. Ths method clarfed the effectveness of local-scope server cooperaton (n the overlay network) wth per-segment management and dscussed how to reduce the overhead n overlay network. 3. Theoretcal Analyss 3. Notatons Parameters () (,) o() r λ R, ΔT,, P X, D m,n (X) C m,n(x) Defnton content Replca of content at surrogate Server orgnally stores () Rankng of request tmes of () Aggregate request rate to server Consstency prorty of (,) Update prorty of (,) Request probablty of obect () Element of placement matrx X Shortest dstance (hop count) from server m to server n under the placement X Average bandwdth (per hop) durng the path from server m to server n under the placement X Table : Clent Workload and Model Parameters We assume that each surrogate s located n a dfferent admnstratve doman, such as an autonomous system (AS). Let S (bytes) denote storage capacty of a server n doman (=,, I), and λ (bytes/second) denote an aggregate request rate from clents to the server. As for the contents, we assume that there are J dfferent contents n our CDN. A parameter P, defnes the request probablty for content (.e., content popularty). In ths paper we look on content as one update obect specfed by (). And ts orgn server s defned as o(). Let X,,, be a parameter whch takes a bnary value of X, = (f obect s stored n server ) X, = 0 (otherwse) () Then, we can get a matrx X of whch one element s X,, whch represents a placement pattern of contents. As for the lnk between two servers, D m,n (X) means the shortest dstance (hop count) from server m to server n under the placement X. And C m,n denotes the average bandwdth (per hop) along the above path from server m to server n. All of the above defned parameters are lsted n Table. Proceedngs of the Jont Internatonal Conference on Autonomc and Autonomous Systems and Internatonal Conference on Networkng and Servces (ICAS/ICNS 2005)

3 3.2 Defnton of Web Access Dstrbuton Let Λ = λ be the total request rate from all the domans. Then, for a gven surrogate, ts surrogate popularty can be gven byλ / Λ. Accordng to the Zp f dstrbuton whch the dstrbuton of Web access follows, the probablty that the content s requested can be obtaned as follows: Ω P ( ) = (2) r α where Ω, α are parameters of the Zpf dstrbuton, and r s the rankng of request tmes. Therefore, we can get the probablty that a request happens for the -th content from surrogate by: Ω Ω λ P (, ) = ( λ / Λ ) = (3) α α r r Λ Recent studes [9] show that the freshness tme of obects follows a Webull dstrbuton wth a CDF: b ( ax) F ( x) = e (4) Furthermore, for content, the mean E(x ) (called MTTF or MTBF) of ths dstrbuton s gven by: b (5) E ( X ) = a Γ ( + ) b where a, b are parameters of the Webull dstrbuton. Assume that the tme when content was last updated s t 0,, and n the perod from t 0, to (t 0, + E(x )) there are W E( X ) total requests happned n the whole CDN system. Then, the number of request tmes for the -th content happened from surrogate wthn ths perod can be obtaned by: Ω R, = W E ( X ) ( λ / Λ ) (6) r α If R, s greater than, t means at least one request has been made for ths obect snce t has been changed last tme. To avod sendng the nvaldaton verson of the data, the replca of content on surrogate should be tmely updated when the orgnal changes. 3.3 Defnton of Average Hop Count In a conventonal method, f a surrogate decdes to fetch the latest verson of a modfed document, t wll contact the modfed document s orgnal server to fetch ts latest verson. If we defne an average hop count H k,,o() (X), whch represents the traverse of the latest verson of content from surrograte k (where a stale copy of content s sotored ) to the orgnal server o (). It can be obtaned by: H = D ( X) ( ) λ P = D ( X) S λ S ko,,() ko,() k ko,() k, = ( ) λ P λ k, k (8) (7) Eq.(8) represents a request probablty weghted by aggregaton rato to server (.e. ont probablty of stream popularty and server popularty). The parameter D k,o() (X) denotes the shortest dstance (hop count) from doman k to server o() storng the obect () under the placement X wth X = (9) k, In the above method, as all update requests are sent to the same orgnal server o() to fetch the latest verson of content, t causes poor user-delay and load balance. Some researchers also advocate fetchng the latest verson from another surrogate nstead of the orgnal server. However, how to select a proper surrogate s stll a problem to be dealt wth. 3.4 Mnmzaton of User Perceved Latency In a conventonal method, f a surrogate decdes to fetch the latest verson of a modfed document, t wll contact the modfed document s orgnal server to fetch ts latest verson. Because all update requests are sent to the same orgnal server o() to fetch the latest verson of content, t always causes poor user-delay and load balance. In ths subsecton, we made the analyss of network traffc cause by sendng the modfed verson of a document. Our goal s to take the latest verson of the modfed document from an alternatve surrogate nstead of the orgnal sever to mnmze the user perceved latency. When a request happens for obect () (content ) from a gven surrogate t where the latest verson of obect () s not avalable, f we assume that there are K surrogates where the latest verson of obect () (content ) s avalable expect the orgnal server o( ), for k={,,k}, we can get: K<=I& k t k o() & X k, = (0) Assume that content s orgnally stored n server o() and C k,t s the average bandwdth (per hop) durng the path from surrogate k to surrogate t. Then, f a clent sends a request for obeect () to surrogate t and Proceedngs of the Jont Internatonal Conference on Autonomc and Autonomous Systems and Internatonal Conference on Networkng and Servces (ICAS/ICNS 2005)

4 surrogate k sends the latest verson to ths clent, the user delay durng the delvery from server k to server t s gven by T (X) = λ B P D (X) C (X ) () kt,, k kt, kt, Λ D k,t) (X 0 ) s the shortest dstance from server k to server t under the ntal placement pattern X and s the total request rate from all the domans. Λ = λ If we contnue to defne: G = B P (2) Λ U (X ) = D (X ) C (X ) (3) k, t k, t k, t t can be obtaned: T (X ) = λ G U (X ) (4) k, t, k k, t Smlarly, f a clent sends a request for obeect () to surrogate t and orgnal server o() sends the latest verson to ths clent, the user delay durng the delvery from server k to server o( ) s gven by T (X) = λ G U (X ) (5) k, o( ), k k, o( ) For a gven surrogate k, we can calculate the reduced user delay ΔT k, by takng a dfference of Eq.(4) and Eq.(5) Δ T = G λ ( U (X) U ) (X)) (6) k, k kt, ko, ( 3.5 Proposed Algorthm We present our algorthm as follows: Step: Scalable Update Selecton When a gven content changes at server o(), a consstency prorty R, wll be calculated accordng to Eq.6. For every replca of content (X, =, ={,,I}) over the whole overlay network, only ts prorty R, s beyond the threshold Th, the replca of content at surrogate wll be updated. Otherwse, ths replca wll not be updated untl a new request for content happens at the ste next tme. Therefore, when a gven content s changed at ts orgnal server, not all ts replcas (X, = ) over the entre overlay network wll be updated to avod the unneccsary waste of update. Step2: Lowest Delay Updatng Assume that there are K ( (X k, =, k={,,k} & K<=I) ) surrogates whch keep the latest verson of content, whne we decde to select whch sorrogate to provde the latest verson to the clent, an update prorty ΔT k,, wll be calculated accordng to Eq.6. The latest verson of content wll be sent to the clent from surrogate k wth the lowest ΔT k,,. Therefore, the latest verson wll be sent from an algorthm-decded ste nstead of ts orgnal server, resultng n the reducton of network traffc and user delay. 4. Evaluaton of Algorthms In ths secton numercal results wll be presented by smulaton experments to valdate the proposed algorthm. 4. Smulaton Condtons Recent studes show that most communcaton networks have Power-Law lnk dstrbutons [22], where the 'th most connected node has Ώ/r β neghbors. As for the network topology, to show the performances of our proposal under dfferent network topologes, we carry out our proposal under the Power- Law lnk dstrbuton as the second step and the parameter β n the Power-Law lnk dstrbuton s set to be 0.8 [5]. Because the dstrbuton of web requests has already proved to follow a Zpf dstrbuton, whch states that the relatve probablty of requests for the 'th most popular page s proportonal to Ώ/r α, the access frequency s decded by ths Zpf dstrbuton wth α =0.8 [20][2]. About the contents, there are 000 dfferent contents. Clent requests arrve accordng to a Posson process [0][7]. All clents are always redrected to the closest server wthout falure of request routng. The total request tmes n the smulatons are There are three replcaton algorthms we wll study: Propagaton Polcy Invaldaton Polcy Proposal To evaluate dfferent algorthms, we use two performance measures. The frst one s traffc generated durng the process of sendng the latest verson of a gven content. Another one s Old Ht, whch s the percentage of nvald obects (not the latest verson) when a request arrves at the replca. 4.2 Smulaton Results Fgure shows the result of Old Ht, whch means that the requested data s not of the new verson. Proceedngs of the Jont Internatonal Conference on Autonomc and Autonomous Systems and Internatonal Conference on Networkng and Servces (ICAS/ICNS 2005)

5 Because the updated verson of the requested document s delvered to all copes when a change s made at ts orgn server n the Propagaton, ts Old Ht s zero. However, the network traffc caused by the Propagaton s very serous as n Fg.2, where the traffc caused by sendng the new verson s shown. As for the Invaldaton, although ts traffc s the least, ts Old Ht s the worst. Our proposal can balance the two conventonal ones: Compared wth the Invaldaton, ther traffcs are closed to each other, but the Old Ht of our proposal s much better. Compared wth the Propagaton, although the Old Ht of our proposal s more than that of the Propagaton, ts traffc can be greatly reduced. The network traffc s calculated by multplyng the data sze by the traversed AS Hops. Old Ht request from a fxed group of users follows a Zpf dstrbuton. Besdes, the value of α, a parameter of Zpf dstrbuton, vares from trace to trace, rangng from 0.64 to 0.83 [20][2]. We then vared the Zpf parameter and get the results shown n Fg.4 and Fg.5. We frstly tested Old Ht wth respect to the vared parameter α. Fgure 3 shows that the proposed algorthm obtans stable performance when the Zpf parameter s changed from 0.6 to It always outperforms the conventonal ones (Invaldaton or Propagaton). Network Traffc (By Zpf P aram eter Invaldaton proposal propagaton Fg. 3: Network Traffc under Dfferent Zpf Parameters Fg.: Comparson of Old Ht wth Dfferent Replcaton Algorthms. Network Traffc (By In valdaton proposal propagaton Fg. 2: Comparson of Network Traffc wth Dfferent Replcaton Algorthms. We contnue to test the algorthm performance when the web access parameters are changed. Several researchers have observed that the dstrbuton of web Old H Zpf P aram eter Fg. 4: Old Ht under Dfferent Zpf Parameters Note that the performance of our proposal gets better wth the Zp f parameter ncreased. When the Zp f parameter s ncreased, the popular obects are requested more often compared wth the stuaton under the low Zp f parameter. It becomes easy for our algorthm to manage the clent s always-requested obects. As our proposal s ntended to keep these obects consstences well, t results n the hgher performance. Proceedngs of the Jont Internatonal Conference on Autonomc and Autonomous Systems and Internatonal Conference on Networkng and Servces (ICAS/ICNS 2005)

6 We then smulate network traffc under the dfferent Zpf parameters are carred out. Smlar results are shown n Fg. 45, where the proposed one reduced network traffc most. Snce our proposed algorthm s desgned to reduce the user delay, the clent can get the latest verson of the request content from the nearer surrogate, so network traffc can also be reduced at the same tme. We conclude that the proposal has better performance and s robust n varyng stuatons when the web access pattern s changed. 5. Conclusons Ths paper proposed a novel algorthm to mnmze average user delay over traversed domans where the scalable content consstency s obtaned. Our proposal dealt wth not only populartes of contents and servers but also server load. We then compared our proposal wth other conventonal methods usng computer smulatons. As for further researches, frst, we plan to do more smulaton results when other parameter and network topology are also consdered. Secondly, theoretcal analyss should be expanded to be applcable to general cases. Fnally, mplementaton s to be carred out. References []J.Kangasharu and K.W. Ross, Performance Evaluaton of Redrecton Schemes n Content Dstrbuton Networks, The 5th Internatonal Web Cachng and Content Delvery Workshop, May [2] A.Beck and M. Hofmann, Enablng the Internet to Delvery Content-Orented Servces Proc. The 6th Internatonal Web Cachng and Content Dstrbuton, Boston, USA Jun 200. [3] Adero, <URL: http: www. adero. com> [4] Akama, <URL: http: www. akama. com> [5] Napster, < URL: [6] P. Cao and C. Lu, Mantanng Strong Cache Consstency n theworld-wde Web, Proc. 7th Int l Conf. Dstrbuted ComputngSystems, May 997. [7] H M. Radha, M.V.D. Schaar, and Y. Chen, The MPEG- 4 Fne Graned Scalable Vdeo Codng Method for Multmeda Streamng Over IP, IEEE Trans. Multmeda Vol.3, No., pp.53-67, March 200. [8] V. Cate, Alex: A Global Fle System, Proc. 992 USENIX FleSystem Workshop, pp. -2, May 992. [9] W.Sh, E.Collns, and V,Karamchet, Modelng obect characterstcs of dynamc Web content, Journal of Parallel and Dstrbuted Computng, Volume 63, Issue 0,Oct,2003 [0] M. Chesre, A. Wolman, G.M.Voelker, and H.M.Levy, Measurement and Analyss of a Stream Meda Workload, USITIS 0, San Francsco, CA, Mar.200. [] S. Acharya and B. Smth and P. Parnes, Characterzng User Access To Vdeos on the Vdeos On the World Wde Web SPIE/ACM MMCN 2000, San Jose, CA, Jan [2] Mkhal Mkhalov, Crag E. Wlls, Evaluatng a New Approach to Strong Web Cache Consstency wth Snapshots of Collected Content, The Twelfth Internatonal World Wde Web Conference, May 2003, Budapest, HUNGARY [3] I. Cdon, S. Kutten, and R. Soffer. Optmal allocaton of electronc content, IEEE Infocom, Anchorage, AK, Aprl, 200. [4] B. L, M. J. Goln, G. F. Italano, and X. Deng. On the optmal placement of web proxes n the nternet. IEEE Infocom, New York, NY, pp 2-25, March 999. [5] L. Qu, V. N. Padmanabhan, and G. M. Voelker. On the placement of web server replcas. IEEE Infocom, Anchorage, AK, pp 22-26, Aprl 200. [6] A.Nnan, P.Kulkarn, P.Shenoy, K.Ramamrtham, R.Tewar Scalable Consstency Mantenance n Content Dstrbuton Networks Usng Cooperatve Leases, IEEE Transactons on Knowledge and Data Engneerng, July/August 2003 [7] Sung-Ju Lee, We-Yng Ma, and Bo Shen An Interactve Vdeo Delvery and Cachng System Usng Vdeo Summarzaton, WCW200, Boston, MA, June 200 [8] Zongmng Fe, ``A novel approach to managng consstency n content dstrbuton networks", Proceedngs of the 6th Internatonal Web Cachng and Content Dstrbtuton Workshop (WCW'0), Boston, MA, June 200, pp.7-86 [9] S.Ganguly, A. Saxena, S.Bhatnagar, S.Baneree, R.Izmalov Fast Replcaton n Content Dstrbuton Overlays, IEEE Infocom, Mam FL, 2005 [20] L. Breslao, P. Cao, L. Fan, G. Phllps, and S. Shenker Web Cachng and Zp-lke Dstrbutons: Evdence and Implcatons Proc. IEEE INFOCOM 99, New York, Aprl, 999. [2] L. Breslau, P. Cao, L. Fan, G. Phllps, and S. Shenker, "On the Implcatons of Zpf's Law for Web Cachng", In 3rd Internatonal WWW Cachng Workshop, June 998. [22] L. A. Adamc, B. Humberman, R. Lukose, and A. Punyan. Search n Power Law Networks Phys. Rev. E, Vol. 64, 200. [23] Z.Su, T.Washzawa, J.Katto, and Y.Yasuda, Integrated Pre-fetchng and Cachng Algorthm for Graceful Image Cachng, IEICE Trans on Commun, Vol.E86-B, No.9, Sep. 2003, pp [24] Z.Su, J.Katto, T.Nshkawa, M.Murakam and Y.Yasuda, Stream Cachng Usng Herarchcally Dstrbuted Proxes wth Adaptve Segments Assgnment, IEICE Trans on Commun, Vol.E86-B, No.6, Jun. 2003, pp Proceedngs of the Jont Internatonal Conference on Autonomc and Autonomous Systems and Internatonal Conference on Networkng and Servces (ICAS/ICNS 2005)