SRB: Shared Running Buffers in Proxy to Exploit Memory Locality of Multiple Streaming Media Sessions

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1 SRB: Shared Runnng Buffers n Proxy to Explot Memory Localty of Multple Streamng Meda Sessons Songqng Chen,BoShen, Yong Yan, Sujoy Basu, and Xaodong Zhang Department of Computer Scence Moble and Meda System Lab The College of Wllam and Mary Hewlett-Packard Laboratores Wllamsburg, VA 387, USA Palo Alto, CA 9434, USA fsqchen,zhangg@cs.wm.edu fboshen,basusg@hpl.hp.com Abstract Wth the fallng prce of the memory, an ncreasng number of multmeda servers and proxes are now equpped wth a large DRAM memory space. Cachng meda objects n the memory of a proxy helps to reduce network traffc, dsk I/O bandwdth requrement, and data delvery latency. The runnng buffer approach and ts alternatves are representatve technques to cache streamng data n the memory. However, there are two lmts n the exstng technques. Frst, although multple runnng buffers for the same meda object co-exst n a gven processng perod, data sharng among the multple buffers s not consdered. Second, user access patterns are not nsghtfully consdered n the buffer management. In ths paper, we propose two technques based on shared runnng buffers (SRB) n the proxy to address these lmts. Consderng user access patterns and characterstcs of the requested meda objects, our technques adaptvely allocate memory buffers to fully utlze the currently buffered data of streamng sessons, wth the am to reduce both the server load and the network traffc. Expermentally comparng wth several exstng technques, we show that the proposed technques have acheved sgnfcant performance mprovement by effectvely usng the shared runnng buffers.. Introducton The basc nfrastructure of a Web content delvery network s a server-proxy-clent system. In ths system, the server delvers the content to the clent through a proxy. The proxy can choose to cache the object so that subsequent requests to the same object can be served drectly from the proxy wthout contactng the server. Proxy cachng strateges have therefore been the focus of many studes. Much work has been done n cachng the statc Web contents to reduce network load and end-to-end latency. The delvery of streamng meda content presents several challenges: () The sze of a streamng meda object s usually orders of magntudes larger than tradtonal textbased Web contents. For example, a two hour MPEG vdeo requres more than GB of dsk space, whle text-based Web objects are of the magntude of KB; () The demand of contnuous and tmely delvery of a streamng meda object s more rgorous than that of the text-based Web pages. Therefore a lot of resources have to be reserved for delverng the streamng meda data to a clent. In practce, even a relatvely small number of clents can overload a meda server, creatng bottlenecks by demandng hgh dsk bandwdth on the server and hgh network bandwdth to the clents. To address these challenges, researchers have proposed dfferent methods to cache streamng meda objects. Partal cachng (see e.g. [3], [7], [], [], [3], [4]) s a techncal method to cache ether a prefx or segments of a meda object n the dsk storage of the proxy. Researchers have also pad attenton to dynamcally cachng streamng data n the proxy memory to reduce the access latency. The fxed-szed runnng buffer cachng [] and the nterval cachng [4], [5] are two representatve memory-based runnng buffer based cachng technques. The basc dea of the runnng buffer based cachng technque s as follows. When a request arrves, a fxed-szed buffer of a predetermned length s allocated n the man memory to cache the meda data fetched by the proxy, hopng that subsquent requests could reuse the data n the memory nstead of obtanng t from other sources (the dsk, the orgn server or other caches). In contrast, the nterval cachng technque uses a dfferent approach. It consders two mmedately followed requests as a request par, and ncrementally orders the arrval ntervals of all request pars (the arrval nterval of a request par s defned as the dfference n ther arrval tmes). In the memory allocaton, the nterval cachng gves a preference to smaller ntervals, ex- Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE

2 pectng more requests can be served for a gven amount of memory. Fgure llustrates the basc deas of the runnng buffer cachng and the nterval cachng technques. Meda Poston R R R3 R4 R5 R6 (a) B B Access Tme Meda Poston R R R3 R4 R5 R6 (b) B B Access Tme Fgure. Runnng Buffer (a) and Interval Cachng (b) In Fgure, the Meda Poston ndcates a tme poston n a streamng meda where the meda object s delvered to the clent. The sold slope represents a delvery sesson. In Fgure (a), a fxed-szed buffer B s allocated upon the arrval of the request R. Subsequently, requests R, R3, R4 are served by the data cached n ths buffer snce they arrve n tme. The request R5 does not arrve n tme, so a new buffer B of the same length s allocated, whch benefts the request R6. In Fgure (b), upon the arrval of R, anntervals formed between R and R, and a buffer of the nterval sze s allocated to cache data read by R from now on. So the request R only needs to read the frst part of data from the proxy/server whle recevng the rest data from the buffer. The stuaton changes untl the arrval of request R5,where we assume the nterval betweenr4 and R5 s smaller than that between R3 and R4. Snce the nterval between R4 and R5 s smaller than that between R3 and R4, the buffer allocated for the nterval between R3 and R4 s deallocated, and the space s re-allocated to the new nterval between R4 and R5. However, the runnng buffer cachng does not take consderaton of user access patterns, resultng n the neffcent usage of the memory resource. For example, n Fgure (a), the sze of buffer B s bgger than the amount needed to serve the requests of R through R 4, the sze of buffer B s bgger than the amount needed to serve the request R 5 and the request R 6. The nterval cachng approach does consder the user access pattern n the buffer allocaton. However, t shares another lmt wth the runnng buffer cachng: data sharng among dfferent buffers has not been consdered. For example, B n Fgure (b) does not need to run to the end of the meda f the data cached n buffer B are shared by the later requests. In ths paper, we frst propose a new memory-based cachng algorthm for streamng meda objects, called Shared Runnng Buffers (SRB). In ths algorthm, the memory space on the proxy s allocated adaptvely based on the user access patterns and the requested meda objects themselves. By cachng streamng sessons n runnng buffers, ths algorthm dynamcally caches meda objects n the memory whle delverng the data to the clent so that the bottleneck of the dsk and/or network I/O s releved. More mportantly, the data cached n dfferent runnng buffers are fully shared, whch s dfferent from any of the prevous work [], [4], [5]. Ths approach s especally useful when requests to streamng objects are hghly temporally localzed. The algorthm also effcently reclams the dle memory space and does near-optmal buffer replacement at runtme when requests are termnated. By further lookng nto the patchng approaches that were heavly studed n the VOD (Vdeo-On-Demand) envronment [6], [8], we found that patchng algorthms, such as the greedy patchng, the grace patchng and the optmal patchng [9], take advantage of the clent-sde storage resource to buffer data n multple channels wthout any delay. The greedy patchng always patches to the exstng complete stream whle the grace patchng restarts a new complete stream at some approprate ponts n tme. Furthermore, the optmal patchng [] consders how to reuse the lmted storage on the clent sde to receve as many data as possble whle lstenng to as many channels as possble. Motvated by ths, we further propose an effcent meda delverng algorthm: Patchng SRB (PSRB), whch further mproves the performance of the meda data delvery wthout the necessty of cachng. Fnally, we evaluated our algorthms through a comprehensve set of smulatons based on synthetc workloads and a real access trace of an enterprse meda server. The smulaton results show that the performance of our algorthms s superor to prevous solutons. The rest of the paper s organzed as follows. Secton descrbes the memory-based SRB algorthms we proposed. Smulaton based performance evaluaton results are presented n Secton 3. We then make concludng remarks n Secton 4.. Shared Runnng Buffers (SRB) Meda Cachng Algorthm It has also been shown that two current memory cachng approaches of the meda objects: the runnng buffer cachng and the nterval cachng, do not make effectve use of the lmted memory resource. Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE

3 Motvated by the lmts of the current memory bufferng approaches, we desgn a Shared Runnng Buffer (SRB) based cachng algorthm for streamng meda wth the am to maxmze the memory utlzaton. In ths secton, wth the ntroducton of several new concepts, we frst descrbe our basc SRB meda cachng algorthm n detal. Then, we present an extenson to the SRB: Patchng SRB (PSRB)... SRB Related Concepts The algorthm frst consders buffer allocaton n a tme span T startng from the frst request. We denote R j as the j-th request to meda object, andt j as the arrval tme of ths request. Assume that there are n request arrvals wthn the tme span T and R n s the last request arrved n T.For the convenence of representaton wthout losng precson, T s normalzed to and T j (where <j» n) s a tme relatve to T. Based on the above, the followng concepts are defned to capture the characterstcs of the user request pattern.. Interval Seres: An nterval s defned as the dfference n tme between two consecutve request arrvals. We denote I j as the j-th nterval for object. AnInterval Seres conssts of a group of ntervals. Wthn the tme T,fn =, the nterval I s defned as ;otherwse, t s defned as: ( T j+ T j ; f» j<n I j = T T n ; f () j = n: Snce I n represents the tme nterval between the last request arrval and the end of the nvestgatng tme perod, t s called as the Watng Tme.. Average Request P Arrval Interval (ARAI):TheARAI s defned as n k= I k =(n ) when n>. ARAI does not exst when n = snce t ndcates only one request arrval wthn tme frame T andthuswesettas. For the buffer management, three buffer states and three tmng concepts are defned respectvely as follows.. Constructon State & Start-Tme: When an ntal buffer s allocated upon the arrval of a request, the buffer s flled whle the request s beng served, expectng that the data cached n the buffer could serve the closely followed requests for the same object. The sze of the buffer may be adjusted to cache less or more data before t s frozen. Before the freezng happens, the buffer s n the Constructon State. Thus, the Start-Tme of a buffer B j, the j-th buffer allocated for object, s defned as the arrval tme of the last request before the buffer s frozen. We use S j to denote the Start-tme of the buffer B j. The requests arrvng n a buffer s Constructon State are called as the resdent requests of ths buffer and the buffer s called as the resdent buffer of these requests.. Runnng State & Runnng-Dstance: After the buffer freezes ts sze t wll serve as a runnng wndow of a streamng sesson and moves along wth the streamng sesson. Therefore, the state of the buffer s called the Runnng State. The Runnng-Dstance of a buffer s defned as the dstance n terms of tme between a runnng buffer and ts precedng runnng buffer. We use D j to denote the Runnng-Dstance of B j. Note that for the frst buffer allocated to an object, D s equal to the length of object : L. Here, we assume a complete vewng scenaro ntally. Snce we are encouragng the sharng among the buffers, the buffer B j needs only to run to the end pont of B j. Mathematcally, we have: ( L ; f j = D j = S j Sj () ; f j>: 3. Idle State & End-Tme: When the runnng wndow reaches the end of the streamng sesson, the buffer enters the Idle State, whch s a transent state that allows the buffer to be reclamed. The End-Tme of a buffer s defned as the tme when a buffer enters dle state and s ready to be reclamed. The End-Tme of the buffer B j, denoted as s defned as: E j E j ( j S = ; f j = (3) T latest + D j ; f j>: T latest denotes the arrval tme of the most recent request to the object. Here, the T latest dynamcally changes wth the comng of new requests and so does the E j. The detaled updatng procedure of s descrbed n the followng Ej secton... SRB Algorthm For an ncomng request to the object, the SRB algorthm works as follows: () If the latest runnng buffer of the object s cachng the prefx of the object, the request wll be served drectly from all the exstng runnng buffers of the object. () Otherwse, (a) If there s enough memory, a new runnng buffer of a predetermned sze T s allocated. The request wll be served from the new runnng buffer and all exstng runnng buffers of the object. (b)if there s no enough memory, the SRB buffer replacement algorthm (see..3) s called to ether re-allocate an exstng runnng buffer to the request or serve ths request wthout cachng. (3) Update the End-Tmes of all exstng buffers Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE

4 Meda Poston T (a) Access Tme Meda Poston T (b) Access Tme Meda Poston T T Fgure. SRB Memory Allocaton: the Intal Buffer Freezes ts Sze (c) Access Tme of the object based on Equaton 3. Durng the process of the SRB algorthm, parts of a runnng buffer could be dynamcally reclamed as descrbed n Secton.. due to the request termnaton and the buffer s dynamcally managed based on the user access pattern through a lfecycle of three states as descrbed n Secton SRB Buffer Lfecycle Management Intally, a runnng buffer s allocated wth a predetermned sze of T. Startng from the Constructon State, t then adjusts ts sze by gong through a three-state lfecycle management process as descrbed n the followng. ffl Case : the buffer s n the Constructon State. The proxy makes a decson at the end of T as follows. If ARAI =, whch ndcates that there s only one request arrval so far, the ntal buffer enters the Idle State (case 3) mmedately. For ths request, the proxy wll serve as a bypass server,.e., the content s passed to the clent wthout cachng. Ths scheme gves preference to more frequently requested objects n the memory allocaton. Fgure (a) llustrates ths stuaton. The shadow ndcates the allocated ntal buffer, whch s reclamed at T. If I n >ARAI(I n s the watng tme), the ntal buffer s shrunk to the extent that the most recent request can be served from the buffer. Subsequently, the buffer enters the Runnng State (case ). Ths runnng buffer wll serve as a shftng wndow and run to the end. Fgure (b) llustrates an example. Part of the ntal buffer s reclamed at the end of T. Ths scheme performs well for perodcally arrved request groups. If I n» ARAI, the ntal buffer mantans the constructon state and contnues to grow to the length of T,whereT = T I n + ARAI, expectng that a new request arrves very soon. At T,theARAI and I are recalculated and the n above procedure repeats. Eventually, when the request to the object becomes less frequent, the buffer wll freeze ts sze and enter the Runnng State (case ). In the extreme case, the full length of the meda object s cached n the buffer. In ths case, the buffer also freezes and enters the runnng state (a statc runnng). For most frequently accessed objects, ths scheme ensures that the requests to these objects are served from the proxy drectly. Fgure (c) llustrates ths stuaton. The ntal buffer has been extended beyond the sze of T for the frst tme. The buffer expanson s bounded by the avalable memory n the proxy. When the avalable memory s exhausted, the buffer freezes ts sze and enters the runnng state regardless of future request arrvals. ffl Case : the buffer s n the Runnng State. After a buffer enters the runnng state, t has run away from the begnnng of the meda object and subsequently arrved requests can not be served completely from the runnng buffer. In ths case, a new buffer of an ntal sze T s allocated and subsequent requests are served from the new buffer as well as ts precedng runnng buffers. In addton, the End-Tme of the new runnng buffer needs to be determned and the End-Tmes of ts precedng runnng buffers E j,... E need to be modfed accordng to the arrval tme of the latest request, as shown n Equaton 3. Fgure 3(a) llustrates the maxmal data sharng n the SRB algorthm. The requests R n to R k+ are served smultaneously from B and B. Late requests could be served from all exstng precedng runnng buffers. Note that except for the frst buffer, the other buffers do not have to run to the end of the object. When the buffer runs to ts End-Tme, tenters the Idle State (case 3). ffl Case 3: the buffer s n the Idle State. Whenabuffer enters the Idle State, t s ready for reclamaton. In the above algorthm, the tme span T (whch s the ntal buffer sze) s determned based on the object length. Typcally, a Scale factor (say, / to /3) of the orgn length s used. To prevent a extremely large or small buffer sze, the buffer sze s bounded by a upper bound: Hgh- Bound and a lower bound: Low-Bound. It can be adjusted by the streamng rate to allow the ntal buffer to cache a reasonable length (e.g., mnute to mnutes) of meda data. The algorthm requres the clent be able to lsten to multple channels at the same tme: once a request s posted, t should be able to receve data from all the ongong runnng buffers of that object smultaneously. Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE

5 Meda Poston B R R... R k R k+ R n (a) B Access Tme R Meda Poston R 3 R 4 5 R R 6 R 7 8 R R B B b a (b) Access Tme Fgure 3. Data Sharng among Buffers n SRB Algorthm (a) and Example of PSRB Algorthm (b)... SRB Buffer Dynamc Reclamaton The memory reclamaton of a runnng buffer s trggered by two dfferent types of sesson termnatons: the complete sesson termnaton and the premature sesson termnaton. In the complete sesson termnaton, a sesson termnates only when the delvery of the whole meda object s completed, whch only happens when the buffer s n the Runnng State. In ths case, assume that R s the frst request beng served by a runnng buffer. When R reaches the end of the meda object, the followng two scenaros happen for the resdent buffer of R ;. If the resdent buffer s the only runnng buffer for the meda object, the resdent buffer enters the dle state. In ths state, the buffer mantans ts content untl all the resdent requests reach the end of the sesson. On that tme, the buffer s released.. If the resdent buffer s not the only runnng buffer, that s, there are succeedng runnng buffers, the buffer enters the dle state and mantans ts content untl ts End-Tme. Note that the End-Tme may be updated by succeedng runnng buffers. The premature sesson termnaton s much more complcated. In the premature sesson termnaton, the request arrvng later may termnate earler, whch can happen when a buffer s n the Constructon State or the Runnng State. Consderng a group of consecutve requests R to that Rn are beng served by a runnng buffer, the sesson for one of the requests, say R j,where <j< n, termnates before everyone else. The stuaton s handled as follows.. If R j s served from the mddle of ts resdent buffer, that s, there are precedng and succeedng requests served from the same runnng buffer, the resdent buffer mantans ts current state and the request R j gets deleted from all ts assocated runnng buffers.. If R j s served from the head of ts resdent buffer, the request s deleted from all of ts assocated runnng buffers. The resdent buffer enters the dle state for a tme perod of I. Durng ths tme perod, the content to the head. At the end of the tme perod I, the buffer space from the tal to the last served request s released and the buffer enters the runnng state agan. wthn the buffer s moved from R j+ 3. If R j s served at the tal of a runnng buffer, two scenaros are further consdered. ffl After deletng the R j from the request lst of ts resdent buffer, f the request lst s not empty, then do nothng. Alternatvely, the algorthm can choose to shrnk the buffer to the extent that R j can stll be served from the buffer (assumng R j s a resdent request of the same buffer). In ths case, the End-Tmes of the succeedng runnng buffers need to be adjusted. ffl If R j s at the tal of the last runnng buffer, the buffer wll be shrunk to the extent that R j s the last request served from the buffer. R j s deleted from the request lst...3. SRB Buffer Replacement Polcy The replacement polcy s mportant n the sense that the avalable memory s stll scarce compared to the sze of vdeo objects. So to effcently use the lmted resources s crtcal to acheve the best performance gan. In ths secton, we propose popularty based replacement polces for the SRB meda cachng algorthm. The basc dea s descrbed as follows: ffl When a request arrves whle there s no avalable memory, all the objects that have on-gong streams n the memory are ordered accordng to ther populartes calculated n a certan past tme perod. If the object beng demanded has a hgher popularty than the least popular object n the memory, then the latest runnng buffer of the least popular object wll be deallocated, and the space s re-allocated to the new request. Those requests wthout runnng buffers do not buffer ther data at all. In ths case, theoretcally, they are assumed to have no memory consumpton. We have precsely analyzed our popularty based replacement polces by both the modelng and the smulaton n the reference [], whch s omtted due to page lmts..3. Patchng SRB (PSRB) Meda Delverng Algorthm Snce the proxy has a fnte amount of memory space, t s possble that the proxy serves as a bypass server to transently cache concurrent sessons. The SRB algorthm pro- Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE

6 hbts the sharng of such sessons, whch may lead to excessve server access when there are ntensve request arrvals to many dfferent objects. To solve ths problem, the SRB algorthm s extended to a Patchng SRB (PSRB) algorthm whch enables the sharng of such bypass sessons. It s mportant to note that PSRB scheme makes the memorybased SRB algorthm work wth the memoryless patchng algorthm. Fgure 3(b) llustrates a PSRB scenaro. The frst runnng buffer B has been formed for requests R to R5.Nobuffer s runnng for R 6 snce t does not have a close neghborng request. However, a patchng sesson has been started to retreve the absent prefx n B from the content server. At ths tme, request R 6 s served from both the patchng sesson and B untl the mssng prefx s patched. Then, R6 s served from B only (the sold lne for R6 ends). When R 7 and R 8 arrve and form the second runnng buffer B, they are served from B and B as descrbed n the SRB algorthm. In addton, they are also served from the patchng sesson ntated for R 6. Note that the patchng sesson for R 6 s transent, or we can thnk of t as a runnng buffer sesson wth zero buffer sze. As evdent from the fgure, the fllng of B does not cause server traffc between poston a and b (no sold lne between a and b)snceb s flled from the patchng sesson for R 6. Sharng the patchng sesson further reduces the the number of server accesses for R 7 and R8. In general, the PSRB algorthm s a combnaton of the SRB algorthm wth the optmal patchng algo- rthm proposed n []. By usng more clent-sde storage, PSRB tres to maxmze the data sharng among concurrent sessons n order to mnmze the server-to-proxy traffc. 3. Performance Evaluaton To evaluate the performance of the proposed algorthms and to compare them wth pror solutons, we have mplemented an event-drven smulator to model a proxy s memory cachng behavor. Both synthetc workloads and a real workload extracted from enterprse meda server logs are used. However, n the followng context, only the performance results based on the real workload are presented. Others are omtted due to page lmts. Interested readers can refer to []. The real workload, named as REAL, s extracted from HP Corporate Meda Solutons, coverng the perod from Aprl to Aprl,. There are a total of 43 objects, and the unque object sze accounts to G. There are 9 requests, whch run for 9647 seconds, roughly days. Our analyss shows that 83% requests only vew the objects for less than mnutes and 56% requests only vew the objects for less than %. Only about % requests vew the whole objects. 3.. Evaluaton Metrcs Snce the object ht rato or ht rato s not sutable for evaluatng the cachng performance of the streamng meda, we use the server traffc reducton (shown as bandwdth reducton n the fgures) to evaluate the performance of the proposed cachng algorthms. If the algorthms are employed on a server, ths parameter ndcates dsk I/O traffc reducton. Usng SRB or PSRB algorthms, a clent needs to lsten to multple channels for the maxmal sharng of the cached data n the proxy s memory. We measure the traffc between the proxy and the clent n terms of average clent channel requrement. Ths s an averaged number of channels the clents are lstenng to durng the sessons. Snce the clents are lstenng to earler on-gong sessons, storage s needed at the clent to buffer the data before ts presentaton. We use the average clent storage requrement n percentage of the full sze of the meda object to ndcate the storage requrement on the clent sde. If a sesson termnates before t reaches the end of the requested meda object, t s possble that the clent has already downloaded future part of the meda stream whch s no longer needed. To characterze ths wasted delvery from proxy to the clent, we record average clent waste durng the smulaton. It s the percentage of wasted bytes versus the averaged total prefetched data. The effectveness of the algorthms s studed by smulatng dfferent scale factors for the allocaton of the ntal buffer sze and varyng memory cache capactes. The streamng rate s assumed to be constant for smplcty. The smulatons are conducted on a HP workstaton x4, wth GHz CPU and GB memory, runnng Lnux Redhat 7.. For each smulaton, we compare a set of seven algorthms n three groups. The frst group contans bufferng schemes whch nclude the runnng buffer cachng and the nterval cachng. The second group contans patchng algorthms, specfcally the greedy patchng, the grace patchng and the optmal patchng. The thrd group contans the two shared runnng buffer algorthms proposed n ths paper. 3.. Performance Results Frst, we evaluate the cachng performance wth respect to the ntal buffer sze. Wth a fxed memory capacty of GB, the ntal buffer sze vares from to /3 of the length of meda objects. For each scale factor, the ntal buffer of dfferent szes s allocated f the length of the meda object s dfferent. The server traffc reducton,theaverage clent channel requrement and the average clent storage requrement are recorded n the smulaton. The results are plotted n Fgure 4 and Fgure 5. Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE

7 Bandwdth Reducton (%) RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB /Scale Average Clent Channel Requrement RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB /Scale Fgure 4. REAL: (a) Bandwdth Reducton and (b) Average Clent Channel Requrement wth GB Memory Average Clent Storage Requrement (%) RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB /Scale Average Clent Waste (%) RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB /Scale Fgure 5. REAL: (a) Average Clent Storage Requrement(%) and (b) Clent Waste(%) wth GB Memory Fgure 4(a) shows the server traffc reducton acheved by each algorthm. Notce that PSRB acheves the best traffc reducton. As expected, the performance of the three patchng algorthms does not depends on the scale factor for allocatng the ntal buffer. Nether does that of the nterval cachng snce the nterval cachng allocates buffers based on access ntervals. The changes of scale factor have a sgnfcant mpact on the performance of the proposed SRB and PSRB algorthms, especally when the scale factor s /8, /6 or /3. Ths s due to the burst nature of the accesses logged n the workload and the trade-off between the number of runnng buffers and the szes of runnng buffers. A larger buffer mples that more requests can be served from the proxy buffer. However, a larger buffer also ndcates that less memory space s left for other requests. Ths n turn leads to a larger number of server accesses snce there s no avalable memory. On the other hand, a smaller buffer may serve a smaller number of requests but t leaves more memory space for the system to allocate for other requests. Despte of these performance fluctuatons, we can stll see that PSRB and SRB acheve hgher traffc reducton rates from Fgure 4. The result concludes that PSRB uses 6% of the clent channel to acheve 5% hgher traffc reducton than the optmal patchng as shown n Fgure 4(b). Fgure 5(a) shows the average storage requrement on the clent. PSRB allows the sesson sharng even when memory space s not avalable. It s therefore expected that PSRB acheves the hghest rate of server traffc rate reducton. In the mean tme, t also requres the largest clent sde storage. On the other hand, SRB acheves about 4% less traffc reducton averagely, but the requrement on clent channel and storage s sgnfcantly lower. Fgure 5(b) shows that the clent sde wastes for PSRB Bandwdth Reducton (%) RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB Memory Cache Sze (Gbytes) Average Clent Channel Requrement RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB Memory Cache Sze (Gbytes) Fgure 6. REAL: (a) Bandwdth Reducton and (b) Average Clent Channel Requrement wth the Scale of /4 and SRB are about 33% and 5% respectvely, compared to % for the nterval cachng. Snce the wasted bytes are not counted as hts, ths leads to the lowered traffc reducton rate for PSRB and SRB. From another perspectve, even wth the waste, PSRB and SRB stll can acheve better performance than other technques. Settng the ntal buffer sze as /4 of the requested meda object, we agan evaluate the cachng performance wth the ncreasng amount of the avalable proxy memory. Fgure 6 and Fgure 7 show the server traffc reducton rate and the clent sde statstcs respectvely. Fgure 6(a) shows that dstances between the traffc reducton curves of PSRB, SRB and the nterval cachng become much smaller n general. Ths renforces the observaton that PSRB and SRB have more waste due to the partal vewng nature. In addton, the grace patchng achevng al- Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE

8 Average Clent Storage Requrement (%) RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB Memory Cache Sze (Gbytes) Average Clent Waste (%) RB Cachng Interval Cachng SRB Cachng Greedy Patchng Grace Patchng Optmal Patchng Patchng SRB Memory Cache Sze (Gbytes) Fgure 7. REAL: (a) Average Clent Storage Requrement(%) and (b) Clent Waste(%) wth the Scale of /4 most no traffc reducton shows ts ncapablty n dealng wth the partal vewng stuaton. Fgure 6 and Fgure 7 also show a flat gan when the memory capacty ncreases. It seems to ndcate that the memory capacty s a mnor factor. Once agan, the burst nature of the request arrval may play a role here. In addton, the volume of the burst may also be low whch leads to the fact that a lmted amount of memory space suffces the sharng of sessons. 4. Concluson In ths paper, we propose two new algorthms for effcently delverng streamng meda objects. Shared Runnng Buffers (SRB) cachng algorthm s proposed to dynamcally cache meda objects n the proxy memory durng the delvery. Patchng SRB (PSRB) algorthm s proposed to further enhance the memory utlzaton n the proxy. Our algorthms can adaptvely allocate the memory buffer by consderng the user access pattern, and enable the data beng fully shared among dfferent buffers. Extensve smulatons are conducted to evaluate these algorthms. The smulaton results demonstrate the effcency acheved by the proposed algorthms. Both algorthms requre the clent capable of lstenng to multple channels at the same tme. Compared wth prevous solutons whch also requre multple clent channels, the proposed algorthms acheve hgher server traffc reducton rate wth less or smlar load on the lnk between the proxy and the clent. References [] E. Bommaah, K. Guo, M. Hofmann, and S. Paul. Desgn and mplementaton of a cachng system for streamng meda over the nternet. In Proceedngs of IEEE Real Tme Technology and Applcatons Symposum, May. [] S. Chen, B. Shen, S. Basu, and Y. Yan. Srb:the shared runnng buffer based proxy cachng of streamng sessons. In Hewlett-Packard Laboratores Tech. Report, 3. [3] S. Chen, B. Shen, S. Wee, and X. Zhang. Adaptve and lazy segmentaton based proxy cachng for streamng meda delvery. In Proceedngs of ACM Workshop on Network and Operatng System Support for Dgtal Audo and Vdeo (NOSSDAV), June 3. [4] A. Dan and D. Staram. Buffer management polcy for an on-demand vdeo server. In IBM Research Report 9347, 993. [5] A. Dan and D. Staram. A generalzed nterval cachng polcy for mxed nteractve and long vdeo workloads. In Proceedngs of Multmeda Computng and Networkng, Jan [6] A. Dan, D. Staram, and P. Shahabuddn. Schedulng polces for an on-demand vdeo server wth batchng. In Proceedngs of ACM Multmeda, Oct [7] D. L. Eager, M. C. Ferrs, and M. K. Vernon. Optmzed regonal cachng for on-demand data delvery. In Proceedngs of Multmeda Computng and Networkng, Jan [8] L. Gao and D. Towsley. Supplyng nstantaneous vdeo-ondemand servces usng controlled multcast. In Proceedngs of IEEE Internatonal Conference on Multmeda Computng and Systems, June, 999. [9] K. A. Hua, Y. Ca, and S. Sheu. Patchng : A multcast technque for true vdeo-on-demand servces. In Proceedngs of ACM Multmeda, Sept [] S. Lee, W. Ma, and B. Shen. An nteractve vdeo delvery and cachng system usng vdeo summarzaton. In Computer Communcatons, volume 5, pages , March. [] R. Rejae, M. Handley, H. Yu, and D. Estrn. Proxy cachng mechansm for multmeda playback streams n the nternet. In Proceedngs of Web Cachng Workshop, March 999. [] S. Sen, L. Gao, J. Rexford, and D. Towsley. Optmal patchng schemes for effcent multmeda streamng. In Proceedngs of ACM Workshop on Network and Operatng System Support for Dgtal Audo and Vdeo (NOSSDAV), June 999. [3] S. Sen, J. Rexford, and D. Towsley. Proxy prefx cachng for multmeda streams. In Proceedngs of IEEE INFOCOM, March 999. [4] K. Wu, P. S. Yu, and J. Wolf. Segment-based proxy cachng of multmeda streams. In Proceedngs of WWW, Sept.. Acknowledgments We apprecate the constructve comments from the anonymous referees. We also thank Mtch Trott and Suse Wee of HP Laboratores for ther comments and suggestons on ths work. Proceedngs of the 4th Internatonal Conference on Dstrbuted Computng Systems (ICDCS 4) /4 $. 4 IEEE