Harmonic Placement: File System Support for Scalable Streaming of Layer Encoded Object

Transcription

1 Harmonc Placement: Fle System Support for Scalable Streamng of Layer Encoded Obect Sooyong Kang Department of Computer Scence Educaton Hanyang Unv., Seoul, , Korea Youp Won Seunghyun Roh Dept. of Electrcal & Computer Engneerng Hanyang Unv., Seoul, , Korea {ywon ABSTRACT From fle system s pont of vew, scalable streamng ntroduces another dmenson of complexty n ds schedulng. Ths s partcularly because when a subset of nformaton s retreved, the playbac does not necessarly concdes wth the sequental access. We propose a new fle organzaton technque called Harmonc placement. The basc dea s to cluster the frequently accessed layers together. We develop elaborate analytcal models for dfferent fle organzaton technques: Progressve placement, Interleaved placement and Harmonc placement. We nvestgate the performance of fle organzaton technques under varyng worload condtons. The models developed n ths wor enables us to predct the performance and effcency of the storage system n scalable streamng envronment. We fnd that the Harmonc placement outperforms other schemes n scalable streamng envronment. Key Words: Fle System, Multmeda, Layered Encodng, Scalable Streamng 1. INTRODUCTION Compresson technology and networ transport technology have made sgnfcant advancement to effcently provde multmeda servce over dynamcally changng user bandwdth avalablty. These technque brng greater flexblty n content management and save greater amount of storage space. In storage subsystem s aspect, numerous technques have been proposed to effcently support real-tme multmeda I/O, e.g. ds schedulng, buffer cache management, dedcated fle system for multmeda applcaton, load balancng and etc. To effectvely handle heterogenety n networ bandwdth and hardware capablty of clent termnals, a number of compresson schemes have been proposed[5, 7]. For a gven bandwdth budget, t s mportant to select rght set of layers n transmttng layer encoded obect. A number of wors proposed layer selecton schemes under uncast and multcast set- Correspondng Author. Permsson to mae dgtal or hard copes of all or part of ths wor for personal or classroom use s granted wthout fee provded that copes are not made or dstrbuted for proft or commercal advantage and that copes bear ths notce and the full ctaton on the frst page. To copy otherwse, to republsh, to post on s or to redstrbute to lsts, requres pror specfc permsson and/or a fee. NOSSDAV 6 Newport, Rhode Island USA Copyrght 26 ACM /6/5...$5.. tng[2, 1, 9, 1, 11]. Scalable streamng and layered encodng s an effectve soluton n vdeo streamng for wreless envronment[12, 3, 6]. Whle the above mentoned wors well cover the ssue of real-tme multmeda streamng n networ, compresson, or fle system area, the effcent support of layered streamng from fle system s perspectve s yet to be answered. In ths wor, we am at fllng out the chasm between fle system technology and scalable streamng technology of layer encoded content. We carefully conecture that the placement of data bloc n scalable encodng needs to be treated dfferently from the legacy multmeda contents. When the fle s encoded n scalable fashon, and playbac rate dynamcally changes, the noton of sequental playbac does not necessarly concde wth sequental access on the fle data blocs. Hence, scalable encodng scheme ntroduces another dmenson of complexty from fle system pont of vew. Legacy fle system model and ds schedulng strategy does not ncorporate ths characterstcs. Dal up ISDN Cable modem ADSL VDSL Contents farm 6 Web Clent connected to the nternet usng cable modem 1. Intal access to web 2. Web page contanng contents lst 3. Selected content request 4. Networ speed test Fgure 1: Servce Model 5. Redrect to cable modem 6. Content request to the redrected Fg. 1 llustrates the underlyng servce envronment. User can access the content va wde varety of dfferent networ medum whose bandwdth capablty vares wdely. To effectvely cope wth the varety n connecton medum, content provdng system conssts of a number of s and each s dedcated to harbor the contents for a gven bandwdth connecton. Once the connecton speed of the ncomng request s determned, the ncomng request s drected to the approprate and s servced from the respectve. In ths wor, we propose a fle organzaton technque called Harmonc placement. The contrbuton of ther wor n two fold. Frst, we developed an elaborate model for fle system

2 technque. It s mportant that we have accurate model to predct the performance of a fle system under a gven worload. Second, we found that harmonc nterleavng actually yelds the most desrable performance aganst the exstng fle organzaton technques. We examne the performance of a number of dfferent fle organzaton technques. We compare the result obtaned from our performance model and the result from the physcal experment. The result from these two sources well match each other and the harmonc nterleavng exhbt superor performance under legacy streamng servce envronment. 2. FILE ORGANIZATION TECHNIQUES We vew a meda fle as a collecton of logcal storage unts, called segment. A segment can be a frame or group of pctures. We assume that the amount of data read n a round (or perod s determned based on the Constant Tme Length (CTL scheme. We examne three dfferent fle organzaton technque: Progressve placement, Interleaved placement, and Harmonc placement. Progressve placement strategy clusters the data blocs n a layer together. Ths allocaton strategy manfests tself when networ bandwdth avalablty s very lmted and when the streamng can transport the lowest layers n most of the tme. Progressve placement scheme entals sgnfcant ds head movement overhead when the transports larger numbers of layers. We call the frame-maor placement scheme as Inter-leaved placement. Ths s plan sequental placement. When the streamng retreves data blocs n all layers, ds access yelds sequental access pattern not only from a logcal aspect but also from a physcal aspect. When the transports only the proper subset of layers, ether fle access entals undesrable see operaton or needs to dscard some of the retreved nformaton. Interleaved placement scheme manfests tself when the transports most of the layers. The Progressve placement and Interleaved placement strateges can be thought as two extremes n a wde spectrum of fle organzaton technques. In practce, the networ bandwdth avalablty vares wdely. Also, the speed of the clent connecton vares from a few hundreds Kbts/sec (e.g. W-CDMA to hundreds of Mbts/sec. Data placement strategy should be carefully desgned so that t can effcently support a wde varety of QoS requrements. We beleve that nether Progressve Placement nor Interleaved Placement strategy s desrable from the perspectve of fle system effcency. In ths study, we propose a novel fle organzaton strategy, Harmonc Placement. Fg. 2 llustrates the fle organzaton under the Harmonc placement strategy. Seg 1 Seg 2 Seg m Layer low+1 Layer low+2 Layer l !!... """ ### $$$ %%%... && '' (( *** !! """ ### $$$ %%% && '' (( *** +++ Lower Layers Layer 1 Layer 2 Layer low Seg 1 Seg 2 Seg m Upper Layers Seg 1 -- // Layer low+1 Layer low+2 Layer l Seg 2 Seg m Fgure 2: Harmonc Placement: In the fgure, low means the number of lower layers n the obect. In Harmonc placement, the layers are parttoned nto two groups: a set of lower layers and a set of upper layers. For example, wth fve layers, the layers can be parttoned as Notaton B R l T(x r N L o L N L o L N o N N w z Descrpton maxmum ds bandwdth (MBytes/sec length of a round length (sec number of layers tme to see x cylnders data rate of layer total number of sessons sze of the obect n number of cylnders sze of layer n number of cylnders number of sessons accessng layer n a round sze of obect n number of cylnders sze of layer of obect n number of cylnders total number of obects number of sessons accessng obect number of sessons accessng layer of obect ndex of the frst obect accessed n a round ndex of the last obect accessed n a round Table 1: Notatons {L 1, L 2, L 3 } and {L 4, L 5 }. In ths case, we assume that upto layer 3 are frequently requested and layer 4 and layer 5 are less frequently accessed. Harmonc Placement adopts Progressve Placement for nter-group placement and Interleaved Placement for ntra-group placement. Usng ths scheme, we can reduce ds see tme by clusterng the frequently accessed layers together. Hence, when only lower layers are accessed n most of the tme and nformaton n the upper layers s rarely used, ths scheme outperforms the other schemes. However, f the upper layers are accessed frequently, the ds see overhead can result n lower performance. Therefore, layers needs to be carefully parttoned by consderng both networ bandwdth and the clent devce. The effectveness of Harmonc placement s subect to the layer parttonng polcy and the varablty n networ bandwdth avalablty. 3. MODELING THE FILE SYSTEM 3.1 Bacground Developng a fle system performance model for a gven worload s very challengng tas. In generc multmeda servce envronment, t s common that a harbors multple vdeo fles and a number of clents access these contents n On-Demand fashon. We develop analytcal performance model for ndvdual placement scheme for ths streamng envronment. We use Ds Operaton Effcency as a performance metrc for T fle system. Ds Operaton Effcency s defned as read, T read +T overhead where T read and T overhead corresponds to data transfer tme and the ds overhead whch ncludes see tme, rotatonal latency, command queueng and etc. Table 1 shows notatons used n ths wor. There exst multple vdeo obects n the storage and multple sessons are accessng them. Sesson n ths paper refers to only ds retreval sesson and does not nclude the playbac from the buffered contents. At any gven tme nstance, each sesson accesses dfferent porton of an obect or dfferent obect. Before defnng see overhead model for each scheme, we frst develop the common data read tme model. Snce the total amount of data that should be read n the round s N o l =1 =1 r R N, we can model the tme to transfer data blocs read from No =1 l=1 r R N B. the ds as T read = To establsh the see overhead model, we categorze sees

3 nto ntra-obect see, nter-obect see and return see. Intra-obect see occurs n an obect whle readng data blocs n dfferent segments or layers, nter-obect see occurs after readng the last necessary data bloc n an obect and gong forth to the frst necessary data bloc n the next obect and the return see s a see from the last bloc n a round to the frst bloc of the next round. In the rest of the paper, we call the ntra-obect see as ntra see and the nter-obect see as nter see. Let us model the nter-see dstance frst. Assumng that we are accessng obect and obect n sequental fashon, the nter-see dstance between obect and obect conssts of three components. The frst component, dstance A, s the see from the last read bloc of obect to the end of obect. The second component, dstance B, s the see dstance to sp the obects between obect and. The thrd component, dstance C, s the see dstance from the begnnng of obect to the frst data bloc to be read n obect. For convenence, let us nclude dstance C to the ntra see model and hence we can only consder dstance A and dstance B for nter see overhead model. Let the last-read cylnder of an obect be the cylnder where the last bloc read n the obect locates. Then, the dstance A of an obect becomes the dstance between the last-read cylnder to the last cylnder of the obect. Assumng obect resdes between obect and obect, the dstance B can be thought of as the dstance A of obect regardng the frst cylnder of the obect as the last-read cylnder of the obect. Therefore, we can model the nter see overhead n per obect base wth only dstance A. Let denote the dstance between the frst cylnder of the obect and the last-read cylnder of the obect. Then, the dstance A of each obect can be calculated as the sze of the obect subtractng. Assume that the popularty of each obect s the same. Let w and z be the ndces of the frst and the last obect accessed n a round, respectvely. Then the expected values of w and z correspond to N o N+1 and No N+1 N, respectvely. The dstance of return see can be approxmated as the sum of the dstance from the frst cylnder of obect w to the last cylnder of obect z 1, z 1 L o, and of obect z (Fg. 3. sum of the sze of obects from obect w to obect z 1 of obect z last read cylnder n obect z obect w 1 obect w obect z obect z+1 return see dstance Fgure 3: The return see dstance 3.2 Progressve Placement Scheme Progressve placement scheme clusters the data blocs n the same layer together and the number of sees for layer of obect n a round corresponds to the number of sessons but cannot exceed the number of cylnders occuped by the respectve layer. Therefore, the number of sees can be represented as mn{l, N }. the total number of ntra-layer sees corresponds to l =1 mn{l, N }. The average dstance of n- dvdual sees corresponds to L mn{l,n }+1. After readng all requested data blocs n a layer, ds head moves to the approprate cylnder n the next layer(nter-layer see. The overhead of ntra see to read data blocs n layer of obect, T ntra,, can be modeled as T ntra, = T ( L mn{n +1,L mn{n, L }. The total ntra see overhead n obect becomes l =1 T. ntra, To calculate, we frst defne P as the probablty that the last accessed bloc of obect belongs to the layer, assumng that N >. Then, P = N N +1. If the last data bloc belongs N to the layer, the average value of, δ, becomes 1 =1 L + L N +1 N (Fg. 4. frst cylnder of obect layer 1 Hence, the expected value of n obect L 1+ L L 1 L N N + 1 the last sesson n layer layer layer +1 last read cylnder Fgure 4: The value of n obect n the Progressve placement scheme becomes E[δ ] = ( ( l =1 P L N +1 N + 1. =1 L Also, f the last accessed bloc of obect belongs to the layer, the dstance A becomes d, A = l =1 L ( 1 =1 L + L N +1 N = l =+1 L +(L L N +1 N l =+1 L + L, n average. The expected value +1 N of dstance A n obect, E[d, A ], can be computed as l =1 P ( L + l N +1 =+1 L. Hence, the expected nter see overhead n obect can be represented as T( E[d, ]. When A N = and =, we can regard the frst cylnder of the obect as the last-read cylnder of the obect. Hence, the dstance A s the sze of obect, L o, and the nter see overhead becomes T(L o. Combnng those two cases, we can represent the nter see overhead n obect, T as n Eq. 1. nter T nter = { T( E[d, A ] f N > T(L o f N = Fnally, the sum of all ntra see overheads and nter see overheads n each obect n a round can be represented as z l =1 T + z 1 ntra, T. Snce the dstance of the return nter see s approxmated as the sum of the dstance from the frst cylnder of obect w to the last cylnder of obect z 1, z 1 L o, and n obect z, the average return see overhead can be calculated as T ( z 1 L o + E[δ]. Fnally, the overall see overhead of Progressve scheme n a round can be modeled as n Eq. 2. z l z 1 z 1 T overhead = T ntra, + T nter + T L o + E[δ ] (2 =1 3.3 Interleaved Placement Scheme In Interleaved placement scheme, data blocs n the same segment are clustered together. The ntra see dstance manly depends on the nterval between two adacent sessons. Average nterval between two adacent sessons accessng the same } (1

4 sesson 1 S1 S2 S3 sesson N 1 sesson N Lo Lo Lo N +1 N +1 N +1 average nterval between two adacent sessons Slast Fgure 5: The value of n obect n the Interleaved placement scheme obect depends both on the sze of the fle and the number of concurrent sessons. To compute the worst case see tme behavor, we assume that the access poston of ndvdual playbacs are evenly dstrbuted. Snce see tme profle s convex functon, gven a total see dstance, total see tme s maxmzed when the all sees are of the same dstance. The average ntra see dstance n obect can be calculated smply as L o. The number of sees n a round usng Interleaved N +1 placement scheme s mn{n, L o }. Therefore, the total ntra see overhead durng readng data blocs of obect, T, can be ntra calculated as T (( = T L o mn{n, L ntra mn{n +1,L o}. The value o } of n obect can be calculated as L o N +1 N (Fg. 5. Hence, the dstance A for nter see n obect becomes L o L o N +1 N and the nter see overhead, T, can be calculated as T nter ( L = T nter o L o N +1 N. Therefore, the total see overhead n obect, sum of the ntra see overhead and nter see overhead, s T + ntra T. The return see dstance nter of Interleaved placement scheme s the sum of the value of n obect z and the sum of obect szes from obect w to obect z 1. Hence, the return see overhead of Interleaved placement scheme s T ( z 1 L o + Lz o N z +1 Nz. Puttng all together, the total see overhead of Interleaved placement scheme can be modeled as n Eq. 3. z z 1 z 1 T overhead = T ntra + T nter + T L L z o o + N z + 1 Nz (3 3.4 Harmonc Placement Scheme In Harmonc placement schemes, the layers are parttoned nto two groups, namely, lower and upper layer. We apply dfferent placement scheme for each of lower layers and upper layers. Ths s prmarly to explot the access frequency and access pattern of the respectve layers. Interleaved placement scheme s used for placng the nformaton n lower layers and Progressve scheme s used n placng the nformaton n upper layers. See behavor for lower and upper layer accesses wll be smlar to the see behavor of the Interleaved and progressve placement scheme. Let low and L be the lower number of lower layers and the number of cylnders that data blocs belongng to the lower layers n obect are stored, respectvely. Then L = low lower =1 L. The ntra see overhead that occurs n lower layer of obect, T, can be calculated, n a smlar fashon to that of Interleaved placement scheme, as T ntra,low ( = T L lower ntra,low mn{n +1,L lower } mn{n, L }. Also, the ntra see overhead that occurs n upper layer of obect, T ntra,, can be calculated, n a smlar lower fash- on to that of Progressve scheme, as T ( = T L ntra, mn{n +1,L } mn{n, L }. The total ntra see overheads that occur n all upper layers of obect becomes l =low+1 T ntra,. Assume that N >. Then, the last data bloc read n a round n an obect belongs to ether lower layers or upper layers. When t belongs to the lower layers, of an obect wll be smlar to that of the Interleaved placement scheme. If t belongs to the upper layers, can be obtaned n smlar fashon to the Progressve scheme. The average value of of obect of Harmonc scheme becomes E[δ ] = low =1 P L lower N +1 N + l =low+1 P L N +1 N + 1 =1 L. When the last-read cylnder belongs to the lower layer, the dstance A of obect for nter see becomes d, = A L o low =1 L lower N +1 N low =1 ( L o L lower N +1 N. When the last-read cylnder of obect belongs to the upper layer, t becomes d, = A L o l =low+1 L =1 L l =low+1( L + N +1 l =+1 L. Hence, the expected length of dstance A for nter see n obect becomes E[d, ] = low A =1 P ( L o L lower N +1 N + l =low+1 P ( L + l N +1 =+1 L. When N =, = and dstance N +1 N + 1 A becomes L o. Therefore, the nter see overhead n obect of Harmonc scheme, T, can be calculated as n Eq. 4. nter T nter = { T ( E[d, A ] f N > T(L o f N = Hence, the total see overhead n obect, sum of the ntra see overhead and nter see overhead, s T + l ntra,low =low+1 T + ntra,, and summng up all of them of each obect, we can get the T nter total see overhead n a round except the return see overhead as n ( z T + l ntra,low =low+1 T ntra, + z 1 T. nter The return see dstance of Harmonc scheme s the sum of the value of of obect z and the sum of obect szes from obect w to obect z 1. Hence, the return see overhead of Harmonc scheme s formulated as T ( z 1 L o + E[δz]. Puttng all together, the total see overhead of Harmonc scheme n a round can be modeled as n Eq. 5. T overhead = z ( T ntra,low + l =low+1 T ntra, (4 + z 1 T nter + T ( z 1 L o + E[δz ] (5 4. PERFORMANCE ANALYSIS 4.1 Experment Setup Our experment manly focus on two ssues. Frst, we le to verfy the accuracy of the analytcal models developed n ths wor. Second, more mportantly, we examne the performance of the ndvdual placement schemes. The networ bandwdth avalablty trace s obtaned va networ smulator, NS. Our networ topology has dumbbell settng. In our networ settng, a sngle s servcng multmeda streamng clents usng RAP(Rate Adaptve Protocol[8]. The and the clent s connected va one ln. To smulate the actual networ envronment, we ntroduce ten ftp sessons whch share the ln. There are ten ftp nodes and ten ftp clent nodes. Each and clent par

5 forms a sngle sesson. In our smulaton, we use four dfferent bottlenec ln bandwdths: 2.6 Mbts/sec, 7.7 Mbts/sec, 15.4 Mbts/sec and 3 Mbts/sec. Each of the bottlenec ln bandwdths are chosen to represent typcal subscrber lne bandwdth capacty: ISDN(128 Kbts/sec, or dfferent speed DSL(or Cable Modem subscrptons(384 Kbts/sec, 768 Kbts/sec and 1.5 Mbts/sec. And the layer sze ncreases exponentally as the layer ndex ncreases[4]. Hence, when we use Harmonc placement scheme, a that provdes streamng servces to clents whose subscrber lne bandwdth s 128 Kbps may store multmeda obects puttng only layer 1 nto the lower layers set and other layers nto the upper layers set. In ths case, the Harmonc placement scheme becomes exactly the same as the Progressve placement scheme. A that serves clents whose subscrber lne bandwdth s 384 Kbps may put layer 1 and layer 2 nto the lower layers set and layer 3 and layer 4 nto the upper layers set. A that serves clents whose subscrber lne bandwdth s 768 Kbps may put layer 1, layer 2 and layer 3 nto the lower layers set and only layer 4 nto the upper layers set. Fnally, a that serves clents whose subscrber lne bandwdth s 1.5 Mbps may store multmeda obects puttng all layers nto the lower layers set. In ths case, the Harmonc placement scheme becomes exactly the same as the Interleavng placement scheme. In ths way, usng Harmonc placement scheme, four dfferent nds of s that store multmeda obects n four dfferent ways provde streamng servce to four groups of clents whose subscrber lne bandwdth s dfferent each other. Snce large scale ISPs (Internet Servce Provders that provdes streamng servce to clents operate more than tens of homogeneous streamng s n general, they can use Harmonc placement scheme only through reformng the homogeneous farm nto the heterogeneous farm wthout addtonal hardware cost. We can verfy the effectveness of three placement strateges under dfferent clent bandwdth capablty. Usng the bandwdth avalablty trace, we generate layer access patterns for ndvdual clents and subsequently a sequence of I/O requests on the streamng. Wth ths I/O trace, we examne the ds utlzaton. Ds utlzaton s obtaned va two dfferent ways: analytcal model and physcal experment. Wth a gven I/O sequence, we can compute the ds overhead and ds transfer tme usng the models developed n ths wor. We also measure the behavor of the ds subsystem. 4.2 Experment Results Fg. 6 shows the results of analytcal models and physcal experments under three placement schemes. There are thrty concurrent sessons accessng ten vdeo obects. They are unformly dstrbuted. In physcal experment, we found that hard ds drve wth Progressve placement s saturated under thrty concurrent sessons (1.5 Mbts/sec subscrber lne capacty. Subsequent experment s based upon the worload generated by thrty sessons. 1 As can be seen n Fg. 6, the ds operaton effcency obtaned from the analytcal models are very close to the results obtaned from physcal experments. Among three schemes, the Harmonc placement scheme shows the best performance n all subscrber lne capactes. When the subscrber lne bandwdth s relatvely small, the Progressve placement scheme 1 Actually, the ds operaton effcency of each scheme becomes larger when the number of sessons are larger than 3. We only shows a snapshot of effcency spectrum n Fg. 6. Ds Operaton Effcency(% Harmonc-Model Harmonc-Experment Progressve-Model Progressve-Experment Interleaved-Model Interleaved-Experment 128 Kbps 376 Kbps 768 Kbps Subscrber Lne Bandwdth 1.5 Mbps Fgure 6: Ds operaton effcency of ndvdual placement schemes: analytcal model and physcal experment: 3 concurrent sessons accessng dfferent obects wth unform probablty shows better performance than the Interleaved placement scheme. Snce, n the Progressve placement scheme, data blocs n the same layer are stored contguously, the average see dstance s smaller than that n the Interleaved placement scheme when the subscrber lne bandwdth s 128 Kbps, where only layer 1 data blocs are read, or 384 Kbps, where only layer 1 and layer 2 data blocs are read. On the other hands, when the subscrber lne bandwdth s relatvely large, the Progressve placement scheme generates more number of sees than Interleaved placement scheme and the dstance of the ndvdual sees ncreases as well. The Interleaved placement scheme stores data blocs of all layers n the same segment contguously. Therefore, as the subscrber lne bandwdth becomes larger, the Interleaved placement scheme shows better performance than the Progressve placement scheme. The Harmonc placement scheme contguously stores data blocs that are supposed to be read contguously n each subscrber lne bandwdth. Hence, the Harmonc placement scheme always outperforms the other schemes. Fg. 7 shows the ds operaton effcency under varyng number of subscrbers. The number of sessons vares from 5 to 3. As we can see from all fgures, the Harmonc placement scheme shows better ds operaton effcency regardless of the number of sessons. As the number of sessons ncreases, not only the ds operaton effcency of each scheme ncreases but also the dfference of ds operaton effcency among each scheme ncreases. When the subscrber lne bandwdth s 128 Kbps, the Progressve placement scheme outperforms Interleaved placement scheme and n other cases the Interleaved placement scheme outperforms the Progressve scheme. Fg. 8 shows the maxmum number of concurrent sessons n ndvdual placement schemes. When the subscrber lne bandwdth s small(128kbts/sec, Harmonc and Progressve Placement scheme yeld the best performance. Ths s because only fracton of the obects are accessed due to bandwdth lmtaton. On the other hand, when the subscrber lne bandwdth s suffcent(1.5 Mbts/sec, Interleaved and harmonc placement yeld the best performance. When the subscrber lne bandwdth s large, relatvely sgnfcant fracton of the fle s accessed and therefore sequental playbac on a fle yelds

6 Ds Operaton Effcency(% Subscrber lne B/W = 128 Kbps Interleaved Harmonc(=Progressve Ds Operaton Effcency(% Interleaved Progressve Harmonc Subscrber lne B/W = 768 Kbps Ds Operaton Effcency(% Subscrber lne B/W = 1.5 Mbps Harmonc(=Interleaved Progressve Number of Sessons Number of Sessons Number of Sessons Fgure 7: Ds operaton effcency of each placement scheme accordng to the number of smultaneous sessons Number of Sessons Kbps 376 Kbps Interleaved Progressve Harmonc 768 Kbps Subscrber Lne Bandwdth 1.5 Mbps Fgure 8: Maxmum number of sessons almost sequental ds access. It s worth notng that the dfferences among the ndvdual placement strateges become more sgnfcant under low subscrber lne bandwdth. In fact, ths phenomenon confrmed by the analytcal model as well as physcal experment put forth an mportant sgn n placement strategy. When a may have to servce large number of low bandwdth sessons, specal care needs to be taen to properly partton the set of layers and to use harmonc placement strategy. The Interleaved placement scheme should be avoded especally when we are to provde low-qualty vdeo streamng servce or musc streamng servce to clents. 5. CONCLUSION In ths wor, we am at fllng up the chasm between the fle system technology and scalable streamng technology. Our thess n ths paper s on f t s possble to support scalable streamng n more effcent fashon from fle system s pont of vew. We propose novel fle organzaton, Harmonc Placement. Harmonc Placement clusters the frequently accessed layers together. We develop elaborate performance models for three fle organzaton schemes whch effectvely capture the fle system behavor. The accuracy of the model s confrmed va physcal experment. To examne the performance of the gven placement schemes, we physcally measure the ds utlzaton behavor and also compute the ds utlzaton usng the analytcal model developed n ths wor. The result obtaned from the physcal experment and the analytcal model le wthn very close proxmty. It s found that n all cases, Harmonc placement exhbts the best performance. The result of our wor provdes mportant gudance on streamng plannng and storage management. 6. REFERENCES [1] A. Bal, M. Gerla, D. Maggorn, and M. Sanadd. Adaptve vdeo streamng: pre-encoded mpeg-4 wth bandwdth scalng. Computer Networs, 44: , 24. [2] P. de Cuetos and K. W. Ross. Adaptve rate control for streamng stored fne-graned scalable vdeo. In Proceedngs of the 12th nternatonal worshop on Networ and operatng systems support for dgtal audo and vdeo, pages ACM Press, 22. [3] F. Ftze, P. Seelng, and M. Resslen. Vdeo streamng n wreless nternet. Wreless Internet: Technologes and Applcatons Seres: Electrcal Engneerng and Appled Sgnal Processng Seres, 24. [4] R. N. Inc. Helx producer user s gude, June 22. [5] W. L. Overvew of Fne Granularty Scalablty n MPEG-4 Vdeo Standard. IEEE Trans. on Crcuts and Systems for Vdeo Technology, 11(3, March 21. [6] J. Lu, B. L, Y. T. Hou, and I. Chlamtac. On optmal layerng and banwdth allocaton for multsesson vdeo broadcastng. IEEE Trans. on Wreless Communcaton, 3(2: , March 24. [7] H. M. Radha, M. van der Schaar, and Y. Chen. The mpeg-4 fne-graned scalable vdeo codng method for multmeda streamng over p. IEEE Trans. on Multmeda, 3(1:53 58, March 21. [8] R. Reae, M. Handely, and D. Estrn. Rap: An end-to-end rate-based congeston control mechansm for realtme streams n the nternet. In Proceedngs of IEEE Infocom, pages , New Yor, NY, USA, March [9] R. Reae and A. Ortega. Pals: Peer-to-peer adaptve layered streamng. In Proceedngs of Networ and Operatng System Support for Dgtal Audo and Vdeo, Monterey, CA. USA, June 23. [1] S. ryong Kang, Y. Zhang, M. Da, and D. Logunov. Mult-layer actve queue management and congeston control for scalable vdeo streamng. In Proceedngs of the 24th Internatonal Conference on Dstrbuted Computng Systems(ICDCS 4, 24. [11] D. Saparlla and K. W. Ross. Optmal streamng of layered vdeo. In Proceedngs of IEEE INFOCOM, 2. [12] D. Wu, Y. T. Hou, and Y.-Q. Zhang. Scalable vdeo codng and transport over broad-band wreless networs. Proceedngs of IEEE, 89(1:6 15, Jan 21.