分散ストレージシステム (4) (5) (6) 書き込み 書き込み 読み出し 読み出し (2) コーディネータ 1 Fig. 1 Image of distributed storage system. 2 Fig. 2 Process flow of ( 1 ) ( 2 ) ( 3 )
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1 key-value store Application of Load Balancing Mechanism with Considering Data Access Frequency to Daisuke Kawakami, 1 Toshihiro Matsui, 1 Shoichi Saito, 1 Tomoaki Tsumura 1 and Hiroshi Matsuo 1 is the distributed key-value storage system with high availability and responsibility. But it doesn t consider the difference of data access frequency well. Therefore, we applied the dynamic load balancing mechanism with considering data access frequency to to balance the load of each node. In the result, we confirmed the increase of data access efficiency under the condition of unbalanced data access occurring. 1 Nagoya Institute of Technology 1. Farsite 1) Google file system 2) 1 3) key-value store key-value key-value ) 5) 1 c 2009 Information Processing Society of Japan
2 分散ストレージシステム (4) (5) (6) 書き込み 書き込み 読み出し 読み出し (2) コーディネータ 1 Fig. 1 Image of distributed storage system. 2 Fig. 2 Process flow of ( 1 ) ( 2 ) ( 3 ) ( 4 ) ( 5 ) ( 6 ) c 2009 Information Processing Society of Japan
3 B C2 B3 A1 B2 A トークン B1 A2 C3 C C1 A3 キー コーディネータ =A プリファレンスリスト ={A, C, B (N = 3) 3 Fig. 3 Determination of coordinator and preference list. 1, 2, A 3 A N N C 1 C 3 C 3 B 2 B 3.3 R W R W R W 3 c 2009 Information Processing Society of Japan
4 不整合データのベクタクロック {N1, 2, {N1, 1, {N1, 2, {N1, 2, {N1, 3, {N1, 2, {N1, 3, {N1, 3, , {N2, 1, {N1, 2, , {N2, 1, {N1, 2, , {N3, 1, 解決後データのベクタクロック {N1, 2, {N1, 2, 解決不可 ( ユーザ依存 ) {N1, 3, , {N2, 1, 解決不可 ( ユーザ依存 ) 5. {X, Y, Z = { コーディネータ, コーディネート数, 最近コーディネート時のタイムスタンプ 4 Fig. 4 Resolution of inconsistency data with vector clock DAB-(Data Access Balanced ) 1 5 MaxNode MinNode Threshold MaxNode Threshold 4 c 2009 Information Processing Society of Japan
5 sort( ); MaxNode = max( ). ; MinNode = min( ). ; Threshold = (MaxNode. - MinNode. ) / 2; foreach(node =. ) { sort(node. ) foreach(token = Node.. ) { if(token. + TotalLoad < Threshold) { TotalLoad = TotalLoad + Token. ; Token ; if( ) { break; if( ) { MinNode ; Fig. 5 5 Algorithm of making load balancing information. MinNode 2 6 N 1 N N 1 名 N1 N2 N3 N4 全の負荷情報 最大負荷 = N1 最小負荷 = N3 総コーディネート数 N1 の詳細負荷情報 トークンコーディネート数 閾値 = ( 最大総コーディネート数 最小総コーディネート数 ) / 2 = 986 負荷分散対象トークンリスト ( 合計コーディネート数 < 986) = {34, 45 Fig. 6 6 Example of determination of load balancing target = 972 < N 3 7 ( 1 ) ( 2 ) 5 c 2009 Information Processing Society of Japan
6 変更先 Table 1 1 Experimentation environment. 代表 CPU Intel Pentium 4 3.0GHz 2GB LAN Ethernet(100Mbps) Erlang 7) ver (2) (1) 変更元 7 Fig. 7 Mechanism of avoidance of data inconsistency. 2 Table 2 Experimentation condition (32 8 ) 5000/ ( : =2:1) MD5( 32 ) / ( 3 ) ( 4 ) 6. DAB :1 1 / Kai 6) c 2009 Information Processing Society of Japan
7 Table 3 3 Experimentation result (execution time). DAB (4096) 12% 11 DAB 数トー 2000 ネィデーコ1000 均平 0 DAB ( 秒 ) 8 Fig. 8 Number of average process requests (balanced request). 1 数ト0.8 ーネィデ0.6 ー ) コ大 0.4 / 最均 0.2 ( 平 0 DAB ( 秒 ) 9 Fig. 9 Average load balance (balanced request). DAB- 7. key-value store 3000 数トー 2000 ネィデーコ1000 均平 0 DAB ( 秒 ) 1 数ト0.8 ーネィデ0.6 ー ) コ大 0.4 / 最均 0.2 ( 平 0 DAB ( 秒 ) 10 Fig. 10 Number of average process requests (balanced request). 11 Fig. 11 Average load balance (balanced request). 7 c 2009 Information Processing Society of Japan
8 1) Adya, A., Bolosky, W.J., Castro, M., Cermak, G., Chaiken, R., Douceur, J.R., Howell, J., Lorch, J.R., Theimer, M. and Wattenhofer, R.P.: FARSITE: Federated, available, and reliable storage for an incompletely trusted environment, In Proceedings of the 5th Symposium on Operating Systems Design and Implementation (OSDI), pp.1 14 (2002). 2) Ghemawat, S., Gobioff, H. and Leung, S.-T.: The Google File System, In Proceedings of the Nineteenth ACM Symposium on Operating Systems Principles (SOSP), pp (2003). 3) Hastorun, D., Jampani, M., Kakulapati, G., Pilchin, A., Sivasubramanian, S., Vosshall, P. and Vogels, W.: : amazon s highly available key-value store, Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles, ACM, pp (2007). 4) Karger, D., Lehman, E., Leighton, T., Levine, M., Lewin, D. and Panigrahy, R.: Consistent hashing and random trees: Distributed caching protocols for relieving hot spots on the World Wide Web, In ACM Symposium on Theory of Computing, pp (1997). 5) Lamport, L.: Time, clocks, and the ordering of events in a distributed system, Commun. ACM, Vol.21, No.7, pp (1978). 6) Kai. kai.html. 7) Armstrong, J.: Making reliable distributed systems in the presence of hardware errors, PhD Thesis, The Royal Institute of Technology Stockholm, Sweden (2003). 8 c 2009 Information Processing Society of Japan
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