Cluster-Aware Cache for Network Attached Storage *

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1 Cluter-Aware Cache for Network Attached Storage * Bin Cai, Changheng Xie, and Qiang Cao National Storage Sytem Laboratory, Department of Computer Science, Huazhong Univerity of Science and Technology, Potfach , Wuhan, P.R. China hut_caibin@ohu.com Abtract. Decentralized, cooperative and large-cale ditributed torage ytem that conit of a cluter of torage node attached with local dik can deliver high reource utilization, high availability and eay calability. Thi paper decribe the deign and prototype implementation of a novel Cluter-Aware Cache (CAC) algorithm that hare memorie between node in cluter to contruct an efficient and cooperative cache-to-dik accee policy. The difference between our cheme and previou tudie i that procee on different node can acce the ame page concurrently. Furthermore, CAC algorithm i alo well uited to heterogeneou cluter where one or more node may have larger amount of memory than the other. The performance meaurement with a Web erver on our ytem how dramatic performance improvement with increaing number of node. 1 Introduction Large-cale ditributed torage ytem that conit of a cluter of torage node with local dik have become a cot-effective olution for wide range of application, ranging form enterprie-cla torage backend, HPC (High-Performance Computing) to data mining and Internet ervice. Such ytem can be realized at little or no extra cot, can offer an inherently calable aggregate I/O bandwidth, and can take advantage of exiting cluter intallation through double-ue or upgrade of older hardware. Although the parallelim offered by the numerou dik in a cluter can alleviate the I/O bandwidth problem, it doe not really addre the latency iue which i largely limited by eek and rotational cot. Caching data block in memory i a well known way of reducing I/O latencie, provided we can achieve good hit ratio. In thi paper, we decribe the deign of a torage cluter uing inexpenive PC equipped with local dik. In our ytem, large file are tored in a calable fahion by triping the data acro multiple node to obtain high aggregate bandwidth. In order to olve the dik latency iue, we preent the deign and prototype implementation of a novel Cluter-Aware Cache (CAC) cheme, which change the cache hierarchy of traditional ditributed ytem (client cache, erver cache, erver dik) by letting one node cache mie to be checked againt other node cache before the local torage * Thi reearch i upported by National 973 Great Reearch Project of P.R. China under the grant No. 2004CB and National Natural Science Foundation under grant No and No H. Jin, D. Reed, and W. Jiang (Ed.): NPC 2005, LNCS 3779, pp , IFIP International Federation for Information Proceing 2005

2 364 B. Cai, C. Xie, and Q. Cao device. Thu, the working et can grow beyond the local memory limit while application read latency can be alleviated tremendouly becaue remote cache were acceed fater over high-peed network than the dik even if it i local. The remainder of the article i organized a follow: In ection2, we decribe the related work about cooperative caching cheme. In ection3, we introduce the architecture of our torage cluter ytem, and detail the CAC cheme in ection 4. The experimental reult are evaluated at ection 5. The concluion come at ection 6. 2 Related Work Uing regular node a torage node ha previouly been uggeted in the Slice [1,2] and OPIOM [3] project, but where they primarily focu on uing dedicated torage node, we examine the poibilitie for ditributing the load acro all node in a cluter. The Network Block Device (NBD) [4] and GNBD/VIA [5] alo provide network acce to a remote block device, but the architecture are neither modular nor extenible. The xfs [6,7] introduced the notion of cooperative caching. Other I/O buffer cache management cheme exit on global memory management and cooperative caching [8] by extending the ue of a hared ditributed buffering mechanim to the I/O device themelve. PACA [9] i another cooperative file ytem cache. It attempt to avoid replication and the aociated conitency mechanim by allowing only one cached block copy in the entire cluter-wide cache. That i poible ince PACA ue a memory copy mechanim (a ort of Remote DMA) to end the data from the cache to the uer memory. However, every data acce ha to go through thi memory copy mechanim which i clearly much lower than acceing a local block copy. Other low level approache to remote I/O include Swarm [10] and Network- Attached Secure Dik (NASD) [11]. Swarm offer the torage abtraction of a triped log while NASD provide an object-oriented interface. 3 Sytem Architecture In thi ection, we decribe the main component of NAS torage cluter ytem and how they work together. We firt provide an overview of the architecture, and then we cover the CAC algorithm in more detail. The phyical layout of uch torage cluter i hown in figure 1. To provide an interface of a ingle virtual cluter erver, each cluter i aigned with a multicat IP addre. All participating cluter member joint in thi multicat group, whoe IP addre i known to each other. The main advantage of NAS approach i that internally the deign can eamlely integrate major torage component to work cloely together. All member in thi ytem work collaboratively to contruct a torage ytem with a unified torage pace. Each of the torage device member in the cluter run a program, called daemon. Daemon communicate with each other and provide ome function, including tranferring file data, tranferring control meage, and performing tatitical information. When a node need to get file at other node, the daemon find the file firtly, and then get the file from remote node. Daemon check uage of the CAC at a fixed interval

3 Cluter-Aware Cache for Network Attached Storage 365 in order to provide reaonable cache replacement policy. When a node reidual cache capacity i le than the threhold value, the daemon will move ome block from it local cache to the remote cache in order to balance the load. Fig. 1. Architecture of NAS Storage Cluter Fig. 2. Daemon and CAC Kernel Module Each of the torage device member in the cluter alo ha a kernel module. It divide the node total memory into two part: one i the node local cache; the remainder memory at each node therefore make of the CAC cache pace. The typical etup and poible cenario are hown in figure 2. CAC hide the ditributed nature of the cluter node cache by offering the local hot an interface to a global unified buffer cache. Similar to GMS [8], CAC ue a high-level abtraction (dik block) to deal with remote reource and cooperative cache algorithm to jointly manage the cluter cache. It rely on the low communication latencie of powerful interconnect to minimize block acce time. 4 Implementation of CAC Scheme Each node ha a local cache to cater to the individual proce requet at that node; and upon a mi goe to a hared cooperative cache running on one or more node of the cluter which can poible atify requet that come from different node. 4.1 Local Cache We opted to implement the local cache within the Linux kernel that can be hared acro all the procee running on that node. Only when the requet mie in thi cache (either all or ome of the requet cannot be atified locally), i an external requet initiated out of that node to the cooperative cache. Thi cache i implemented uing open hahing with econd chance LRU replacement. There i a dirty lit, a free lit, and a buffer hah to chain ued block for fater retrieval and acce. The hahing function take a parameter the inode number of the file and the block number to

4 366 B. Cai, C. Xie, and Q. Cao index the buffer hah table. There are two kernel thread called fluher and harveter in the implementation. Write are normally non-blocking (except the ync write explained later), and the fluher periodically propagate dirty block to the cooperative cache. The harveter i invoked whenever the number of block in the free lit fall below a low water mark, upon which it free up block till the free lit exceed a high water mark. A block ize of 4K byte i ued in our implementation. Note that uch a kernel implementation automatically allow multiple application/procee to hare thi local cache, thu making more effective ue of phyical memory. 4.2 Global Unified Cache The cooperative cache, a explained earlier, add one more level to the torage hierarchy before the dik at one node to be acceed, and we go over it in the following dicuion, explaining the bae algorithm in our implementation. Currently, we ue a eparate cooperative cache for each file. If there i little file haring acro application, or even acro parallel procee of the ame application, then the requet would automatically ditribute the load more evenly with thi approach. Since we would alo like to be able to perform inter-application optimization baed on haring pattern, we have opted to hare the cooperative cache acro application. Thi can help one application benefit from the data brought in earlier by another from the cache. Thi feature i one key difference between our ytem and GMS [8] where the global cache i intended for optimization within the procee of a ingle application. Similar to the local cache implementation, we implement the cooperative cache within the Linux kernel. The internal data tructure and activitie of the cooperative cache are more or le imilar with thoe for the local cache that were decribed earlier. One could deignate uch global cache on different node, particularly on thoe node with larger phyical memory (DRAM). Conequently, thi architecture i alo well uited to heterogeneou cluter where one or more node may have larger amount of memory than the other. The bae algorithm of CAC i decribed in following peudo-code: Application iue file requet; if (file i at local cache){ give the file to application; return; if (file i at remote cache){ repeat-remote: ue Daemon Communication to fetch the file; if ( the file i hot){ repeat-local: if (local cache ha pace){ add the file to local cache; give the file to application; return; give the file to application; return;

5 Cluter-Aware Cache for Network Attached Storage 367 give the file to application; return; if (file i at local torage device){ goto repeat-local; if (file i at remote torage device){ goto repeat-remote; can not find the file; return error; 4.3 Daemon Communication Each node run a uer-level daemon program for the purpoe of tranferring file data, tranferring control meage, and performing tatitical information. TCP/IP ocket are being explicitly ued for ending meage to it from the individual local cache regardle of which application proce i making a call. The convenience and flexibility of a uer-level implementation ha led u to implement the daemon running on each node of our cluter erving requet to a pecific file running on a cluter node, to which explicit requet are ent by the local cache, and i hared by different application. When a node need to get file at other node, the daemon find the file firtly, and then get the file from remote node. Daemon check uage of the CAC at a fixed interval in order to provide reaonable cache replacement policy. When a node reidual cache capacity i le than the threhold value, the daemon will move ome block from it local cache to the remote cache in order to balance the load. The proce of communication between daemon and CAC i preented a following peudo-code: wakeup (Daemon Communication); if (available CAC cache ize < threhold_ CAC _ize){ dicard ome block; // replacement policy leep; if (available local cache ize < threhold_local_ize){ find the node with more available cache pace; migrate the block to that node; leep; leep;

6 368 B. Cai, C. Xie, and Q. Cao 5 Experimental Reult In thi ection, we preent an evaluation of the performance of the CAC prototype. The performance goal of CAC i to have a performance cloe to that of local cache and to have a mall overhead on the node hoting the dik. For the purpoe of our experiment, we contructed a mall cluter with five equivalent Pentium4/2GHz PC with 256MB DRAM running Linux operating ytem with the verion of the 2.4 kernel. Each PC wa equipped with a ingle Gigabit network card a well a a ingle 160G IDE hard dik to provide torage pace. No pecial kernel optimization were done to optimize I/O or inter-proce communication. One node wa dedicated to ervicing HTTP requet and the other four node were available to ervice data torage. Each node wa running a daemon and a CAC kernel module, and hared 128MB RAM to conit of cooperative cache, therefore, the cooperative cache cache capacity i 640MB. Each client wa a Window PC running the WebBench [12] uite of e-commerce tet. WebBench i a benchmark program that meaure the performance of Web erver uing PC client. In our tet, the file et wa 1.5GB and wa placed on the dik of Web erver initially, and we ued 10 client running WebBench to generate 1000 WebBench-client requet to Web erver imultaneouly. The experiment were done according to the requet and cache hit ratio, irrepectively. A comparion between remote dik, local dik, remote cache, and local cache in term of the number of requet operation i preented in figure 3. Notice that Web erver performance upgrade fat with the increaing number of the node. Large part of requet hitting in Web erver local cache improve the I/O performance of Web erver dramatically. Similar comparion in term of requet byte i preented in figure 5. A comparion between cache hit ratio in term of the number of requet operation i preented in figure 4. Notice that I/O in Web erver local dik degrade fat Web erver throughput Hit Ratio remote dik local dik remote cache remote cache local dik local cache 600 local cache total requet ) d n o c e 400 / r e b m 300 u n ( t e 200 u q e r 60 ) 50 ( % tio 40 r a it h node number node number Fig. 3. The Comparion of Requet Number Fig. 4 The Comparion of Hit Ratio

7 Cluter-Aware Cache for Network Attached Storage ) d n o c e / e t y B ( d a e R 5000 Web erver throughput (Byte) remote dik local dik remote cache local cache total requet ) ( % tio 40 r a it h Hit Ratio (Byte) remote cache local dik local cache node number node number Fig. 5. The Comparion of Requet Byte Fig. 6. The Comparion of Hit Ratio with the increaing number of the node, large part of requet hitting in Web erver local cache or remote cache improve the Web erver I/O performance. Similar comparion in term of requet byte i preented in figure 6. 6 Concluion By leveraging the high-peed communication afforded by the cluter interconnect uch a Fat/Gigabit Ethernet, large file can be tored in a calable fahion by triping the data acro multiple node; by ditributing the dik acro a ufficient number of cluter node, high aggregate bandwidth can be eaily obtained with current hardware. In order to olve the dik latency iue, we preent the deign and prototype implementation of a novel cluter caching cheme, which change the cache hierarchy of traditional ditributed ytem (client cache, erver cache, erver dik) by letting one node cache mie to be checked againt other node cache before the local torage device. Thu, the working et can grow beyond the local memory limit while application read latency can be alleviated tremendouly becaue remote cache were acceed fater over high-peed network than the dik even if it i local. Performance meaurement of uch a ytem are encouraging, howing that the I/O performance of Web erver improve fat with the increaing number of node. Reference 1. D.C.Anderon, J.Chae, and A.Vadat, Interpoed requet routing for calable network torage, Proceeding of the 4 th Sympoium on Operating Sytem Deign and Implementation, October J.Chae, D.Anderon, A.Gallatin, A.Lebeck, and K.Yocum, Network I/O with trapeze Proceeding of 1999 Hot Interconnect Sympoium, Augut P.Geoffray, OPIOM: Off-proceor I/O with myrinet, Proceeding of the firt ACM/IEEE International Sympoium on Cluter Computing and Grid, May 2001.

8 370 B. Cai, C. Xie, and Q. Cao 4. P.T.Breuer, A.M.Lopez, and A.G.Are, The network block device, Linux Journal, (73), May K.Kim, J.Kim. and S.Jung, BNBD/VIA: A network block device over virtual interface architecture on Linux, Proceeding of the 16 th International Parallel and Ditributed Proceing Sympoium, April M.Dahlin, R.Yang, T.Anderon, and D.Patteron, Cooperative Caching: Uing remote client m emory to improve file ytem performance, Proceeding of firt Sympoium on Operating Sytem Deign and Implementation, November T.Anderon, M.Dahlin, J.M.Neefe, D.Patteron, D.Roeli, and R.Y.Wang, Serverle network file ytem, Proceeding of the 15 th Sympoium on Operating Sytem Principle, December M.I.Feeley, W.E.Morgan, F.H.Pighin, A.R.Karlin, and H.M.Levy, Implementing global memory management in a worktation cluter, Proceeding of the 15 th ACM Sympoium on Operating Sytem Principle, pp , December T.Corte, S.Girona, and L.Labatra, PACA: A ditributed file ytem cache for parallel machine. Performance under Unix-like workload, Technical Report UPC-DAC-RR- 95/20 or UPC-CEPBA-RR-95/13, Department d Arquitectura de Computador, Univerittat Politecnica de Catalunya, J.H.Hartman, I.Murdock, and T.Spalink, The Swarm calable torage ytem, Proceeding of the 19 th IEEE International Conference on Ditributed Computing Sytem (ICDCS 99), June G.A.Gibon, D.F.Nagle, K.Amiri, F.W.Chang, H.Gobioff, E.Riedel, D.Rochberg, and J.Zelenka, File ytem for network-attached ecure dik, Technical Report CMU-CS , School of Computer Science, Carnegie Mellon Univerity, Pittburgh, PA , July

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