Chapter 3: Dynamic Performance Provisioning with

Transcription

1 Chapter 3: Dynamic Performance Provisioning with Storage Virtualization About the space provisioning and performance provisioning introducing above, one of the problem is they can't provide enough performance as need automatically. So if is a environment that the workload may be changed rapidly at different time, the traditional provisioning system have to be prepared enough and works at all time even there are almost no work at all. So there is a big cost. For this reason, we propose a new method named dynamic performance provisioning to solve this problem The Idea We want to propose one method that would provide enough performance even in the case like Figure 3-1. So we propose dynamic performance provisioning as Figure 3-2. Figure 3-1:Performance Provisioning for Workload Changing

2 Figure 3-2: The Review of Dynamic Performance Provisioning When it is low workload, the logical storage is constituted by allotting some disk that would provide enough performance, and the conditional disk is just free to reduce management cost. When the workload becomes high and the present disks can't afford the high workload like the marked place of Figure 3-1, the conditional disks wake up to have work. The new work come to the conditional disks first, the using the way of copy-on-write, the conditional disk allot the work to present disks to provide good performance. When the workload comes down again and the conditional disks are not needed, the new work is allotted to the original disks, and the conditional disks are cleared using segment cleaning. Then the conditional disks go to sleep again. During the segment cleaning, there will be overhead of course, but it may be ignored for it happen at low workload. 3.2 The Basic Structure The Basic Structure is constructed by IO conversion system,conversion list

3 Figure 3-3: The Design of Dynamic Performance Provisioning (Meta information) and segment cleaning system as shown in Figure 3-3. If the user send IO request to storage virtualization system, the IO request information has to be changed to the IO information used in storage pool for operation, so IO conversion system works for that. The conversion list is the information converse IO information. for the above IO conversion system to The segment cleaning system is for segment cleaning when move from high workload to low workload.

4 Chapter 4: Evaluation 4.1 Evaluation Environment For the evaluation, the evaluation way with kernel-land LVM and the evaluation way with in-band virtualization server are proposed. In this paper, we used the half evaluation with user-land LVM like Figure 4-1. Figure 4-1: Evaluation on Dynamic Performance Provisioning In this evaluation Implementation userland LVM Application (get IO trace, and input user-land LVM) 1.DB (TPC-C) 2.File System (PostMark) 3.Benchmark (SPC) Difficulty

5 1. Need LFS Function (Write, reference, segment cleaning) coding 2. Some difficulty during implementation 4.2 IO Trace-based Experiments In this experiment, we use carefully implemented IO replayer and real IO trace to qualify the effectiveness of dynamic performance provisioning IO Replayer This IO replayer is constituted by mult-thread. The IO trace file is read by IO Play thread, then the Execution thread gets the IO information as IO trace file. And the Execution thread executes IO. And the same time, the Conversion table is referred. The IO referring is changed as the table to execute the IO trace in normal volume or extended volume. To get the function of reduction, there is also reorganization thread in the trace replayer. Figure 4-2: Software Structure of Trace Replayer

6 4.3 Implementation Data In this paper, we use the trace data getting from HP as Figure 4-2 and Figure 4-3. Figure 4-3: The review of the Trace Data for Evaluation 1 Figure 4-4: The review of the Trace Data for Evaluation 2 49

7 Figure 4-5:The review of the Trace Data for Evaluation 3 Figure4-5 shows the cello99 data. Green points mean write and red points mean read. The horizontal axis means time and the whole graph is a whole day data. The vertical axis means the logical disk space and we can know the whole logical disk space is about 73 GB from this graph. In cello99 data, there is about months data of several logical disks. We use the data as showing in the picture. 4.4 Evaluation Result The Virtualization Cost In the evaluation, we find it will take about 5 `20 us for reading and 50 `80 us for writing. So it is much lower overhead than IO execution time, and the time is not changed largely with executing different IO number.

8 And about the conversion table size, there is about 350K records after executing 10M IOs. So it is absolutely able to be controlled in main memory Extension effects Figure 4-6: The Extension effects 1 51

9 Figure 4-7: The extension effects 2 With 4-6 and 4-7, we can find comparing with normal method, the response time of the method proposed by us is much shorter and the throughput is much larger. So from the data, we could prove the effeteness.

10 Autonomic Low Reorganization Priority-based Chapter 5: Conclusion and Future Research Dynamic performance provisioning Future High extension effects achieved virtualization overhead confirmed impacts examined work IO scheduling between normal IOs and reorg. IOs control of volume extension and reduction 53

11 Reference [1] Masaru Kitsuregawa, Chapter 1,"Storage Networking" [6] Cltharine Van Ingen."Fun with Numbers: Storage Provisioning" [8] [9] M. Rosenblum, J. K. Ousterhout. The Design and Implementation of a Log-Structured File System. ACM Trans. Comp. Syst. 10(1) 1992 J. Menon. A performance comparison RAID-5 and log-structured arrays. IEEE Symp. on High-Performance Distributed Computing W. Wang, Y.Zhao, R. Bunt. HyLog: A High Performance Approach to Managing Disk Layout. USENIX FAST 2004 [12] VERITAS Software Corporation,"Storage Virtualization White Paper" May 2001 K. Goda, T. Tamura, M. Oguchi and M. Kitsuregawa,"Run-time Load Balancing System on SANconnected PC Cluster for Dynamic Injection of CPU and Disk Resource-A Case Study of Data Mining Application-," Proc. 13th Intl. Conf. on Database and Expert Systems Applications, pp , Aixen- Provence, France, Sept Xusheng Tian and Chunagyi Ji."Bounding the Performance of Dynamic Channel Allocation with Qos Provisioning for Distributed Admission Control in Wirreless Networks".--- IEEE Transactions on Vehicular Technology, Vol50, NO.2, March 2001 [17] Oracle Corporation."Task Automation Performance Monitoring Dynamic Provisioning" A. Capone, J. Elias, F.Martignon, GPujolle."Distributed Dynamic Bandwidth Provisiong in Quality of Service Networks" [19] Per B. Hansen."High performance data networks"- ADVA Optical Networking igrid 2005 Ramu Ramamurthy, Zbigniew Bogdanowicz, Shahrokh Samieian, Debanjan Saha, Bala Rajagopalan, Sudipta Sengupta, Sid Chaudhuri,, Krishna Bala."Capacity Performance of Dynamic Provisioning in Optical Networks".- Journal of Lightwave technology, Vol.19, N0.1, January 2001 Fei Cao, Barrett R, Bayan,Shih-His Liu, Wei Zhao,"A Non-Invasive Approach to Dynamic Web Services Provisioning"--- IEEE International Conference on Web Services(ICWS'05) PP [22] Tony Asaro,"Thin Provisioning---Focus on Compellent Dynamic Capacity", ESG Bhuvan Urgaonkar, Prashant Shenoy, Abhishek Chandra, Pawan Goyal,"Dynamic Provisioning of Multi-tier Internet Applications". Wu Feng, Nageswara S. Rao, William R. Wing"DOE Workshop on Ultra High-Speed Transport Protocols and Dynamic Provisioning for Large Scale Science Applications" 54