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The Impact of Soft Resource Allocation on n-tier Application Scalability Qingyang Wang, Simon Malkowski, Yasuhiko Kanemasa, Deepal Jayasinghe, Pengcheng.

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Presentation on theme: "The Impact of Soft Resource Allocation on n-tier Application Scalability Qingyang Wang, Simon Malkowski, Yasuhiko Kanemasa, Deepal Jayasinghe, Pengcheng."— Presentation transcript:

1 The Impact of Soft Resource Allocation on n-tier Application Scalability Qingyang Wang, Simon Malkowski, Yasuhiko Kanemasa, Deepal Jayasinghe, Pengcheng Xiong, Motoyuki Kawaba, Lilian Harada, Calton Pu

2 22 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Outline  Background & Motivation  Background  Motivational experiment  Performance Impact of Soft Resource Allocation  Over-allocation of soft resources  Under-allocation of soft resources  Special case of under-allocation  Solution  A practical algorithm for good soft resource allocation  Conclusion & Future Works

3 33 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Cloud Computing Environment Good performance + Cost efficiency  Scaling applications on demand High throughput + low response time High resource utilization

4 44  Soft resources in n-tier systems  Threads, database connections, TCP connections, locks, etc. Soft Resource Allocation 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Is it okay to duplicate the same configuration of soft resource allocation?

5 55 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Outline  Background & Motivation  Background  Motivational experiment  Performance Impact of Soft Resource Allocation  Over-allocation of soft resources  Under-allocation of soft resources  Special case of under-allocation  Solution  A practical algorithm for good soft resource allocation  Conclusion & Future Works

6 66  RUBBoS benchmark  Bulletin board system like Slashdot (www.slashdot.org)www.slashdot.org  Typical 3-tier or 4-tier architecture  Two types of workload  Browsing only  Read/Write mix  24 web interactions  C-JDBC  Middleware for database scale-out  Read: act as a load-balancer  Write: send a request to all databases to keep consistency Experimental Environment (1) 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011

7 77  Emulab (http://www.emulab.net)  Relatively modest testbed originally for network research  Virtual network & physical machines (not VM) Experimental Environment (2) 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 HardwareSpecifications Server typePC3000 in Emulab ProcessorXeon 3GHz 64bit Memory2GB Network1Gbps Disk2 x 146GB 10,000rpm

8 88  Software setups Experimental Environment (3) 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 FunctionSoftware Web serverApache Application serverApache Tomcat DB clustering middlewareC-JDBC Database serverMySQL a JavaSun jdk1.6.0_14 Operating systemRedhat FC4 System MonitorSysstat 7.0.2

9 99  Notation Experimental Environment (4) 25th IEEE International Parallel & Distributed Processing Symposium 19 May / 3 / 1 / 2 configuration

10 10 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Result of Motivational Experiment Scale out

11 11 Hardware configuration 2 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Challenge Hardware configuration Soft resource allocation Hardware configuration 1 Soft resource allocation 1 Thread pool, DB connection pool Thread pool, DB connection pool Soft resource allocation 2 Good performance Bad performance Good performance Scale out How to choose a reasonable soft resource allocation to match the hardware configuration?

12 12  Evaluate two important soft resources  Threads  Database connections  Show their performance impact on n-tier applications  Over-allocation & under-allocation cases  Special case of under-allocation  Introduce a practical way to choose a reasonable allocation of soft resources Focus of This Paper 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011

13 13 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Outline  Background & Motivation  Background  Motivational experiment  Performance Impact of Soft Resource Allocation  Over-allocation of soft resources  Under-allocation of soft resources  Special case of under-allocation  Solution  A practical algorithm for good soft resource allocation  Conclusion & Future Works

14 14 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Performance Loss due to Soft Resource Over-allocation (1) Sensitivity analysis: change DB Connection pool size in Tomcat

15 15 25th IEEE International Parallel & Distributed Processing Symposium 19 May Performance degradation Goodput 1/4/1/4CPU utilization in CJDBC Throughput with response time boundary Performance Loss due to Soft Resource Over-allocation (2) High allocation of DB connections in Tomcat degrades the system performance

16 16 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 JVM Garbage Collection Costs Over-allocation of soft resources causes waste of critical hardware resources % more time used for GC over experimental time JVM Garbage Collection in CJDBC

17 17 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Outline  Background & Motivation  Background  Motivational experiment  Performance Impact of Soft Resource Allocation  Over-allocation of soft resources  Under-allocation of soft resources  Special case of under-allocation  Solution  A practical algorithm for good soft resource allocation  Conclusion & Future Works

18 18 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Performance Loss due to Soft Resource Under-allocation (1) Sensitivity analysis: change thread pool size in Tomcat

19 th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Performance Loss due to Soft Resource Under-allocation (2) Goodput 1/2/1/ CPU utilization of Tomcat 20 6 Under-allocation of soft resources causes inefficient utilization of hardware resources

20 20 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Outline  Background & Motivation  Background  Motivational experiment  Performance Impact of Soft Resource Allocation  Over-allocation of soft resources  Under-allocation of soft resources  Special case of under-allocation  Solution  A practical algorithm for good soft resource allocation  Conclusion & Future Works

21 21 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Special Case of Soft Resource Under- allocation Sensitivity analysis: change thread pool size in Apache

22 th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Performance Loss due to Under- allocation of Apache Threads Goodput 1/4/1/4 CPU utilization in CJDBC Low allocation of Apache threads degrades the system performance

23 23 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Non-Trivial Correlation between Apache and Tomcat Threads (1) > 6 * 4 Why are 30 threads in Apache not enough?

24 24 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Non-Trivial Correlation between Apache and Tomcat Threads (2) Waiting for TCP FIN reply from the client

25 25 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Non-Trivial Correlation between Apache and Tomcat Threads (3) The long waiting time for FIN reply from clients is unpredictable and frequently happens under high workload Waiting for TCP FIN reply from client

26 26 Concurrency for Concurrency for Large number of soft resources in front tier acts as a buffer providing stable workload for lower tiers 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Concurrency of Apache Threads Connecting to Tomcat

27 27 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Summary of Experiments 1.Over-allocation of soft resources causes waste of critical hardware resources 2.Under-allocation of soft resources causes inefficient utilization of hardware resources 3.Large number of soft resources in front tier acts as a buffer providing stable workload for downstream tiers

28 28 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Outline  Background & Motivation  Background  Motivational experiment  Performance Impact of Soft Resource Allocation  Over-allocation of soft resources  Under-allocation of soft resources  Special case of under-allocation  Solution  A practical algorithm for good soft resource allocation  Conclusion & Future Works

29 29 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Soft Resource Allocation Algorithm  Key idea: allocating soft resources globally to utilize the critical hardware resource as efficiently as possible

30 30 1. Identifying the critical hardware resource first Soft Resource Allocation Algorithm (1) 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 (1) Bottleneck server

31 31 1. Identifying the critical hardware resource first 2. Allocating proper soft resources for the bottleneck server Soft Resource Allocation Algorithm (2) 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Throughput knee Minimum Saturation workload (2) Ave. number of active threads (1) Bottleneck server

32 32 (3) Dependency between current tier and bottleneck tier 1. Identifying the critical hardware resource first 2. Allocating proper soft resources for the bottleneck server 3. Allocating proper amount soft resources in other tiers Soft Resource Allocation Algorithm (3) 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 (2) Ave. number of active threads (1) Bottleneck server

33 33 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Outline  Background & Motivation  Background  Motivational experiment  Performance Impact of Soft Resource Allocation  Over-allocation of soft resources  Under-allocation of soft resources  Special case of under-allocation  Solution  A practical algorithm for good soft resource allocation  Conclusion & Future Works

34 34 Achieving good performance by scaling n-tier applications in Cloud requires a unified exploration of both hardware and software Contributions:  We showed allocation of soft resources has a big impact on the total performance of an N-tier system  We showed to decide a proper soft-resources allocation is a complex problem, especially in cloud environments which requires dynamic scaling-out/in  We gave a practical algorithm for proper soft resource allocation 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Conclusion

35 35 25th IEEE International Parallel & Distributed Processing Symposium 19 May 2011 Future Work  Explore more soft resources such as locks, buffer/queue  Explore more efficient ways to find proper soft resource allocation  Explore the impact of soft resource allocation in virtualized environment

36 Thank You. Any Questions? Qingyang Wang


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