skip to main content
research-article
Public Access

Performance and Cost Considerations for Providing Geo-Elasticity in Database Clouds

Published:18 December 2017Publication History
Skip Abstract Section

Abstract

Online applications that serve global workload have become a norm and those applications are experiencing not only temporal but also spatial workload variations. In addition, more applications are hosting their backend tiers separately for benefits such as ease of management. To provision for such applications, traditional elasticity approaches that only consider temporal workload dynamics and assume well-provisioned backends are insufficient. Instead, in this article, we propose a new type of provisioning mechanisms—geo-elasticity, by utilizing distributed clouds with different locations. Centered on this idea, we build a system called DBScale that tracks geographic variations in the workload to dynamically provision database replicas at different cloud locations across the globe. Our geo-elastic provisioning approach comprises a regression-based model that infers database query workload from spatially distributed front-end workload, a two-node open queueing network model that estimates the capacity of databases serving both CPU and I/O-intensive query workloads and greedy algorithms for selecting best cloud locations based on latency and cost. We implement a prototype of our DBScale system on Amazon EC2’s distributed cloud. Our experiments with our prototype show up to a 66% improvement in response time when compared to local elasticity approaches.

References

  1. Daniel Abadi. 2012. Consistency tradeoffs in modern distributed database system design: CAP is only part of the story. Computer 45, 2 (Feb. 2012), 37--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Sharad Agarwal, John Dunagan, Navendu Jain, Stefan Saroiu, Alec Wolman, and Harbinder Bhogan. 2010. Volley: Automated data placement for geo-distributed cloud services. In Proceedings of the Conference on Networked Systems Design and Implementation (NSDI’10). 17--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Amazon Global Infrastructure 2016. Amazon Global Infrastructure. Retrieved from http://aws.amazon.com/about-aws/global-infrastructure/.Google ScholarGoogle Scholar
  4. Amazon Route 53 2015. Amazon Route 53: Choosing a Routing Policy. Retrieved from http://docs.aws.amazon.com/Route53/latest/DeveloperGuide/routing-policy.html.Google ScholarGoogle Scholar
  5. Yair Amir, Claudiu Danilov, Michal Miskin-Amir, Jonathan Stanton, and Ciprian Tutu. 2003. On the Performance of Consistent Wide-area Database Replication. Technical Report.Google ScholarGoogle Scholar
  6. Martin F. Arlitt and Carey L. Williamson. 1997. Internet web servers: Workload characterization and performance implications. IEEE/ACM Transactions on Networking 5, 5 (1997), 631--645. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Robert Birke, Lydia Y. Chen, and Evgenia Smirni. 2012. Usage patterns in multi-tenant data centers: A temporal perspective. In Proceedings of the 2015 IEEE International Conference on Autonomic Computing (ICAC’12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. George Edward Pelham Box and Gwilym Jenkins. 1990. Time Series Analysis, Forecasting and Control. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. O. J. Boxma, R. D. van der Mei, J. A. C. Resing, and K. M. C. van Wingerden. 2005. Sojourn time approximations in a two-node queueing network. In Proceedings of the International Trade Commission (ITC’05).Google ScholarGoogle Scholar
  10. G. Casale, Ningfang Mi, L. Cherkasova, and E. Smirni. 2012. Dealing with burstiness in multi-tier applications: Models and their parameterization. IEEE Transactions on Software Engineering 38, 5 (2012), 1040--1053. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Emmanuel Cecchet, Rahul Singh, Upendra Sharma, and Prashant Shenoy. 2011. Dolly: Virtualization-driven database provisioning for the cloud. In Proceedings of the Conference on Virtual Execution Environments (VEE’11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Ludmila Cherkasova and Rob Gardner. 2005. Measuring CPU overhead for I/O processing in the xen virtual machine monitor. In Proceedings of the Annual Technical Conference (ATEC’05). Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Ron C. Chiang and H. Howie Huang. 2011. TRACON: Interference-aware scheduling for data-intensive applications in virtualized environments. In Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis. ACM, 47. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Cisco Global Cloud Index 2016. Cisco Global Cloud Index:Forecast and Methodology, 2015--2020. Retrieved from http://www.cisco.com/c/dam/en/us/solutions/collateral/service-provider/global-cloud-index-gci/white-paper-c11-738085.pdf.Google ScholarGoogle Scholar
  15. James C. Corbett, Jeffrey Dean, Michael Epstein, Andrew Fikes, Christopher Frost, J. J. Furman, Sanjay Ghemawat, Andrey Gubarev, Christopher Heiser, Peter Hochschild, Wilson Hsieh, Sebastian Kanthak, Eugene Kogan, Hongyi Li, Alexander Lloyd, Sergey Melnik, David Mwaura, David Nagle, Sean Quinlan, Rajesh Rao, Lindsay Rolig, Yasushi Saito, Michal Szymaniak, Christopher Taylor, Ruth Wang, and Dale Woodford. 2012. Spanner: Google’s globally-distributed database. In Proceedings of the 10th USENIX Conference on Operating Systems Design and Implementation (OSDI’12). USENIX Association, Berkeley, CA, 251--264. Retrieved from http://dl.acm.org/citation.cfm?id=2387880.2387905. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Carlo Curino, Evan P. C. Jones, Samuel Madden, and Hari Balakrishnan. 2011a. Workload-aware database monitoring and consolidation. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD’11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Carlo Curino, Evan Jones, Raluca Ada Popa, Nirmesh Malviya, Eugene Wu, Samuel Madden, Hari Balakrishnan, and Nickolai Zeldovich. 2011b. Relational cloud: A database-as-a-service for the cloud. In proceedings of the 5th Biennial Conference on Innovative Data Systems Research.Google ScholarGoogle Scholar
  18. G. DeCandia, D. Hastorun, and M. Jampani. 2007. Dynamo: Amazon’s highly available key-value store. ACM SIGOPS Operat. (2007). Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Aaron J. Elmore, Sudipto Das, Divyakant Agrawal, and Amr El Abbadi. 2011. Zephyr: Live migration in shared nothing databases for elastic cloud platforms. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD’11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Global Cloud Infrastructure 2016. Regions Beyond Regions: Global Cloud Infrastructure Expansions. Retrieved from https://blog.fugue.co/2016-04-12-regions-beyond-regions-global-cloud-infrastructure-expansions.html.Google ScholarGoogle Scholar
  21. Chuanxiong Guo, Lihua Yuan, Dong Xiang, Yingnong Dang, Ray Huang, Dave Maltz, Zhaoyi Liu, Vin Wang, Bin Pang, Hua Chen, Zhi-Wei Lin, and Varugis Kurien. 2015. Pingmesh: A large-scale system for data center network latency measurement and analysis. In Proceedings of the 2015 ACM Conference on Special Interest Group on Data Communication (SIGCOMM’15). ACM, New York, NY, 139--152. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. T. Guo and P. Shenoy. 2015. Model-driven geo-elasticity in database clouds. In Proceedings of the 2015 IEEE International Conference on Autonomic Computing (ICAC’15). Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Tian Guo, Prashant Shenoy, and Hakan Hacigümüş. 2016. GeoScale: Providing geo-elasticity in distributed clouds. In Proceedings of the IEEE International Conference on Cloud Engineering (IC2E’16).Google ScholarGoogle ScholarCross RefCross Ref
  24. Keqiang He, Alexis Fisher, Liang Wang, Aaron Gember, Aditya Akella, and Thomas Ristenpart. 2013. Next stop, the cloud: Understanding modern web service deployment in EC2 and azure. In Proceedings of the Internet Measurement Conference (IMC’13). Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Melanie Kambadur, Tipp Moseley, Rick Hank, and Martha A. Kim. 2012. Measuring interference between live datacenter applications. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis. IEEE Computer Society Press, 51. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. S. Kundu, R. Rangaswami, K. Dutta, and Ming Zhao. 2010. Application performance modeling in a virtualized environment. In Proceedings of the Conference on High Performance Computer Architecture (HPCA’10).Google ScholarGoogle ScholarCross RefCross Ref
  27. John D. C. Little. 1961. A proof for the queuing formula: L = λW. Operat. Res. 9, 3 (1961), 383--387. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Guoxin Liu, Haiying Shen, and Harrison Chandler. 2013. Selective data replication for online social networks with distributed datacenters. In Proceedings of the 2013 21st IEEE International Conference on Network Protocols (ICNP’13). IEEE, 1--10.Google ScholarGoogle ScholarCross RefCross Ref
  29. Maxmind GeoIP Service 2016. Maximind GeoIP Service. Retrieved from https://www.maxmind.com/en/home.Google ScholarGoogle Scholar
  30. Memcached 2015. Memcached. Retrieved from http://memcached.org/.Google ScholarGoogle Scholar
  31. Xiaoqiao Meng, Canturk Isci, Jeffrey Kephart, Li Zhang, Eric Bouillet, and Dimitrios Pendarakis. 2010. Efficient resource provisioning in compute clouds via VM multiplexing. In Proceedings of the 2015 IEEE International Conference on Autonomic Computing (ICAC’10). 10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Ningfang Mi, Giuliano Casale, Ludmila Cherkasova, and Evgenia Smirni. 2008. Burstiness in multi-tier applications: Symptoms, causes, and new models. In Proceedings of the Conference on Middleware. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Barzan Mozafari, Carlo Curino, and Samuel Madden. 2013. DBSeer: Resource and performance prediction for building a next generation database cloud. In Proceedings of teh Conference on Innovative Data Systems Research (CIDR’13).Google ScholarGoogle Scholar
  34. Mohamed N. Bennani and Daniel A. Menasce. 2005. Resource allocation for autonomic data centers using analytic performance models. In Proceedings of the 2015 IEEE International Conference on Autonomic Computing (ICAC’05). Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Ripal Nathuji, Aman Kansal, and Alireza Ghaffarkhah. 2010. Q-clouds: Managing performance interference effects for QoS-aware clouds. In Proceedings of EuroSys. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Faisal Nawab, Vaibhav Arora, Divyakant Agrawal, and Amr El Abbadi. 2015. Minimizing commit latency of transactions in geo-replicated data stores. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD’15). ACM, New York, NY, 1279--1294. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Hiep Nguyen, Zhiming Shen, Xiaohui Gu, Sethuraman Subbiah, and John Wilkes. 2013. Agile: Elastic distributed resource scaling for infrastructure-as-a-service. In Proceedings of the USENIX International Conference on Automated Computing (ICAC’13).Google ScholarGoogle Scholar
  38. P. N. Shankaranarayanan, Ashiwan Sivakumar, Sanjay Rao, and Mohit Tawarmalani. 2014. Performance sensitive replication in geo-distributed cloud datastores. In Proceedings of the Conference on Dependable Systems and Networks (DSN’14). Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Percona Xtrabackup. 2015. Percona Xtrabackup (2015). Retrieved from: https://www.percona.com/software/mysql-database/percona-xtrabackup.Google ScholarGoogle Scholar
  40. Fan Ping, Xiaohu Li, Christopher McConnell, Rohini Vabbalareddy, and Jeong-Hyon Hwang. 2011. Towards optimal data replication across data centers. In Proceedings of the 2011 31st International Conference on Distributed Computing Systems Workshops (ICDCSW’11). IEEE, 66--71. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Raluca Ada Popa, Catherine Redfield, Nickolai Zeldovich, and Hari Balakrishnan. 2011. CryptDB: Protecting confidentiality with encrypted query processing. In Proceedings of the 23rd ACM Symposium on Operating Systems Principles. ACM, 85--100. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. S. Sakr and A. Liu. 2012. SLA-based and consumer-centric dynamic provisioning for cloud databases. In Proceedings of the IEEE International Conference on Cloud Computing (CLOUD’12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Ankit Singla, Balakrishnan Chandrasekaran, P. Brighten Godfrey, and Bruce Maggs. 2014. The internet at the speed of light. In Proceedings of the 13th ACM Workshop on Hot Topics in Networks (HotNets-XIII’14). ACM, New York, NY, Article 1, 7 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Yair Sovran, Russell Power, Marcos K. Aguilera, and Jinyang Li. 2011. Transactional storage for geo-replicated systems. In Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (SOSP’11). ACM. 385--400. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. The ObjectWeb TPC-W implementation 2005. The ObjectWeb TPC-W implementation. Retrieved from http://jmob.ow2.org/tpcw.html.Google ScholarGoogle Scholar
  46. B. Urgaonkar, P. Shenoy, A. Chandra, and P. Goyal. 2005. Dynamic provisioning of multi-tier internet applications. In Proceedings of the 2015 IEEE International Conference on Autonomic Computing (ICAC’05). Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Daniel Villela, Prashant Pradhan, and Dan Rubenstein. 2007. Provisioning servers in the application tier for e-commerce systems. In Proceedings of TOIT (2007).Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Website Latency With and Without a Content Delivery Network 2016. Website Latency With and Without a Content Delivery Network. Retrieved from https://www.keycdn.com/blog/website-latency/.Google ScholarGoogle Scholar
  49. Timothy Wood, Ludmila Cherkasova, Kivanc Ozonat, and Prashant Shenoy. 2008. Profiling and modeling resource usage of virtualized applications. In Proceedings of the Conference on Middleware. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. P. Xiong, Y. Chi, S. Zhu, H. J. Moon, C. Pu, and H. Hacigümüş. 2011. Intelligent management of virtualized resources for database systems in cloud environment. In Proceedings of the 2011 IEEE 27th International Conference on Data Engineering. 87--98. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Qiang Xu, Jeffrey Erman, Alexandre Gerber, Zhuoqing Mao, Jeffrey Pang, and Shobha Venkataraman. 2011. Identifying diverse usage behaviors of smartphone apps. In Proceedings of the ACM Internet Measurement Conference (IMC’11). Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Qi Zhang, Ludmila Cherkasova, and Evgenia Smirni. 2007. A regression-based analytic model for dynamic resource provisioning of multi-tier applications. In Proceedings of the 2015 IEEE International Conference on Autonomic Computing (ICAC’07). Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Qian Zhu and Teresa Tung. 2012. A performance interference model for managing consolidated workloads in QoS-aware clouds. In Proceedings of the 2012 IEEE 5th International Conference on Cloud Computing (CLOUD’12). IEEE, 170--179. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Performance and Cost Considerations for Providing Geo-Elasticity in Database Clouds

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          • Published in

            cover image ACM Transactions on Autonomous and Adaptive Systems
            ACM Transactions on Autonomous and Adaptive Systems  Volume 12, Issue 4
            December 2017
            224 pages
            ISSN:1556-4665
            EISSN:1556-4703
            DOI:10.1145/3155314
            Issue’s Table of Contents

            Copyright © 2017 ACM

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 18 December 2017
            • Revised: 1 May 2017
            • Accepted: 1 May 2017
            • Received: 1 August 2016
            Published in taas Volume 12, Issue 4

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article
            • Research
            • Refereed
          • Article Metrics

            • Downloads (Last 12 months)9
            • Downloads (Last 6 weeks)0

            Other Metrics

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader
          About Cookies On This Site

          We use cookies to ensure that we give you the best experience on our website.

          Learn more

          Got it!