Abstract
With the increasing of software complexity and user demands, collaborative service is becoming more and more popular. Each service focuses on its own specialty, their cooperation can support complicated task with high efficiency. To improve the resources utilization, virtualization technology like container is used and it enables multiple services running in the same physical machine. However, since the host physical machine is shared by several services, the resource competition is inevitable. Isolation is an effective solution, but the weak isolation mechanisms of container cannot handle such complicated scenarios. In the worst situation, the performance of services cannot meet the requirements and the system may crash. In order to solve this problem, we propose a priority-based optimization mechanism for I/O isolation after analyzing the characteristics of typical service workloads. Based on the real-time performance data, priority is automatically assigned to each service and corresponding optimization methods are applied. We evaluate the optimization effects of the priority-based mechanism in both static and dynamic workload cases, besides, the influence of different priority order is also analyzed. The experimental results show that our approach can indeed improve the system performance and guarantee the requirements of all the running services are satisfied.
Supported in part by the Natural Science Foundation of Zhejiang Province under Grant LQ18F020003 and Grant LY18F020014, and in part by the Natural Science Foundation of China under Grant 61802093 and Grant 61572163, in part by the Xi’an Key Laboratory of Mobile Edge Computing and Security (201805052-ZD3CG36) and in part by the Key Research and Development Program of Zhejiang Province under Grant 2018C01098.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bernstein, D.: Containers and cloud: from LXC to docker to kubernetes. IEEE Cloud Comput. 1(3), 81–84 (2015)
Bruno, J., Brustoloni, J., Gabber, E., Mcshea, M., Silberschatz, A.: Disk scheduling with quality of service guarantees. In: IEEE International Conference on Multimedia Computing & Systems (1999)
Dean, J., Barroso, L.A.: The tail at scale. Commun. ACM 56(2), 74–80 (2013)
Felter, W., Ferreira, A., Rajamony, R., Rubio, J.: An updated performance comparison of virtual machines and linux containers. In: IEEE International Symposium on Performance Analysis of Systems & Software (2007)
Foster, H., Uchitel, S., Magee, J., Kramer, J.: Model-based verification of web service compositions. In: 18th IEEE International Conference on Automated Software Engineering (ASE 2003), Montreal, Canada, pp. 152–163, 6–10 October 2003. https://doi.org/10.1109/ASE.2003.1240303
Gulati, A., Ahmad, I., Waldspurger, C.A.: Parda: proportional allocation of resources for distributed storage access. In: Proceedings of the Conference on File & Storage Technologies (2009)
Gulati, A., Shanmuganathan, G., Zhang, X., Varman, P.: Demand based hierarchical QOS using storage resource pools. In: Usenix Conference on Technical Conference (2012)
Gulati, A., Varman, P.J.: mClock: handling throughput variability for hypervisor IO scheduling. In: Usenix Conference on Operating Systems Design & Implementation (2011)
Jeon, M., et al.: Predictive parallelization: taming tail latencies in web search (2014)
Jin, W., Chase, J.S., Kaur, J.: Interposed proportional sharing for a storage service utility. ACM Sigmetrics Perform. Eval. Rev. 32(1), 37–48 (2004)
Li, N., Jiang, H., Feng, D., Shi, Z.: PSLO: enforcing the X\({}^{\text{th}}\) percentile latency and throughput slos for consolidated VM storage. In: Proceedings of the Eleventh European Conference on Computer Systems, EuroSys 2016, London, United Kingdom, pp. 28:1–28:14, 18–21 April 2016. https://doi.org/10.1145/2901318.2901330
Li, N., Jiang, H., Feng, D., Shi, Z.: Customizable slo and its near-precise enforcement for storage bandwidth. ACM Trans. Storage 13(1), 6 (2017)
Li, Y., Zhang, J., Jiang, C., Wan, J., Ren, Z.: Pine: optimizing performance isolation in container environments. IEEE Access 7, 30410–30422 (2019)
Lo, D., Cheng, L., Govindaraju, R., Ranganathan, P.: Heracles: improving resource efficiency at scale. ACM Sigarch Comput. Archit. News 43(3), 450–462 (2015)
Marshall, P., Keahey, K., Freeman, T.: Improving utilization of infrastructure clouds. In: IEEE/ACM International Symposium on Cluster (2011)
McDaniel, S., Herbein, S., Taufer, M.: A two-tiered approach to I/O quality of service in docker containers. In: 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015, Chicago, IL, USA, pp. 490–491, 8–11 September 2015. https://doi.org/10.1109/CLUSTER.2015.77
Suresh, L., Canini, M., Schmid, S., Feldmann, A.: C3: cutting tail latency in cloud data stores via adaptive replica selection. In: Usenix Conference on Networked Systems Design & Implementation (2015)
Touzi, J., Benaben, F., Pingaud, H., Lorré, J.P.: A model-driven approach for collaborative service-oriented architecture design. Int. J. Prod. Econ. 121(1), 5–20 (2009)
Wang, A., Venkataraman, S., Alspaugh, S., Katz, R., Stoica, I.: Cake: enabling high-level SLOs on shared storage systems. In: ACM Symposium on Cloud Computing (2012)
Xavier, M.G., Oliveira, I.C.D., Rossi, F.D., Passos, R.D.D., Matteussi, K.J., Rose, C.A.F.D.: A performance isolation analysis of disk-intensive workloads on container-based clouds. In: Euromicro International Conference on Parallel (2015)
Li, Y., Zhou, M., You, C., Yang, G., Mei, H.: Enabling on demand deployment of middleware services in componentized middleware. In: Grunske, L., Reussner, R., Plasil, F. (eds.) CBSE 2010. LNCS, vol. 6092, pp. 113–129. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-13238-4_7
Zhang, J., Sivasubramaniam, A., Riska, A., Qian, W., Riedel, E.: An interposed 2-level i/o scheduling framework for performance virtualization. In: ACM Sigmetrics International Conference on Measurement & Modeling of Computer Systems (2005)
Zhu, T., Tumanov, A., Kozuch, M.A., Harchol-Balter, M., Ganger, G.R.: Prioritymeister: Tail latency QOS for shared networked storage. In: ACM Symposium on Cloud Computing (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Zhang, J., Li, Y., Zhou, L., Ren, Z., Wan, J., Wang, Y. (2019). Priority-Based Optimization of I/O Isolation for Hybrid Deployed Services. In: Wang, X., Gao, H., Iqbal, M., Min, G. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 292. Springer, Cham. https://doi.org/10.1007/978-3-030-30146-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-30146-0_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30145-3
Online ISBN: 978-3-030-30146-0
eBook Packages: Computer ScienceComputer Science (R0)