Bubble: Lightweight Core Sharing in NFV
Authors: 
Haiping Wang, Zhilong Zheng, Chen Sun, Jun BiAuthors Info & Claims
Haiping Wang, Zhilong Zheng, Chen Sun, Jun BiAuthors Info & ClaimsPages 1 - 6
Abstract
Many researches have revealed the requirement of enabling multiple network functions (NFs) to share a CPU core in Network Function Virtualization (NFV) to support fine-grained NF models, efficient resource utilization, and chain consolidation. However, these works usually enable core sharing via kernel-level threads, which incurs significant performance degradation. In this paper, we present Bubble to enable lightweight core sharing in NFV. Bubble leverages user-level threads to eliminate the performance overhead introduced by kernel-level thread scheduling. Bubble is designed to satisfy unique requirements in NFV by providing accurate and low-overhead scheduling, in support of on- demand resource allocation, and accurate NF load measurement. Evaluations over a Bubble prototype implementation demonstrate that Bubble can improve the performance by 1.6Ã- to 6.2Ã- for co-located NFs and by 3.7Ã- to 68.8Ã- for a consolidated Service Function Chain (SFC) in a core against two state- of-the-art solutions.
References
[1]
A. Tootoonchian, A. Panda, C. Lan, M. Walls, K. Argyraki, S. Ratnasamy, and S. Shenker, “Resq: Enabling slos in network function virtualization,” in NSDI. USENI XAssociation, 2018.
[2]
J. Martins, M. Ahmed, C. Raiciu, V. Olteanu, M. Honda, R. Bifulco, and F. Huici, “Clickos and the art of network function virtualization,” in NSDI. USENIX Association, 2014, pp. 459–473.
[3]
W. Zhang, G. Liu, W. Zhang, N. Shah, P. Lopreiato, G. Todeschi, K. Ramakrishnan, and T. Wood, “Opennetvm: A platform for high performance network service chains,” in HotMiddlebox. ACM, 2016.
[4]
A. Panda, S. Han, K. Jang, M. Walls, S. Ratnasamy, and S. Shenker, “Netbricks: Taking the v out of nfv,” in OSDI, 2016.
[5]
S. G. Kulkarni, W. Zhang, J. Hwang, S. Rajagopalan, K. K. Ramakrishnan, T. Wood, M. Arumaithurai, and X. Fu, “Nfvnice: Dynamic backpressure and scheduling for nfv service chains,” in SIGCOMM. ACM, 2017.
[6]
W. Zhang, J. Hwang, S. Rajagopalan, K. Ramakrishnan, and T. Wood, “Flurries: Countless fine-grained nfs for flexible per-flow customization,” in CoNEXT. ACM, 2016.
[7]
A. Bremler-Barr, Y. Harchol, and D. Hay, “Openbox: A software-defined framework for developing, deploying, and managing network functions,” in SIGCOMM. ACM, 2016, pp. 511–524.
[8]
V. Sekar, N. Egi, S. Ratnasamy, M. K. Reiter, and G. Shi, “Design and implementation of a consolidated middlebox architecture,” in NSDI. USENIX Association, 2012.
[9]
A. Sriraman and T. F. Wenisch, “µtune: Auto-tuned threading for OLDI microservices,” in OSDI. USENIX Association, 2018.
[10]
“The go programming language,” https://golang.org/, 2009.
[11]
S. Barghi, “uthreads: Concurrent user threads in c++ (and c),” https://github.com/samanbarghi/uThreads, 2015.
[12]
“Dpdk l-thread subsystem,” https://doc.dpdk.org/guides-16.04/sample_app_ug/performance_thread.html, 2014.
[13]
H. Qin, Q. Li, J. Speiser, P. Kraft, and J. Ousterhout, “Arachne: Core-aware thread management,” in OSDI, 2018.
[14]
Z. Zheng, J. Bi, H. Wang, C. Sun, H. Yu, H. Hu, K. Gao, and J. Wu, “Grus: Enabling latency slos for gpu-accelerated nfv systems,” in ICNP, 2018.
[15]
ETSI-. (2013) Network functions virtualization (nfv): Architectural framework. [Online]. Available: http://www.etsi.org.
[16]
I. Molnar, “Linux kernel documentation: Cfs scheduler,” https://www.kernel.org, 2017.
[17]
M. Kablan, A. Alsudais, E. Keller, and F. Le, “Stateless network functions: Breaking the tight coupling of state and processing.” in NSDI, 2017, pp. 97–112.
[18]
“Time stamp counter (tsc),” https://en.wikipedia.org/wiki/Time_Stamp_Counter, 2017.
[19]
K. Zhang, B. He, J. Hu, Z. Wang, B. Hua, J. Meng, and L. Yang, “G-net: Effective gpu sharing in nfv systems,” in NSDI, 2018.
[20]
“Nonlinear optimization,” https://www.mathworks.com/help/optimlno-nlinear-programming.html, 2019.
[21]
Intel. (2012) Data plane development kit (dpdk). [Online]. Available: http://dpdk.org.
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Published: 01 December 2019
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