Time Jails: A Hybrid Approach to Scalable Network Emulation

ABSTRACT

It is essential to evaluate the performance of newly developed distributed software and network protocols. Network emulation enables reproducible evaluation of unmodified real implementations. Software built for distributed systems, such as a large scale peer-to-peer system, requires evaluation scenarios with thousands of communicating nodes. Two approaches for scaling network emulation to such scenario sizes have been proposed in the literature: node virtualization and time virtualization. Node virtualization allows maximizing the utilization of standard hardware used for emulation experiments. Time virtualization enables trading experiment duration for virtually increased resources of the hardware. It stands to reason that a combination of those two approaches may increase scalability even further. However, in existing combinations, either node virtualization implies relatively high overhead or time virtualization requires modifications of the test subject implementation.In this paper, we present a novel hybrid approach called Time Virtualized Emulation Environment (TVEE). It integrates node virtualization with low overhead and time virtualization, which is transparent to the execution of test subjects. We introduce virtual time based on epochs to enable better dynamic hardware utilization during long lasting experiments. Additionally, a mechanism similar to soft timers ensures an accurate reproduction of network properties in the time virtualized emulation. Our evaluations show the accuracy and scalability of time virtualized network emulation. Comparing TCP throughput, TVEE outperforms other approaches using an event based virtual time by an order of magnitude.

REFERENCES

• 1: George Apostolopoulos , Constantinos Hassapis, V-eM: A Cluster of Virtual Machines for Robust, Detailed, and High-Performance Network Emulation, Proceedings of the 14th IEEE International Symposium on Modeling, Analysis, and Simulation, p.117-126, September 11-14, 2006 [doi>10.1109/MASCOTS.2006.51]
• 2: Mohit Aron , Peter Druschel, Soft timers: efficient microsecond software timer support for network processing, Proceedings of the seventeenth ACM symposium on Operating systems principles, p.232-246, December 12-15, 1999, Charleston, South Carolina, United States
• 3: Paul Barham , Boris Dragovic , Keir Fraser , Steven Hand , Tim Harris , Alex Ho , Rolf Neugebauer , Ian Pratt , Andrew Warfield, Xen and the art of virtualization, Proceedings of the nineteenth ACM symposium on Operating systems principles, October 19-22, 2003, Bolton Landing, NY, USA
• 4: Craig Bergstrom , Srinidhi Varadarajan , Godmar Back, The Distributed Open Network Emulator: Using Relativistic Time for Distributed Scalable Simulation, Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation, p.19-28, May 24-26, 2006 [doi>10.1109/PADS.2006.34]
• 5: Peter A. Dinda, The statistical properties of host load, Scientific Programming, v.7 n.3-4, p.211-229, August 1999
• 6: R. M. Fujimoto, Parallel discrete event simulation, Proceedings of the 21st conference on Winter simulation, p.19-28, December 04-06, 1989, Washington, D.C., United States [doi>10.1145/76738.76741]
• 7: Diwaker Gupta , Kenneth Yocum , Marvin McNett , Alex C. Snoeren , Amin Vahdat , Geoffrey M. Voelker, To infinity and beyond: time-warped network emulation, Proceedings of the 3rd conference on Networked Systems Design & Implementation, p.7-7, May 08-10, 2006, San Jose, CA
• 8: M. Hibler, R. Ricci, L. Stoller, J. Duerig, S. Guruprasad, T. Stack, K. Webb, and J. Lepreau. Feedback-directed Virtualization Techniques for Scalable Network Experimentation. University of Utah Flux Group Technical Note FTN-2004- 02, School of Computing, University of Utah, May 2004.
• 9: P. H. Kamp and R. N. M. Watson. Jails: Confining the omnipotent root. In Proceedings of the 2nd International SANE Conference, 2000.
• 10: Cameron Kiddle , Rob Simmonds , Brian Unger, Improving Scalability of Network Emulation through Parallelism and Abstraction, Proceedings of the 38th annual Symposium on Simulation, p.119-129, April 04-06, 2005 [doi>10.1109/ANSS.2005.26]
• 11: Kenichi Kourai , Toshio Hirotsu , Koji Sato , Osamu Akashi , Kensuke Fukuda , Toshiharu Sugawara , Shigeru Chiba, Secure and Manageable Virtual Private Networks for End-users, Proceedings of the 28th Annual IEEE International Conference on Local Computer Networks, p.385, October 20-24, 2003
• 12: S. Maier, A. Grau, H. Weinschrott, and K. Rothermel. Scalable Network Emulation: A Comparison of Virtual Routing and Virtual Machines. In Proceedings of the IEEE Symposium on Computers and Communications (ISCC'07), pages 395-402, Aveiro, Portugal, July 1-4 2007.
• 13: netperf. http://www.netperf.org, 2007.
• 14: OpenVZ. http://openvz.org, 2007.
• 15: George F. Riley , Richard M. Fujimoto , Mostafa H. Ammar, A Generic Framework for Parallelization of Network Simulations, Proceedings of the 7th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, p.128, March 24-28, 1999
• 16: R. Simmonds and B. W. Unger. Towards scalable network emulation. Computer Communications, 26(3):264- 277, 2003.
• 17: S. Y. Wang , H. T. Kung, A new methodology for easily constructing extensible and high-fidelity TCP/IP network simulators, Computer Networks: The International Journal of Computer and Telecommunications Networking, v.40 n.2, p.257-278, 7 October 2002 [doi>10.1016/S1389-1286(02)00254-2]
• 18: Rich Wolski , Neil Spring , Chris Peterson, Implementing a performance forecasting system for metacomputing: the Network Weather Service, Proceedings of the 1997 ACM/IEEE conference on Supercomputing (CDROM), p.1-19, November 15-21, 1997, San Jose, CA [doi>10.1145/509593.509600]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.3 Applications

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Network communications
  C.4 PERFORMANCE OF SYSTEMS
      Subjects: Modeling techniques

General Terms:
Design, Performance