skip to main content
research-article

It's a Match!: Near-Optimal and Incremental Middlebox Deployment

Published:11 January 2016Publication History
Skip Abstract Section

Abstract

The virtualization and softwarization of modern computer networks offers new opportunities for the simplified management and exible placement of middleboxes as e.g. rewalls and proxies. This paper initiates the study of algorithmically exploiting the exibilities present in virtualized and software-defined networks. Particularly, we are interested in the initial as well as the incremental deployment of middleboxes. We present a deterministic O(log(min{n,k})) approximation algorithm for n-node computer networks, where k is the middlebox capacity. The algorithm is based on optimizing over a submodular function which can be computed efficiently using a fast augmenting path approach. The derived approximation bound is optimal: the underlying problem is computationally hard to approximate within sublogarithmic factors, unless P = NP holds. We additionally present an exact algorithm based on integer programming, and complement our formal analysis with simulations. In particular, we consider the number of used middleboxes and highlight the benefits of the approximation algorithm in incremental deployments. Our approach also finds interesting applications, e.g., in the context of incremental deployment of software-defined networks.

References

  1. A. Gember-Jacobson et al. OpenNF: Enabling innovation in network function control. In Proc. ACM SIGCOMM, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. M. Bagaa, T. Taleb, and A. Ksentini. Service-aware network function placement for efficient traffic handling in carrier cloud. In Proc. IEEE WCNC, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  3. J. Chuzhoy and J. Naor. Covering problems with hard capacities. SIAM J. Comput., 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. V. Chvatal. A greedy heuristic for the set-covering problem. Math. of Operations Research, 4(3), 1979. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. Levin et al. Panopticon: Reaping the benefits of incremental sdn deployment in enterprise network. In Proc. USENIX ATC, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. N. Feamster, J. Rexford, and E. Zegura. The road to sdn. Queue, 11(12):20:20--20:40, Dec. 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. U. Feige. A threshold of ln n for approximating set cover. Journal of the ACM, 45(4):634--652, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. J. Sherry et al. Making middleboxes someone else's problem: Network processing as a cloud service. In Proc. ACM SIGCOMM, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. R. Karp. Reducibility among combinatorial problems. In Complexity of Computer Computations. 1972.Google ScholarGoogle Scholar
  10. S. Knight, H. Nguyen, N. Falkner, R. Bowden, and M. Roughan. The internet topology zoo. Selected Areas in Communications, IEEE Journal on, 29(9):1765--1775, October 2011.Google ScholarGoogle Scholar
  11. L. Lovász. Submodular functions and convexity. Mathematical Programming The State of the Art, 1983.Google ScholarGoogle ScholarCross RefCross Ref
  12. C. Lund and M. Yannakakis. On the hardness of approximating minimization problems. Journal of the ACM, 41(5):960--981, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. T. Lukovszki and S. Schmid Online admission control and embedding of service chains. In Proc. SIROCCO, 2015.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. M. Markovitch and S. Schmid. Shear: A highly available and flexible network architecture: Marrying distributed and logically centralized control planes. In Proc. 23rd IEEE ICNP, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  15. W. Rankothge, J. Ma, F. Le, A. Russo, and J. Lobo. Towards making network function virtualization a cloud computing service. In IFIP/IEEE IM, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  16. S. Raza, G. Huang, C.-N. Chuah, S. Seetharaman, and J. P. Singh. Measurouting: A framework for routing assisted traffic monitoring. IEEE/ACM Trans. Netw., 20(1):45--56, Feb. 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. T. Ritter. Network-based firewall services: Extending the firewall into the cloud. In Nemertes White Paper N0496, 2009.Google ScholarGoogle Scholar
  18. S. Fayazbakhsh et al. Flowtags: Enforcing network-wide policies in the presence of dynamic middlebox actions. In Proc. ACM HotSDN, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. R. Raz and S. Safra. A sub-constant error-probability low-degree test, and sub-constant error-probability pcp characterization of np. In Proc. ACM STOC, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. A. Schrijver. Combinatorial Optimization -- Polyhedra and Efficiency. Springer-Verlag, 2003.Google ScholarGoogle Scholar
  21. S. Vissicchio, L. Vanbever, and O. Bonaventure. Opportunities and Research Challenges of Hybrid Software Defined Networks. ACM CCR, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. L. Wolsey. An analysis of the greedy algorithm for the submodular set covering problem. Combinatorica, 2(4):385--393, 1982.Google ScholarGoogle ScholarCross RefCross Ref
  23. Z. Qazi et al. Simple-fying middlebox policy enforcement using sdn. In Proc. ACM SIGCOMM, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. It's a Match!: Near-Optimal and Incremental Middlebox Deployment

        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

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader