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QoSNC: A Novel Approach for Providing QoS with Network Coding

QoSNC: A Novel Approach for Providing QoS with Network Coding. Amir Hesam Salavati Babak Hosein Khalaj Mohammad Reza Aref. Sharif University of Technology Information Systems and Security Lab (ISSL). Presentation Layout. Introduction and motives What is QoS ? How is it provided?

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QoSNC: A Novel Approach for Providing QoS with Network Coding

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  1. QoSNC: A Novel Approach for Providing QoS with Network Coding Amir HesamSalavati BabakHoseinKhalaj Mohammad Reza Aref Sharif University of Technology Information Systems and Security Lab (ISSL)

  2. Presentation Layout • Introduction and motives • What is QoS? • How is it provided? • Why QoS network coding? • A brief review of QoS network coding • QoS network coding • QoSNC: A new approach • Network model and notations • Problem formulation • Comparison with previous works • Conclusion and future works

  3. What is QoS? • Quality of Service is the process of providing the required quality of audio, video and other important flows. • Examples: Youtube, Yahoo Music, … Why QoS? • Nowadays, user demands has grown beyond email and web browsing. • They need more interactive services as well as new services like audio/video broadcasting.

  4. How QoS Is Provided? • First step: over-provisioning • In addition, all algorithms in all layers of network should be modified: • More reliable physical layer • Priority-based queuing in MAC layer • QoS routing in network layer • … • Network coding has many advantage over routing. • So it is reasonable to have the same expectations about QoS network coding and QoS routing.

  5. Why QoS Network Coding? • Network Coding Advantages [1], [2] • More Throughput • Less delay • Constant jitter • More robustness • More reliabality • More Simplicity • So network coding improves QoS

  6. A Brief Review of QoS Network Coding • There are some algorithms that improve QoS by using network coding. • Some of these algorithms maximize network utilization. In this way, throughput is maximized according to operation costs [3]-[5]. • Some other algorithms minimized some sort of cost. This cost, could be energy, delay, etc [6]. • A number of other works just apply network coding to current QoS routing methods to benefit from its advantages [7]-[10]. • But none of them guarantee quality of service.

  7. QoSNC: QoS-based Network Coding

  8. What Is the Problem? • We are given a network with one multicast session running. • The multicast source is asked to provide multicast sinks with requested flows. • The multicast users require flows with guaranteed quality. • More specifically: • The end-to-end delay of each flow should be less than the specified amount. • Its rate should be higher than the minimum required rate.

  9. Algorithm Properties • We are interested in solutions that: • Satisfy delayconstraints • Satisfy rateconstraints • Minimize networkcost • The Algorithm finds minimum cost QoS subgraphs. • Network codes is determined by any code construction method like [11] or[12]. What Is New? • To the best of our knowledge, no one has considered links delays in current algorithms explicitly. • In current works, there are no discrimination is made between different flows.

  10. Network Model and Notations • Network is modeled as a connected graph G(V,E) • Multicast case: one source (s) and a set of receivers (T). • M quality classes • D(c): Maximum tolerable delay of class c • R(c) : Minimum required rate of class c • r(c) : Rate of class c

  11. Network Model and Notations (contd.) • xl(t)(c) :The subflow of class c on link l destined to receiver t • zl(c):The coded flow of class c on link l • Zl: total flow on link l • f(Zl) : the cost of using link l • dl: Delay of link l

  12. zl(1) Network Model and Notations (contd.) Zl xl(1)(1) xl(1)(2) xl(1)(3) xl(1)(3) xl(1)(1) zl(2)

  13. Problem Formulation • According to our model and notations, the QoS-based NC problem would be as follows: Where:

  14. Problem Formulation (contd.) • Subject to: Where:

  15. Problem Formulation (contd.) • The constraint (4a) guarantees that the total flow on link l is less than its capacity. • Equation (4b) indicates the rate constraint. • The constraint (4c) ensures that the total rate of all classes is less than the maxflow rate of the network. • Equation (4d) specifies the delay constraint, making sure that the delay of class c is less than the maximum tolerable delay of the class. • Equation (4e) specifies the flow conservation equation. • Finally, constraints (4f) guarantees the non-negativity of network flows.

  16. Solution • In order to solve the previous problem, primal-dual decomposition method is used [13]. • First, the problem is decomposed into primal subproblems. • Next, the primal and dual problems are solved in a distributed manner. • Lagrange multipliers are exchanged locally during the optimization process. • Due to the convexity of the problem, duality gap is zero [14]. • Further details could be found in the paper.

  17. Comparison with Previous Works

  18. Comparison with Minimum Cost Multicast • We compare our work with minimum cost multicast approaches. • We show that our algorithm is able to provide QoS with costs not much higher than the possible minimum. • Several scenarios are considered to show the advantage of our algorithm over MCM. • In cases where delay constraint is omitted, our algorithm is reduced to MCM. • Thus MCM is a special case of our algorithm.

  19. Scenario 1: Minimum Cost Multicast [1] • Butterfly network, no delay, rate 1 optimal cost = 6 5 a t1 1 1 1 c s 1 1 1 b t2 5

  20. Scenario II: QoS NC • Butterfly network, rate =1, delay constraint = 2 optimal cost = 6, optimal Delay = 2. • But the minimum cost solution does not satisfy delay constraint. Thus, the algorithm chooses the not-minimum cost feasible solution. 5 a t1 1 1 1 c s 1 1 1 b t2 5

  21. More Complex Scenarios • Random topologies, all links with unit delay and cost. • 11% additional costs in the worst case.

  22. More Complex Scenarios (contd.)

  23. Conclusion and Future Works

  24. Conclusion • Due to natural advantages of network coding over routing, it is reasonable to use NC in QoS provisioning. • So far, there is no algorithm that proposes QoS guarantees in the realm of network coding. • We have proposed a distributed algorithm to fill this gap. • The algorithm determines the minimum cost QoS flow subgraph that satisfies delay and throughput constraints.

  25. Future Works • Non-multicast cases • Extending to wireless networks • Practical issues

  26. Thanks For Your Attention Any Questions?

  27. References • R. Ahlswede , N. Cai , S.-Y. Li and R. Yeung Network Information Flow, IEEE Trans. Inf. Theory, vol. 46, pp. 1204, Jul. 2000. • C. Fragouli , J.-Y. L. Boudec and J. Widmer Network Coding: An instant primer, SIGCOMM Comput. Commun. Rev., vol. 36, pp. 63, 2006. • Yunnan Wu, Sun-Yuan Kung, ”Distributed Utility Maximization for Network Coding Based Multicasting: A Shortest Path Approach”, IEEE J. Sel. Areas Commun., Vol. 24, no. 8, pp. 1475-1488, Aug. 2006 • Y. Xi and E. M. Yeh Distributed Algorithms for Minimum Cost Multicast With Network Coding, in Proceedings of the 43rd Annu. Allerton Conf. on Communication, Control, and Computing, Sept. 2005. • Y. Xi and E. M. Yeh, ”Distributed Algorithms for Minimum Cost Multicast with Network Coding in Wireless Networks,” in Proc. 4th Int. Symp. Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt ’06), Boston, MA, Apr. 2006. • D. S. Lun , N. Ratnakar , M. Medard , R. Koetter , D. R. Karger , T. Ho , E. Ahmed and F. Zhao Minimum-cost Multicast Over Coded Packet Networks, IEEE Trans. Inf. Theory, vol. 52, pp. 2608, Jun. 2006. • HulyaSeferoglu, AthinaMarkopoulou, "Opportunistic Network Coding for Video Streaming over Wireless", 2007arXiv0706.1395S

  28. References (contd.) • XuChenguang, XuYinlong, Zhan Cheng, Wu Ruizhe, Wang Qingshan, "On Network Coding Based Multirate Video Streaming in Directed Networks", Performance, Computing, and Communications Conference, 2007. IPCCC 2007. IEEE International, pp. 332 339, Apr. 2007 • ShirishKarande, KiranMisra, HayderRadha, "CLIX: Network Coding and Cross Layer Information Exchange of Wireless Video", Image Processing, 2006 IEEE International Conference on, pp. 737-740, Oct. 2006 • Jiang Guo, Ying Zhu, Baochun Li, "CodedStream: Live Media Streaming with Overlay Coded Multicast", Proceedings of SPIE -- Volume 5305 Multimedia Computing and Networking 2004, NaliniVenkatasubramanian, Editor, December 2003, pp. 28-39 • S. Jaggi, P. Sanders, P. A. Chou, M. Effros, S. Egner, K. Jain, and L. Tolhuizen, Polynomial time algorithms for multicast network code construction, IEEE Trans. Inf. Theory, vol. 51, no. 6, pp. 1973-1982, Jun. 2005. • T. Ho , R. Koetter , M. Mdard , D. R. Karger and M. Effros The Benefits of Coding Over Routing in a Randomized Setting, Proc. IEEE Int. Symp. Information Theory, Yokohama, Japan, Jun./Jul. 2003, p. 442. • D. Palomar and M. Chiang A Tutorial on Decomposition Method and Distributed Network Resource Allocation, IEEE J. Sel. Areas Commun., vol. 24, pp. 1439, Aug. 2006 • S. Boyd and L. Vandenberghe, ”Convex Optimization”,Cambridge, U.K.: Cambridge Univ. Press, 2004.

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