A distributed newton method for dynamic Network Utility Maximization with delivery contracts

2012 46th Annual Conference on Information Sciences and Systems, CISS 2012

Volumn , Issue , 2012, Pages

  Wei, Ermin ^a   Ozdaglar, Asuman ^a   Eryilmaz, Atilla ^b   Jadbabaie, Ali ^c  

^a Department of Electrical Engineering and Computer Science   (United States)

^b OHIO STATE UNIVERSITY   (United States)

^c UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMOUNT OF INFORMATION; CONVERGENCE RATE IMPROVEMENT; DUAL DECOMPOSITION; DYNAMIC NETWORK; DYNAMIC PROBLEM; ERROR LEVELS; FINITE TERMINATION; FIRST-ORDER; ITERATIVE APPROACH; LOCAL QUADRATIC CONVERGENCE; MATRIX SPLITTINGS; NETWORK UTILITY MAXIMIZATION; NEWTON DIRECTIONS; NEWTON-TYPE ALGORITHMS; OPTIMAL SOLUTIONS; SUBGRADIENT; TEMPORAL DYNAMICS; TIME INTERVAL; WEB-PAGE;

ALGORITHMS; INFORMATION SCIENCE; NEWTON-RAPHSON METHOD; VIDEO STREAMING;

LOADING;

EID: 84868524605     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CISS.2012.6310918     Document Type: Conference Paper

References (15)

1. S. Athuraliya and S. Low. Optimization flow control with Newton-like algorithm. Journal of Telecommunication Systems, 15:345-358, 2000.
2. S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004.
3. M. Chiang, S. H. Low, A. R. Calderbank, and J.C. Doyle. Layering as optimization decomposition: a mathematical theory of network architectures. Proceedings of the IEEE, 95(1):255-312, 2007.
4. R. Cottle, J. Pang, and R. Stone. The Linear Complementarity Problem. Academic Press, 1992.
5. F. Jarre. Interior-point methods for convex programming. Applied Mathematics and Optimization, 26:287-311, 1992.
6. F. Kelly. Charging and rate control for elastic traffic. European Transactions on Telecommunications, 8:33-37, 1997.
7. F. P. Kelly, A. K. Maulloo, and D. K. Tan. Rate control for communication networks: shadow prices, proportional fairness, and stability. Journal of the Operational Research Society, 49:237-252, 1998.
8. S. H. Low and D. E. Lapsley. Optimization flow control, I: basic algorithm and convergence. IEEE/ACM Transaction on Networking, 7(6):861-874, 1999.
9. J. Mo and JWalrand. Fair end-to-end window-based congestion control. IEEE/ACM Transactions on Networking, 8(5), 2000.
10. A. Nedic and A. Ozdaglar. Convex Optimization in Signal Processing and Communications, chapter Cooperative distributed multi-agent optimization. Eds., Eldar, Y. and Palomar, D., Cambridge University Press, 2008.
11. Y. Nesterov and A. Nemirovskii. Interior-Point Polynomial Algorithms in Convex Programming. SIAM, 2001.
12. R. Srikant. The Mathematics of Internet Congestion Control (Systems and Control: Foundations and Applications). Birkhäuser Boston, 2004.
13. N. Trichakis, A. Zymnis, and S. Boyd. Dynamic Network Utility Maximization with delivery contracts. Proceedings IFAC World Congress, pages 2907-2912, 2008.
14. E. Wei, A. Ozdaglar, and A. Jadbabaie. A distributed Newton method for Network Utility Maximization, I: Algorithm. LIDS Report 2832, submitted for publication, 2011.
15. E. Wei, A. Ozdaglar, and A. Jadbabaie. A distributed Newton method for Network Utility Maximization, II: Convergence. LIDS Report 2870, submitted for publication, 2011.