A Systematic Design Method for Large-Scale Wireless Ad Hoc Network Protocol Based on Optimization Decomposition Theory

The idea of network protocol design based on optimization theory has been proposed and used practically in Internet for about 15 years. However, for large-scale wireless ad hoc network, although protocol could be viewed as a recursive solving of a global optimization problem, protocol design is still facing huge challenge because an effective distributed algorithm for solving global optimization problem is still lacking. We solve the problem by putting forward a systematic design method based on optimization decomposition. The systematic method includes primal decomposition method and dual decomposition method, with which a complex optimization problem can be decomposed into several smaller and independent optimization subproblems. By using subgradient method, each of these subproblems can be solved distributively. Further, the above two methods can be combined in different sequences or used recursively to solve more complex optimization problems. Two examples of wireless protocol design, the transmission control protocol and the joint congestion control and power control protocol, are given to demonstrate its validity.

[1]  Daniel Pérez Palomar,et al.  Power Control By Geometric Programming , 2007, IEEE Transactions on Wireless Communications.

[2]  Naum Zuselevich Shor,et al.  Minimization Methods for Non-Differentiable Functions , 1985, Springer Series in Computational Mathematics.

[3]  Xiaojun Lin,et al.  Joint rate control and scheduling in multihop wireless networks , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[4]  Liqun Fu,et al.  Fast algorithms for joint power control and scheduling in wireless networks , 2010, IEEE Transactions on Wireless Communications.

[5]  Xiaojun Lin,et al.  The impact of imperfect scheduling on cross-Layer congestion control in wireless networks , 2006, IEEE/ACM Transactions on Networking.

[6]  N. Mandayam,et al.  Optimal Utility-Lifetime Trade-off in Self-regulating Wireless Sensor Networks: A Distributed Approach , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[7]  A. Robert Calderbank,et al.  Layering as Optimization Decomposition: A Mathematical Theory of Network Architectures , 2007, Proceedings of the IEEE.

[8]  Ness B. Shroff,et al.  The impact of imperfect scheduling on cross-Layer congestion control in wireless networks , 2006, IEEE/ACM Transactions on Networking.

[9]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[10]  Mung Chiang,et al.  To layer or not to layer: balancing transport and physical layers in wireless multihop networks , 2004, IEEE INFOCOM 2004.

[11]  Daniel Pérez Palomar,et al.  Alternative Distributed Algorithms for Network Utility Maximization: Framework and Applications , 2007, IEEE Transactions on Automatic Control.

[12]  Jamie S. Evans,et al.  Optimal and distributed protocols for cross-layer design of physical and transport layers in MANETs , 2008, IEEE/ACM Trans. Netw..

[13]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..