Distributed Optimization Based on Utility with Delay Constraints in Wireless Sensor Networks

Delay requirement becomes a key problem for the time sensitive applications in wireless sensor networks besides the power conservation issue. This paper proposes a novel Network Utility Maximization (NUM) model with constrained delay for real-time applications in wireless sensor networks. By using dual decomposition techniques, we present a distributed iterative price and rate adaption algorithm which converges to the global optimal solution. The presented algorithm can jointly control congestion and contention while meeting the delay requirement of each flow in the network. Numerical results validate our arguments.

[1]  Stephen P. Boyd,et al.  Simultaneous routing and resource allocation via dual decomposition , 2004, IEEE Transactions on Communications.

[2]  Zongkai Yang,et al.  Distributed Optimization for Utility-Energy Tradeoff in Wireless Sensor Networks , 2007, 2007 IEEE International Conference on Communications.

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

[4]  John W. Byers,et al.  Utility-based decision-making in wireless sensor networks , 2000, 2000 First Annual Workshop on Mobile and Ad Hoc Networking and Computing. MobiHOC (Cat. No.00EX444).

[5]  Dimitri P. Bertsekas,et al.  Data Networks , 1986 .

[6]  Suhas N. Diggavi,et al.  Optimal Rate-Reliability-Delay Tradeoff in Networks with Composite Links , 2007, IEEE Transactions on Communications.

[7]  Wei-Peng Chen,et al.  An energy-aware data-centric generic utility based approach in wireless sensor networks , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[8]  Lui Sha,et al.  Real-time communication and coordination in embedded sensor networks , 2003, Proc. IEEE.

[9]  Mung Chiang,et al.  Balancing transport and physical Layers in wireless multihop networks: jointly optimal congestion control and power control , 2005, IEEE Journal on Selected Areas in Communications.

[10]  Mung Chiang Balancing transport and physical Layers in wireless multihop networks: jointly optimal congestion control and power control , 2005 .

[11]  Steven H. Low,et al.  Optimization flow control—I: basic algorithm and convergence , 1999, TNET.

[12]  Scott Shenker,et al.  Fundamental Design Issues for the Future Internet (Invited Paper) , 1995, IEEE J. Sel. Areas Commun..

[13]  Mitali Singh,et al.  Decentralized Utility-based Sensor Network Design , 2006, Mob. Networks Appl..

[14]  John W. Byers,et al.  Utility-based decision-making in wireless sensor networks , 2000, MobiHoc.

[15]  Mung Chiang,et al.  Cross-Layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.