Stable Wireless Network Control Under Service Constraints

We consider the design of wireless queueing network control policies with particular focus on combining stability with additional application-dependent requirements. Thereby, we consequently pursue a cost function based approach that provides the flexibility to incorporate constraints and requirements of particular services or applications. As typical examples of such requirements, we consider the reduction of buffer underflows in case of streaming traffic, and energy efficiency in networks of battery powered nodes. Compared with the classical throughput optimal control problem, such requirements significantly complicate the control problem. We provide easily verifiable theoretical conditions for stability, and, additionally, compare various candidate cost functions applied to wireless networks with streaming media traffic. Moreover, we demonstrate how the framework can be applied to the problem of energy efficient routing, and we demonstrate the application of our framework in cross-layer control problems for wireless multihop networks, using an advanced power control scheme for interference mitigation, based on successive convex approximation. In all scenarios, the performance of our control framework is evaluated using extensive numerical simulations.

[1]  Jamie S. Evans,et al.  SCALE: A Low-Complexity Distributed Protocol for Spectrum Balancing in Multiuser DSL Networks , 2009, IEEE Transactions on Information Theory.

[2]  John M. Cioffi,et al.  Multi-User Buffer Control with Drift Fields , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[3]  Gerhard Wunder,et al.  Universal stability and cost optimization in controlled queueing networks , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[4]  Sean P. Meyn.  Stability and Asymptotic Optimality of Generalized MaxWeight Policies , 2008, SIAM J. Control. Optim..

[5]  Chan Zhou,et al.  Stability and Cost Optimization in Controlled Random Walks Using Scheduling Fields , 2013, ArXiv.

[6]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1992 .

[7]  Zhi-Quan Luo,et al.  Dynamic Spectrum Management: Complexity and Duality , 2008, IEEE Journal of Selected Topics in Signal Processing.

[8]  Edmund M. Yeh,et al.  Throughput Optimal Distributed Power Control of Stochastic Wireless Networks , 2010, IEEE/ACM Transactions on Networking.

[9]  Leandros Tassiulas,et al.  Linear complexity algorithms for maximum throughput in radio networks and input queued switches , 1998, Proceedings. IEEE INFOCOM '98, the Conference on Computer Communications. Seventeenth Annual Joint Conference of the IEEE Computer and Communications Societies. Gateway to the 21st Century (Cat. No.98.

[10]  Lei Ying,et al.  On Combining Shortest-Path and Back-Pressure Routing Over Multihop Wireless Networks , 2011, IEEE/ACM Transactions on Networking.

[11]  Gerhard Wunder,et al.  Cost based Heterogeneous Access Management in Multi-Service, Multi-System Scenarios , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[12]  Upamanyu Madhow,et al.  Characterizing outage rates for space-time communication over wideband channels , 2004, IEEE Transactions on Communications.

[13]  Gerhard Wunder,et al.  Autonomous algorithms for centralized and distributed interference coordination: a virtual layer-based approach , 2014, EURASIP J. Wirel. Commun. Netw..

[14]  Douglas J. Leith,et al.  Draining time based scheduling algorithm , 2007, 2007 46th IEEE Conference on Decision and Control.

[15]  Alexander L. Stolyar,et al.  A Novel Architecture for Reduction of Delay and Queueing Structure Complexity in the Back-Pressure Algorithm , 2011, IEEE/ACM Transactions on Networking.

[16]  Tara Javidi,et al.  A General Class of Throughput Optimal Routing Policies in Multi-Hop Wireless Networks , 2009, IEEE Transactions on Information Theory.

[17]  Chan Zhou,et al.  A fundamental characterization of stability in broadcast queueing systems , 2009, 2009 IEEE International Symposium on Information Theory.

[18]  Ness B. Shroff,et al.  Understanding the Capacity Region of the Greedy Maximal Scheduling Algorithm in Multihop Wireless Networks , 2008, IEEE/ACM Transactions on Networking.

[19]  Marco Ajmone Marsan,et al.  Bounds on delays and queue lengths in input-queued cell switches , 2003, JACM.

[20]  Jinhua Zhu,et al.  Model and Protocol for Energy-Efficient Routing over Mobile Ad Hoc Networks , 2011, IEEE Transactions on Mobile Computing.

[21]  Gerhard Wunder,et al.  Wireless network design under service constraints , 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[22]  Gerhard Wunder,et al.  Combining cost-based queueing control with resource allocation in wireless networks , 2012, 2012 International ITG Workshop on Smart Antennas (WSA).

[23]  Eytan Modiano,et al.  Distributed Cross-Layer Algorithms for the Optimal Control of Multihop Wireless Networks , 2010, IEEE/ACM Transactions on Networking.

[24]  Michael J. Neely,et al.  Energy optimal control for time-varying wireless networks , 2005, IEEE Transactions on Information Theory.

[25]  Eytan Modiano,et al.  Polynomial Complexity Algorithms for Full Utilization of Multi-Hop Wireless Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[26]  Gerhard Wunder,et al.  μ-MaxWeight queueing network control with application to in-flight entertainment systems , 2012, 2012 Future Network & Mobile Summit (FutureNetw).

[27]  Sean P. Meyn.  Control Techniques for Complex Networks: Workload , 2007 .

[28]  Matthew R. McKay,et al.  On the Mutual Information Distribution of OFDM-Based Spatial Multiplexing: Exact Variance and Outage Approximation , 2007, IEEE Transactions on Information Theory.