Improving the delay performance of CSMA algorithms: A Virtual Multi-Channel approach

CSMA algorithms have recently received a significant amount of interest in the literature for designing efficient wireless control algorithms. CSMA algorithms are attractive because they incur low computation complexity and communication overhead, and can be shown to achieve the optimal capacity under certain assumptions. However, it has also been observed that CSMA algorithms suffer the starvation problem and incur large delay that may grow exponentially with the network size. In this paper, we propose a new algorithm, called Virtual-Multi-Channel (VMC-) CSMA, that can dramatically reduce delay without sacrificing the high capacity and low complexity of CSMA. The key idea of VMC-CSMA to avoid the starvation problem is to use multiple virtual channels to emulate a multi-channel system and compute a good set of feasible schedules simultaneously (without constantly switching/re-computing schedules). Under the protocol interference model and a single-hop utility-maximization setting, our proposed VMC-CSMA algorithm can approach arbitrarily close to the optimal total system utility, with both the number of virtual channels and the computation complexity increasing logarithmically with the network size. The VMC-CSMA algorithm inherits the distributed nature of CSMA algorithms. Further, once our algorithm converges to the steady-state, the expected packet delay for each link equals to the inverse of its long-term average rate, and the distribution of its head-of-line (HOL) waiting time can also be asymptotically bounded. Our simulation results confirm that the proposed VMC-CSMA algorithm indeed achieves both high throughput and low delay. Further, it can quickly adapt to network traffic changes.

[1]  Alexandre Proutière,et al.  Resource Allocation over Network Dynamics without Timescale Separation , 2010, 2010 Proceedings IEEE INFOCOM.

[2]  Atilla Eryilmaz,et al.  A Fast-CSMA Algorithm for Deadline-Constrained Scheduling over Wireless Fading Channels , 2012, ArXiv.

[3]  Minghua Chen,et al.  Mixing time and temporal starvation of general CSMA networks with multiple frequency agility , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[4]  R. Srikant,et al.  Low-Complexity Distributed Scheduling Algorithms for Wireless Networks , 2009, IEEE/ACM Transactions on Networking.

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

[6]  Sheldon M. Ross,et al.  Stochastic Processes , 2018, Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics.

[7]  Yung Yi,et al.  From Glauber dynamics to Metropolis algorithm: Smaller delay in optimal CSMA , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[8]  R. Srikant,et al.  A tutorial on cross-layer optimization in wireless networks , 2006, IEEE Journal on Selected Areas in Communications.

[9]  Devavrat Shah,et al.  Delay optimal queue-based CSMA , 2010, SIGMETRICS '10.

[10]  Yung Yi,et al.  Learning contention patterns and adapting to load/topology changes in a MAC scheduling algorithm , 2006, 2006 2nd IEEE Workshop on Wireless Mesh Networks.

[11]  Donald Ervin Knuth,et al.  The Art of Computer Programming , 1968 .

[12]  Jean C. Walrand,et al.  A Distributed CSMA Algorithm for Throughput and Utility Maximization in Wireless Networks , 2010, IEEE/ACM Transactions on Networking.

[13]  Jian Ni,et al.  Q-CSMA: Queue-Length Based CSMA/CA Algorithms for Achieving Maximum Throughput and Low Delay in Wireless Networks , 2010, INFOCOM 2010.

[14]  Alan M. Frieze,et al.  Torpid mixing of some Monte Carlo Markov chain algorithms in statistical physics , 1999, 40th Annual Symposium on Foundations of Computer Science (Cat. No.99CB37039).

[15]  Dimitri P. Bertsekas,et al.  Convex Analysis and Optimization , 2003 .

[16]  Leandros Tassiulas,et al.  Resource Allocation and Cross-Layer Control in Wireless Networks , 2006, Found. Trends Netw..

[17]  Peter Marbach,et al.  Throughput-optimal random access with order-optimal delay , 2010, 2011 Proceedings IEEE INFOCOM.

[18]  Leandros Tassiulas,et al.  Stability properties of constrained queueing systems and scheduling policies for maximum throughput in multihop radio networks , 1990, 29th IEEE Conference on Decision and Control.

[19]  Murat Alanyali,et al.  Delay performance of CSMA in networks with bounded degree conflict graphs , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[20]  Devavrat Shah,et al.  Hardness of low delay network scheduling , 2010, 2010 IEEE Information Theory Workshop on Information Theory (ITW 2010, Cairo).