A network calculus approach to throughput analysis of stochastic multi-channel networks

In this paper, two types of throughput, which are transient throughput and delay-constraint throughput, are investigated in a Gilbert-Elliott multi-channel network by using the stochastic network calculus. We propose a multi-channel model and derive an equivalent stochastic service curve guaranteed by the whole network. With the stochastic service curve, we obtain the lower bound of the network transient throughput. The throughput is non-asymptotic in that it holds for any number of channels and also fully accounts for transient regime. After, we derive the probabilistic delay bound of the multi-channel network, with which we further ascertain the delay-constraint throughput. Finally, numerical results are presented to show the impacts of the channel memory and number of channel on the transient throughput and that of the delay constraint on the maximum arrival rate sustained by the network.

[1]  Alexander N. Dudin,et al.  Mathematical analysis of the multi-server queueing model for dynamic channel reservation in wireless networks , 2006, IEEE Communications Letters.

[2]  Chuang Lin,et al.  Stochastic Performance Analysis of a Wireless Finite-State Markov Channel , 2013, IEEE Transactions on Wireless Communications.

[3]  Yuming Jiang May.  A Note on Applying Stochastic Network Calculus , 2010 .

[4]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[5]  Tara Javidi,et al.  Delay-Optimal Server Allocation in Multiqueue Multiserver Systems With Time-Varying Connectivities , 2009, IEEE Transactions on Information Theory.

[6]  Florin Ciucu,et al.  On the scaling of non-asymptotic capacity in multi-access networks with bursty traffic , 2011, 2011 IEEE International Symposium on Information Theory Proceedings.

[7]  R. Srikant,et al.  Scheduling for small delay in multi-rate multi-channel wireless networks , 2011, 2011 Proceedings IEEE INFOCOM.

[8]  Yuehong Gao,et al.  Guaranteed service and delay-constrained capacity of a multi-channel cognitive secondary network , 2012, 2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM).

[9]  George Baravdish,et al.  Analysis of vehicular wireless channel communication via queueing theory model , 2014, 2014 IEEE International Conference on Communications (ICC).

[10]  Yuming Jiang,et al.  A stochastic calculus for network systems with renewable energy sources , 2011, 2012 Proceedings IEEE INFOCOM Workshops.

[11]  Parimal Parag,et al.  Resource Allocation and Quality of Service Evaluation for Wireless Communication Systems Using Fluid Models , 2007, IEEE Transactions on Information Theory.

[12]  Cheng-Shang Chang,et al.  Performance guarantees in communication networks , 2000, Eur. Trans. Telecommun..

[13]  Florin Ciucu,et al.  On Superlinear Scaling of Network Delays , 2011, IEEE/ACM Transactions on Networking.

[14]  Florin Ciucu,et al.  Non-asymptotic throughput and delay distributions in multi-hop wireless networks , 2010, 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[15]  Jean-Yves Le Boudec,et al.  Network Calculus: A Theory of Deterministic Queuing Systems for the Internet , 2001 .

[16]  Marwan Krunz,et al.  Bandwidth allocation in wireless networks with guaranteed packet-loss performance , 2000, TNET.

[17]  Khaled Ben Letaief,et al.  Multiuser OFDM with adaptive subcarrier, bit, and power allocation , 1999, IEEE J. Sel. Areas Commun..

[18]  Yuehong Gao,et al.  Analysis on the energy consumption in stochastic wireless networks , 2014, 2014 IEEE International Conference on Communications Workshops (ICC).

[19]  Lei Ying,et al.  Scheduling in Multi-Channel Wireless Networks: Rate Function Optimality in the Small-Buffer Regime , 2014, IEEE Trans. Inf. Theory.