Optimal Resource Scheduling in Wireless Multiservice Systems with Random Channel Connectivity

We investigate an optimal scheduling problem in a discrete-time system of L parallel queues that are served by K identical servers. This model has been widely used in studies of emerging 3G/4G wireless systems. We introduce the class of Most Balancing (MB) policies and provide their mathematical characterization. We prove that MB policies are optimal among all work conserving policies; we define optimality as minimization, in stochastic ordering sense, of a range of cost functions of the queue lengths, including the process of total number of packets in the system. We use dynamic coupling arguments for our proof. We also introduce the Least Connected Server First/Longest Connected Queue (LCSF/LCQ) policy as an approximate implementation of MB policies. We conduct a simulation study to compare the performance of several work conserving policies to that of the optimal one. In the simulations we relax some of the mathematical assumptions we required for the analytical proofs. The simulation results show that: (a) in all cases, MB policies outperform the other policies, (b) randomized policies perform fairly close to the optimal one, and, (c) the performance advantage of the optimal policy over the other work conserving policies increases as the channel connectivity decreases.

[1]  T. Lindvall.  Lectures on the Coupling Method , 1992 .

[2]  Matthew S. Grob,et al.  CDMA/HDR: a bandwidth-efficient high-speed wireless data service for nomadic users , 2000, IEEE Commun. Mag..

[3]  N. L. Lawrie,et al.  Comparison Methods for Queues and Other Stochastic Models , 1984 .

[4]  Demosthenis Teneketzis,et al.  ON THE OPTIMALITY OF AN INDEX RULE IN MULTICHANNEL ALLOCATION FOR SINGLE-HOP MOBILE NETWORKS WITH MULTIPLE SERVICE CLASSES , 2000 .

[5]  Ness B. Shroff,et al.  A framework for opportunistic scheduling in wireless networks , 2003, Comput. Networks.

[6]  Ward Whitt,et al.  Comparison methods for queues and other stochastic models , 1986 .

[7]  G. Michailidis,et al.  On the stationary dynamics of parallel queues with random server connectivities , 1995, Proceedings of 1995 34th IEEE Conference on Decision and Control.

[8]  George Michailidis,et al.  ON PARALLEL QUEUING WITH RANDOM SERVER CONNECTIVITY AND ROUTING CONSTRAINTS , 2002, Probability in the Engineering and Informational Sciences.

[9]  N.B. Shroff,et al.  Optimal opportunistic scheduling in wireless networks , 2003, 2003 IEEE 58th Vehicular Technology Conference. VTC 2003-Fall (IEEE Cat. No.03CH37484).

[10]  Alexander L. Stolyar,et al.  Scheduling for multiple flows sharing a time-varying channel: the exponential rule , 2000 .

[11]  R. Srikant,et al.  Fair scheduling in wireless packet networks , 1999, TNET.

[12]  Leandros Tassiulas,et al.  Dynamic server allocation to parallel queues with randomly varying connectivity , 1993, IEEE Trans. Inf. Theory.

[13]  Alexander L. Stolyar,et al.  On the Asymptotic Optimality of the Gradient Scheduling Algorithm for Multiuser Throughput Allocation , 2005, Oper. Res..

[14]  Zhen Liu,et al.  Optimal Transmission Policies for Noisy Channels , 2001, Oper. Res..

[15]  Eytan Modiano,et al.  Optimal Transmission Scheduling in Symmetric Communication Models With Intermittent Connectivity , 2007, IEEE Transactions on Information Theory.

[16]  Rajeev Agrawal,et al.  Optimality of Certain Channel Aware Scheduling Policies , 2002 .

[17]  Lisa Zhang,et al.  Scheduling over a time-varying user-dependent channel with applications to high-speed wireless data , 2005, JACM.

[18]  M. Andrews,et al.  Instability of the proportional fair scheduling algorithm for HDR , 2004, IEEE Transactions on Wireless Communications.

[19]  R. Srikant,et al.  Fair Resource Allocation in Wireless Networks Using Queue-Length-Based Scheduling and Congestion Control , 2005, IEEE/ACM Transactions on Networking.