TY - JOUR
T1 - Delay-optimal opportunistic scheduling and approximations
T2 - The log rule
AU - Sadiq, Bilal
AU - Baek, Seung Jun
AU - De Veciana, Gustavo
N1 - Funding Information:
Manuscript received September 06, 2009; revised May 18, 2010; accepted July 22, 2010; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor T. Bonald. Date of publication August 30, 2010; date of current version April 15, 2011. This work was supported in part by AFOSR Award FA9550-07-1-0428 and NSF Award CNS-0721532. S. Baek was supported in part by KEIT Contract No. 10035213-2010-01, KU K1011831, and a KU CIC Special Initiation Grant. This paper was presented in part at IEEE INFOCOM, Rio de Janeiro, Brazil, April 19–25, 2009.
PY - 2011/4
Y1 - 2011/4
N2 - This paper considers the design of multiuser opportunistic packet schedulers for users sharing a time-varying wireless channel from performance and robustness points of view. For a simplified model falling in the classical Markov decision process framework, we numerically compute and characterize mean-delay-optimal scheduling policies. The computed policies exhibit radial sum-rate monotonicity: As users' queues grow linearly, the scheduler allocates service in a manner that deemphasizes the balancing of unequal queues in favor of maximizing current system throughput (being opportunistic). This is in sharp contrast to previously proposed throughput-optimal policies, e.g., Exp rule and MaxWeight (with any positive exponent of queue length). In order to meet performance and robustness objectives, we propose a new class of policies, called the Log rule, that are radial sum-rate monotone (RSM) and provably throughput-optimal. In fact, it can also be shown that an RSM policy minimizes the asymptotic probability of sum-queue overflow. We use extensive simulations to explore various possible design objectives for opportunistic schedulers. When users see heterogenous channels, we find that emphasizing queue balancing, e.g., Exp rule and MaxWeight, may excessively compromise the overall delay. Finally, we discuss approaches to implement the proposed policies for scheduling and resource allocation in OFDMA-based multichannel systems.
AB - This paper considers the design of multiuser opportunistic packet schedulers for users sharing a time-varying wireless channel from performance and robustness points of view. For a simplified model falling in the classical Markov decision process framework, we numerically compute and characterize mean-delay-optimal scheduling policies. The computed policies exhibit radial sum-rate monotonicity: As users' queues grow linearly, the scheduler allocates service in a manner that deemphasizes the balancing of unequal queues in favor of maximizing current system throughput (being opportunistic). This is in sharp contrast to previously proposed throughput-optimal policies, e.g., Exp rule and MaxWeight (with any positive exponent of queue length). In order to meet performance and robustness objectives, we propose a new class of policies, called the Log rule, that are radial sum-rate monotone (RSM) and provably throughput-optimal. In fact, it can also be shown that an RSM policy minimizes the asymptotic probability of sum-queue overflow. We use extensive simulations to explore various possible design objectives for opportunistic schedulers. When users see heterogenous channels, we find that emphasizing queue balancing, e.g., Exp rule and MaxWeight, may excessively compromise the overall delay. Finally, we discuss approaches to implement the proposed policies for scheduling and resource allocation in OFDMA-based multichannel systems.
KW - Delay/throughput optimality
KW - Markov decision process
KW - OFDMA resource allocation
KW - opportunistic scheduling
KW - radial sum-rate monotonicity (RSM)
UR - http://www.scopus.com/inward/record.url?scp=79955482963&partnerID=8YFLogxK
U2 - 10.1109/TNET.2010.2068308
DO - 10.1109/TNET.2010.2068308
M3 - Article
AN - SCOPUS:79955482963
VL - 19
SP - 405
EP - 418
JO - IEEE/ACM Transactions on Networking
JF - IEEE/ACM Transactions on Networking
SN - 1063-6692
IS - 2
M1 - 5559458
ER -