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Distributed opportunistic scheduling for ad-hoc communications: an optimal stopping approach
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International Symposium on Mobile Ad Hoc Networking & Computing archive
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing table of contents
Montreal, Quebec, Canada
SESSION: Link layer design and scheduling table of contents
Pages: 1 - 10  
Year of Publication: 2007
ISBN:978-1-59593-684-4
Authors
Dong Zheng  Arizona State University, Tempe, AZ
Weiyan Ge  Arizona State University, Tempe, AZ
Junshan Zhang  Arizona State University, Tempe, AZ
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

We consider distributed opportunistic scheduling (DOS) in wireless ad-hoc networks, where many links contend for the same channel using random access. In such networks, distributed opportunistic scheduling involves a process of joint channel probing and distributed scheduling. Due to channel fading, the link condition corresponding to a successful channel probing could be either good or poor. In the latter case, further channel probing, although at the cost of additional delay, may lead to better channel conditions and hence higher transmission rates. The desired tradeoff boils down to judiciously choosing the optimal stopping strategy for channel probing and the rate threshold. In this paper, we pursue a rigorous characterization of the optimal strategies from two perspectives, namely, a network-centric perspective and a user-centric perspective. We first consider DOS from a network-centric point of view, where links cooperate to maximize the overall network throughput. Using optimal stopping theory, we show that the optimal strategy turns out to be a pure threshold policy, where the rate threshold can be obtained by solving a fixed point equation. We further devise an iterative algorithm for computing the threshold. Next, we explore DOS from a user-centric perspective, where each links seeks to maximize its own throughput. We treat the problem of rate threshold selections for different links as a non-cooperative game. We explore the existence and uniqueness of the Nash equilibrium, and show that the Nash equilibrium can be approached by the best response strategy. We then develop an online stochastic iterative algorithm using local observations only, and establish its convergence. Finally, we observe that there is an efficiency loss in terms of the throughput at the Nash equilibrium, and introduce apricing-based mechanism to mitigate the loss.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
S. Adireddy and L. Tong. Exploiting decentralized channel state information for random access. IEEE Trans. Info. Theory, 51(2):537--561, Feb. 2005.
 
2
R. Agrawal, A. Bedekar, R. J. La, R. Pazhyannur, and V. Subramanian. Class and channel condition based scheduler for EDGE/GPRS. In Proceeding of SPIE, pages 59--68, 2001.
3
 
4
E. Altman, V. S. Borkar, and A. A. Kherani. Optimal random access in networks with two-way traffic. In Proc. WiOpt'05, 2005.
 
5
M. Andrews, K. Kumaran, K. Ramanan, A. Stolyar, P. Whiting, and R. Vijayakumar. Providing quality of service over a shared wireless link. IEEE Communications Magazine, 39:150--154, 2001.
 
6
 
7
 
8
V. S. Borkar and A. A. Kherani. Random access in wireless ad hoc networks as a distributed game. In Proc. WiOpt'04, 2004.
 
9
S. Borst. User-level performance of channel-aware scheduling algotirthms in wireless data networks. In Proc. IEEE INFOCOM'03, 2003.
 
10
 
11
Y. S. Chow, H. Robbins, and D. Siegmund. Great Expectations: Theory of Optimal Stopping. Houghton Mifflin, 1971.
 
12
T. Ferguson. Optimal Stopping and Applications. http://www.math.ucla.edu/~tom/Stopping/Contents.html, 2006.
 
13
S. Guha, K. Munagala, and S. Sarkar. Jointly optimal transmission and probing strategies for multichannel wireless systems. In Proceedings of CISS'06, Princeton, NJ, 2006.
14
15
 
16
R. Knopp and P. Humlet. Information capacity and power control in single cell multiuser communications. In Proc. IEEE ICC 95, June 1995.
 
17
 
18
M. J. Osborne and A. Rubinstein. A Course In Game Theory. The MIT Press, 1994.
 
19
 
20
X. Qin and R. Berry. Exploiting multiuser dieversity for medium access control in wireless networks. In Proceedings of IEEE INFOCOM'03, 2003.
 
21
 
22
23
 
24
C. Saraydar, N. Mandayam, and D. Goodman. Efficient power control via pricing in wireless data networks. IEEE Trans. on Comm., 50(2):291--303, Feb. 2002.
 
25
S. Shakkottai, R. Srikant, and A. L. Stolyar. Pathwise optimality and state space collapse for the exponential rule. In Proceedings of IEEE Symposium on Information Theory, July 2002.
 
26
A. N. Shiryayev. Optimal Stopping Rules. Springer-Verlag, 1978.
 
27
P. Viswanath, D. N. Tse, and R. Laroia. Opportunistic beamforming using dumb antennas. IEEE Trans. Info. Theory, 48(6):1277--1294, June 2002.
 
28
D. Zheng and J. Zhang. Joint optimal channel probing and transmission in collocated wireless networks. In Proc. IEEE INFOCOM'07 (symposium), May 2007.


Collaborative Colleagues:
Dong Zheng: colleagues
Weiyan Ge: colleagues
Junshan Zhang: colleagues