Abstract
This paper studies dynamic resource allocation in a decentralized communication network. The temporal aspect in the decentralized resource allocation problem presents new challenges, e.g., in optimizing the delay-throughput trade-off under user-specific delay costs. A dynamic bandwidth allocation game modelling an agent-based network is presented. The dynamic noncooperative game achieves Pareto-efficient bandwidth allocation that can be implemented by a greedy algorithm with pricing. Optimal dynamic pricing is discussed for the efficient sharing of network resources. An ad hoc wireless network is an example of such self-organizing decentralized system: the mobile nodes need not be directly connected to a base station. Another application of the model is to consider distributed uplink scheduling, based on local information, in a WCDMA network. The discretized control variable of a mobile node is either the received power/QoS-level or the binary decision on packet transmission.
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References
L. Bao and J. Garcia-Luna-Aceves, Distributed transmission scheduling using code-division channelization, in: Proc. Networking, Pisa, Italy (2002).
A. Campbell, M. Barry and A. Veres, Distributed control algorthims for service differentiation in wireless packet networks, in: Proc. Infocom, Anchorage, USA (2001).
S. Deb, A. Ganesh and P. Key, Resource allocation with persistent and transient flows, in: Proc. Networking, Pisa, Italy (2002).
V. Domansky and V. Kreps, Social equilibria for competitive resource allocation models, in: Proc. Constructing and Applying Objective Functions, Lecture Notes in Economics and Mathematical Systems (Springer, 2002).
D. Fudenberg and D. Levine, The Theory of Learning in Games (MIT Press, 1999).
Ö. Gürbuz and H. Owen, Dynamic resource scheduling schemes for W-CDMA systems, IEEE Communications Magazine 38(10) (2000) 80–84.
T. Heikkinen, Distributed scheduling via pricing in a communication network, in: Proc. Networking, Pisa, Italy (2002).
T. Heikkinen, On congestion pricing in a wireless network, Wireless Networks 8(4) (2002) 347–354.
H. Ji and H. Cing-Yao, Noncooperative uplink power control in cellular radio systems, Wireless Networks 4(3) (1998) 233–240.
F. Kelly and R. Gibbens, Resource pricing and the evolution of congestion control, http://www.statslab.cam.ac.uk/~frank/ evol.html
J. Konorski, Multiple access in ad hoc wireless LANs with noncooperative stations, in: Proc. Networking Pisa, Italy (2002).
A. Lazar and N. Semret, Design, analysis and simulation of the progressive second price auction for network bandwidth sharing, Telecommunication Systems, Special Issue on Network Economics (1999).
H. Luo, S. Lu and V. Bharghavan, A new model for packet scheduling in multihop wireless networks, in: Proc.Mobicom, Boston, MA (2000).
R. Myerson, Game Theory (Harvard University Press, 1991).
H. Varian, Microeconomic Analysis (Norton, 1978).
M. Wellman, W. Walsh, P. Wurman and J. MacKie-Mason, Auction protocols for decentralized scheduling, Games and Economic Behaviour 35 (2001) 271–303.
J. Zander, Performance of optimum transmitter power control in cellular radio systems, IEEE Transactions on Vehicular Technology 41(1) (1992) 57–62.
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Heikkinen, T. Distributed Scheduling and Dynamic Pricing in a Communication Network. Wireless Networks 10, 233–244 (2004). https://doi.org/10.1023/B:WINE.0000023858.20849.ab
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DOI: https://doi.org/10.1023/B:WINE.0000023858.20849.ab