A game theoretic framework for bandwidth allocation and pricing in broadband networks

By Haïkel Yaïche, Ravi R. Mazumdar, Catherine P. Rosenberg. TNET, 2000

737 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/a6b5403aecb1c9952055c3a46a5f5d1711857050

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In Computer Networks and Communications

In Electrical and Electronic Engineering

In Media Technology

Citations in the corpus

Fair multiuser channel allocation for OFDMA networks using Nash bargaining solutions and coalitions (2005, methodology): “In [4], the problem is formulated using a max-min criterion for downlink application.”
FAST TCP: Motivation, Architecture, Algorithms, Performance (2006, positive): “The emerging theory of large-scale networks under end-to-end control, e.g., [6], [8], [11], [19], [31], [33]–[35], [39], [41], [42], [44], [46], [50]–[53], [56], [63], [64], [73], [76] (see also, e.g., [30], [40], [43], [57] for recent surveys), forms the foundation of the ﬂow-level design.”
Internet congestion control (2002, background): “A natural way to introduce prices in regard to the above optimization is the duality approach introduced in [10] (see also [39] for related ideas and [20] for multicast extensions).”
Network Optimization and Control (2008, neutral): “in [26].”
Utility maximization for communication networks with multipath routing (2006, background): “, when each user (or class) has only one path, has been extensively studied in the past, mainly in the context of Internet flow control (see, for example, [2], [11], [12], [13], [14] and the reference therein).”
A Survey on Big Data Market: Pricing, Trading and Protection (2018, background): “[64] designed a pricing model to evaluate IoT sensing data.”
Joint congestion control, routing, and MAC for stability and fairness in wireless networks (2006, background): “In the context of wireline networks, the idea of a distributed flow control based on a system-wide optimization problem was developed in [12], and followed by others in [1], [14], [18], [30], and [34]; see [24] for a survey.”
On selfish behavior in CSMA/CA networks (2005, methodology): “the equivalent optimization problem Π1 [20], [10]: z1 = max ∑C i=1 log(ri − r i ) Π1 : s.”
Collaborative Computation Offloading for Multiaccess Edge Computing Over Fiber–Wireless Networks (2018, background): “Moreover, it is noticed that game theory is widely adopted in solving the decision-making problems among multiple rational game players with contrasting goals [39]–[41].”
On the Complexity of Scheduling in Wireless Networks (2006, methodology): “Motivated by the works on fair resource allocation in wireline networks [16, 26, 3, 35], researchers have also incorporated congestion control into the cross-layer optimization framework [4, 19, 21, 33, 28, 36, 24].”
Security and Cooperation in Wireless Networks (2007, background): “In [384], Yaiche, Mazumdar and Rosenberg present a game theoretical framework for bandwidth allocation; they study the centralized problem and show that the solution can be distributed in a way that leads to a system-wide optimum.”
Newsvendor model for a dyadic supply chain with Nash bargaining fairness concerns (2014, background): “Therefore, Nash bargaining solution can been seen as a natural extension of the proportional fairness criterion which is probably the most popular fairness notion (Mazumdar, Mason, and Douligeris 1991; Yaïche, Mazumdar, and Rosenberg 2000).”
Nash equilibria of packet forwarding strategies in wireless ad hoc networks (2006, background): “In [25], Yaı̈che, Mazumdar and Rosenberg present a game theoretical framework for bandwidth allocation; they study the centralized problem and show that the solution can be distributed in a way that leads to a system-wide optimum.”