Weakly-Acyclic (Internet) Routing Games

Engelberg, Roee; Schapira, Michael

doi:10.1007/s00224-013-9474-z

Cited by 7 publications

(11 citation statements)

References 15 publications

(5 reference statements)

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“…[22] and independently [27] observed that the operation of the BGP can be viewed as a best response dynamics in a natural class of routing games and finite improvement paths that terminate in Nash equilibria essentially translate to stable routing states. Following this observation the already mentioned [19] presented a game theoretic analysis of routing on the Internet in presence of 'misbehaving players' or backup edges.…”

Section: Potential Applicationsmentioning

confidence: 87%

“…Weak acyclicity of a game also ensures that certain modifications of the traditional no-regret algorithm yield an almost sure convergence to a Nash equilibrium [35]. [18] and more fully [19] showed that specific Internet routing games are weakly acyclic. In turn, [32] established that certain classes of network creation games are weakly acyclic and moreover that a specific scheduling of players can ensure that the resulting improvement path converges to a Nash equilibrium in O(n log n) steps.…”

Section: Related Workmentioning

confidence: 99%

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Coordination Games on Directed Graphs

Apt

Simon

Wojtczak

2016

Electron. Proc. Theor. Comput. Sci.

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We study natural strategic games on directed graphs, which capture the idea of coordination in the absence of globally common strategies. We show that these games do not need to have a pure Nash equilibrium and that the problem of determining their existence is NP-complete. The same holds for strong equilibria. We also exhibit some classes of games for which strong equilibria exist and prove that a strong equilibrium can then be found in linear time.

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Section: Potential Applicationsmentioning

confidence: 87%

Section: Related Workmentioning

confidence: 99%

Coordination Games on Directed Graphs

Apt

Simon

Wojtczak

2016

Electron. Proc. Theor. Comput. Sci.

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“…To circumvent this problem, in the following we replace the concept of best-response, with the milder notion of better response [42]:…”

Section: Global Energy Efficiency Maximization Without Minimum Rmentioning

confidence: 99%

“…Instead, the goal is just to find a strategy p * k which increases u k compared to the present strategy p k , and given the strategies of the other players p −k . This introduces the notion of better-response dynamics [42]:…”

Section: Global Energy Efficiency Maximization Without Minimum Rmentioning

confidence: 99%

“…A second-order Taylor expansion of (39) gives us p k,n (t + 1) = p k,n (t) + 1 2 Γγ 2 t + γ t p k,n (t) 1 − p k,n (t) P k v k,n (p k,n (t)) (42) where Γ is bounded due to the strict concavity ofû k . Observe that (42) can be seen as a discretized version of (41), up to a bounded error. Since t γ 2 t < t γ t = +∞ by assumption, p k (t) is an asymptotic pseudo-trajectory for (39) [51].…”

Section: B Proof Of Propositionmentioning

confidence: 99%

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A Learning Approach for Low-Complexity Optimization of Energy Efficiency in Multicarrier Wireless Networks

D’Oro

Zappone

Palazzo

et al. 2018

IEEE Trans. Wireless Commun.

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This paper proposes computationally efficient algorithms to maximize the energy efficiency in multi-carrier wireless interference networks, by a suitable allocation of the system radio resources, namely the transmit powers and subcarrier assignment. The problem is formulated as the maximization of the system global energy efficiency (GEE) subject to both maximum power and minimum rate constraints. This leads to a challenging non-convex fractional problem, which is tackled through an interplay of fractional programming, learning, and game theory. The proposed algorithmic framework is provably convergent and has a complexity linear in both the number of users and subcarriers, whereas other available solutions can only guarantee a polynomial complexity in the number of users and subcarriers. Numerical results show that the proposed method performs similarly as other, more complex, algorithms. general an NP-hard problem. Hence, low-complexity solutions are required for practical applications. One widely used approach to reduce complexity makes use of non-cooperative game theory [7]- [9]. In this context, instead of directly tackling the maximization of the systemwide energy efficiency with respect to all of the available network radio resources, the problem is formulated modeling the network nodes as rational agents that compete for individual energy efficiency maximization. Such an approach tackles the system-wide energy efficiency maximization problem by solving a set of user-dependent, convex or pseudo-convex problems, with a reduced set of optimization variables. This leads to a practical resource allocation algorithm, but typically suffers from a significant performance gap in terms of global network performance. In [10], energy-efficient power control in multi-carrier CDMA networks is studied, while in [11] the problem of non-cooperative power control in OFDMA networks is addressed. In [12] non-cooperative energy-efficient power control and receiver design is performed in relayassisted networks.In [13], [14] the non-cooperative, energy-arXiv:1802.09591v1 [cs.NI]

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Dynamic Global Behaviour of Online Routing Games

Varga

2019

Engineering Multi-Agent Systems

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Weakly-Acyclic (Internet) Routing Games

Cited by 7 publications

References 15 publications

Coordination Games on Directed Graphs

Coordination Games on Directed Graphs

A Learning Approach for Low-Complexity Optimization of Energy Efficiency in Multicarrier Wireless Networks

Dynamic Global Behaviour of Online Routing Games

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