Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework

Liang, Qingkai; Wang, Xinbing; Tian, Xiaohua; Wu, Fan; Zhang, Qian

doi:10.1109/tnet.2014.2315194

Cited by 29 publications

(14 citation statements)

References 32 publications

(47 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other problems that have been formulated in terms of potential games are found in routing [9], [97], [156], [157], [186], [203], BS/AP selection [98], [99], [112], [161], [172], cooperative transmissions [4], [139], secrecy rate maximization [11], code design for radar [146], broadcasting [35], spectrum market [87], network coding [115], [147], [148], data cashing [94], social networks [40], computation offloading [42], localization [79], and demand-side management in smart grids [77], [183]. …”

Section: Discussionmentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

View full text Add to dashboard Cite

SUMMARY Potential games form a class of non-cooperative games where the convergent of unilateral improvement dynamics is guaranteed in many practical cases. The potential game approach has been applied to a wide range of wireless network problems, particularly to a variety of channel assignment problems. In this paper, the properties of potential games are introduced, and games in wireless networks that have been proven to be potential games are comprehensively discussed. key words: potential game, game theory, radio resource management, channel assignment, transmission power control IntroductionThe broadcast nature of wireless transmissions causes cochannel interference and channel contention, which can be viewed as interactions among transceivers. Interactions among multiple decision makers can be formulated and analyzed using a branch of applied mathematics called game theory [61], [131]. Game-theoretic approaches have been applied to a wide range of wireless communication technologies, including transmission power control for code division multiple access (CDMA) cellular systems [153] and cognitive radios [132]. For a summary of game-theoretic approaches to wireless networks, we refer the interested reader to [68] [189].In this paper, we focus on potential games [126], which form a class of strategic form games with the following desirable properties:• The existence of a Nash equilibrium in potential games is guaranteed in many practical situations [126] (Theorems 1 and 2 in this paper), but is not guaranteed for general strategic form games. Example 2 in Sect. 2. We provide an overview of problems in wireless networks that can be formulated in terms of potential games. We also clarify the relations among games, and provide simpler proofs of some known results. Problem-specific learning algorithms [92], [168] are beyond the scope of this paper.The remainder of this paper is organized as follows: In Sect. 2, 3, and 4, we introduce strategic form games, potential games, and learning algorithms, respectively. We then discuss various potential games in Sects. 5 to 18, as shown in Table 1. Finally, we provide a few concluding remarks in Sect. 19.The notation used here is shown in Table 2. Unless the context indicates otherwise, sets of strategies are denoted by calligraphic uppercase letters, e.g., A i , strategies are denoted by lowercase letters, e.g., a i ∈ A i , and tuples of strategies are denoted by boldface lowercase letters, e.g., a. Note that a i is a scalar variable when A i is a set of scalars or indices, a i is a vector variable when A i is a set of vectors, and a i is a set variable when A i is a collection of sets.We use R to denote the set of real numbers, R + to denote the set of nonnegative real numbers, R ++ to denote the set of positive real numbers, and C to denote the set of complex numbers. The cardinality of set A is denoted by |A|. The power set of A is denoted by 2 A . Finally, ½condition is the indicator function, which is one when condition is true and is zero otherwise.We treat many sy...

show abstract

Section: Discussionmentioning

confidence: 99%

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Yamamoto

2015

IEICE Trans. Commun.

View full text Add to dashboard Cite

show abstract

“…Some existing works investigated the selfish routing problem from a game-theoretical point of view [9]- [12]. Congestion games are a class of games proposed by Rosenthal [13].…”

Section: Routing Gamementioning

confidence: 99%

“…In [11], congestion is only caused by the neighbors, where wireless spectrum resources are shared by selfish users. The route-switching game in [12] studied a spectrum-mobility-incurred problem in which there is a tradeoff between the channel-switching cost and the routing cost. They considered an exclusively wireless network environment without wired backbone.…”

Section: Routing Gamementioning

confidence: 99%

Selfish task-driven routing in hybrid networks

Tan

Wang

et al. 2015

2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

View full text Add to dashboard Cite

In Hybrid networks, which synergistically mix together wired and wireless links to achieve flexible and reliable communication, it is particularly challenging to routing selfish tasks since each task wish to finish transmission as early as possible and its decision could have impacts on the others. In this paper, we investigate the problem to route a given set of selfish tasks in hybrid networks. Under a unified cost model, the competitive behaviors of selfish players are modeled as a noncooperative game. We show the game is ordinal potential, and the existence of a pure-Nash Equilibrium (pure-NE) is therefore guaranteed. We also design a routing scheme, called Selfish Task-Driven Routing (STaR), to achieve a pure-NE. Extensive simulations show that our scheme can not only efficiently converge to an equilibrium but also outperform other source routing protocols regarding the completion time and load balancing.

show abstract

“…Examples include vehicular ad hoc networks [1], [2], space communication networks [3], [4], mobile sensor networks [5], [6], whitespace networks 1 [7]- [9] and millimeter-wave (mmWave) networks 2 [10]. In Figure 1, we illustrate a simple time-varying graph and its snapshots over 3 time slots.…”

Section: Introductionmentioning

confidence: 99%

Survivability in Time-Varying Networks

Liang

Modiano

2017

IEEE Trans. on Mobile Comput.

Self Cite

View full text Add to dashboard Cite

Abstract-Time-varying graphs are a useful model for networks with dynamic connectivity such as vehicular networks, yet, despite their great modeling power, many important features of time-varying graphs are still poorly understood. In this paper, we study the survivability properties of time-varying networks against unpredictable interruptions. We first show that the traditional definition of survivability is not effective in timevarying networks, and propose a new survivability framework. To evaluate the survivability of time-varying networks under the new framework, we propose two metrics that are analogous to MaxFlow and MinCut in static networks. We show that some fundamental survivability-related results such as Menger's Theorem only conditionally hold in time-varying networks. Then we analyze the complexity of computing the proposed metrics and develop approximation algorithms. Finally, we conduct trace-driven simulations to demonstrate the application of our survivability framework in the robust design of a real-world bus communication network.

show abstract

Two-Dimensional Route Switching in Cognitive Radio Networks: A Game-Theoretical Framework

Cited by 29 publications

References 32 publications

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Selfish task-driven routing in hybrid networks

Survivability in Time-Varying Networks

Contact Info

Product

Resources

About