Game-Based Broadcast over Reliable and Unreliable Wireless Links in Wireless Multihop Networks

Chen, Fuwen; Kao, Jung-Chun

doi:10.1109/tmc.2012.133

Cited by 26 publications

(49 citation statements)

References 31 publications

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

“…The GBBTC algorithm studied in [11] has three main drawbacks. Firstly, it does not perform power control at the transmitting nodes.…”

Section: A Related Workmentioning

confidence: 99%

“…Since the outcome of the MILP must be a tree graph rooted at the source, i.e., S ∈ R i .∀i ∈ W, three conditions for the downstream have to be met [11]. Firstly, the source node cannot be in the downstream of any other node as it is not a CN for other PNs.…”

Section: Centralized Approachmentioning

confidence: 99%

“…More precisely, y i,j = 0 in (37d) indicates that, for a given t j , node i cannot be covered by node j and the downstream value of the link between the nodes j and i must be zero, that is, d i,j = 0. Finally, it should be mentioned that the proposed MILP can also be used for the MFPBT and the MTBT problems [11], [12], however, due to the fixed transmit power, the number of constraints for the MFPBT problem will be much lower than that of the MPBT problem. In fact, since every node has only two choices, that is, whether to transmit or not, there will be only a reachability vector for the nodes and no reachability matrix.…”

Section: Centralized Approachmentioning

confidence: 99%

See 1 more Smart Citation

Cost Sharing Games for Energy-Efficient Multi-Hop Broadcast in Wireless Networks

Mousavi

Al-Shatri

Klein

2020

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

We study multi-hop broadcast in wireless networks with one source node and multiple receiving nodes. The message flow from the source to the receivers can be modeled as a tree-graph, called broadcast-tree. The problem of finding the minimum-power broadcast-tree (MPBT) is NP-complete.Unlike most of the existing centralized approaches, we propose a decentralized algorithm, based on a non-cooperative cost-sharing game. In this game, every receiving node, as a player, chooses another node of the network as its respective transmitting node for receiving the message. Consequently, a cost is assigned to the receiving node based on the power imposed on its chosen transmitting node.In our model, the total required power at a transmitting node consists of (i) the transmit power and (ii) the circuitry power needed for communication hardware modules. We develop our algorithm using the marginal contribution (MC) cost-sharing scheme and show that it is the only scheme by which the optimum broadcast-tree is always a Nash equilibrium (NE) of the game. Simulation results demonstrate that our proposed algorithm outperforms conventional algorithms for the MPBT problem. Besides, we show that the circuitry power, which is usually ignored by existing algorithms, significantly impacts the energy-efficiency of the network. Index TermsEnergy-efficiency; minimum-power multi-hop broadcast; potential game; optimization. is disseminated through the network with the help of some intermediate nodes which re-transmit the message. This problem is known as the minimum-power broadcast-tree (MPBT) problem since the connections between the source and the receiving nodes form a tree-graph rooted at the source, called the broadcast-tree [1]. MPBT construction has been studied by researchers extensively during the past two decades [1][2][3][4][5][6][7][8][9][10][11][12]. NP-completeness of the MPBT can be shown by reducing the Steiner tree problem to it [13]. This means that a polynomial-time algorithm to find the optimum broadcast-tree unlikely exists. Although many algorithms have been proposed for the MPBT problem, most of them are centralized heuristics [1-6]. Since multi-hop device-todevice communication is seen as a promising technique for improving the capacity of 5G cellular networks [14] and due to the variety of its applications, e.g., video streaming [15], vehicular communications [16], etc., it is vital to revisit the MPBT problem to find a decentralized yet efficient algorithm for it.Seeing the MPBT problem from a decentralized optimization point of view, every individual node has to play its own role in forming the broadcast-tree by establishing a communication link to another node. This can be suitably modeled by game theory, in which the players of the game, here the nodes, are typically modeled as selfish agents seeking to minimize (maximize) their own cost (revenue). In our work, the action of a node is to choose another node in the network as its respective transmitting node to receive the source's message from. As a consequence of i...

show abstract

“…It can be used as a rich mathematical tool to evaluate and model a new security problem. Moreover, through the stability analysis of the security game, the protector can gain a deeper understanding of the attacker's strategy, as well as the potential attack risks [4,5]. In this survey, we presented an impression of security and privacy problems that are analyzed within a gametheoretic framework.…”

Section: Introductionmentioning

confidence: 99%

Survey on Automated Intrusion Response System Using Game Theory

Anuvarsha.¹,

Rajeshkumar²

2014

International Journal of Advanced Research in Computer and Comm

View full text Add to dashboard Cite

Abstract:With the increasing number of network technology, intruders are also rationally increased. To provide the security to the network from the intruders is one of the vital one, this survey presents Intrusion Response System to handle the intruders by request and response process by using Game theory. This survey provides a better understanding of the different research approaches by applying game theory for the Automated Intrusion Response System (AIRS). It focuses on fictitious play, fuzzy game, and zero-sum game for automatic response system to the intruders. This survey helps to the researchers in various fields to develop game-theoretic solutions in current and emerging security problems in network security.

show abstract

Game-Based Broadcast over Reliable and Unreliable Wireless Links in Wireless Multihop Networks

Cited by 26 publications

References 31 publications

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

A Comprehensive Survey of Potential Game Approaches to Wireless Networks

Cost Sharing Games for Energy-Efficient Multi-Hop Broadcast in Wireless Networks

Survey on Automated Intrusion Response System Using Game Theory

Contact Info

Product

Resources

About