## On selfish behavior in CSMA/CA networks (2005)

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Venue: | In Proc. of IEEE Infocom |

Citations: | 43 - 6 self |

### BibTeX

@INPROCEEDINGS{Čagalj05onselfish,

author = {Mario Čagalj and Saurabh Ganeriwal and Jean-pierre Hubaux},

title = {On selfish behavior in CSMA/CA networks},

booktitle = {In Proc. of IEEE Infocom},

year = {2005}

}

### Years of Citing Articles

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### Abstract

Abstract — CSMA/CA protocols rely on the random deferment of packet transmissions. Like most other protocols, CSMA/CA was designed with the assumption that the nodes would play by the rules. This can be dangerous, since the nodes themselves control their random deferment. Indeed, with the higher programmability of the network adapters, the temptation to tamper with the software or firmware is likely to grow; by doing so, a user could obtain a much larger share of the available bandwidth at the expense of other users. We use a game-theoretic approach to investigate the problem of the selfish behavior of nodes in CSMA/CA networks, specifically geared towards the most widely accepted protocol in this class of protocols, IEEE 802.11. We characterize two families of Nash equilibria in a single stage game, one of which always results in a network collapse. We argue that this result provides an incentive for cheaters to cooperate with each other. Explicit cooperation among nodes is clearly impractical. By applying the model of dynamic games borrowed from game theory, we derive the conditions for the stable and optimal functioning of a population of cheaters. We use this insight to develop a simple, localized and distributed protocol that successfully guides multiple selfish nodes to a Pareto-optimal Nash equilibrium. I.

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Citation Context ...e problem of misbehaving from the perspective of a single cheater and then consider more complex scenarios with multiple cheaters in the system. We model the cheaters’ interaction using a static game =-=[16]-=-. A static game is one in which all players make decisions (or select a strategy) simultaneously, without knowledge of the strategies that are being chosen by other players. A. Variation of throughput... |

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Citation Context ...he normal IEEE 802.11 protocol. Note that our goal in this paper is prevent network collapse, in an efficient way, rather than finding the optimal contention window for a network of N = C nodes [25], =-=[17]-=-. However, our adaptive cheating algorithm leads to the same optimal point, without explicit knowledge of the number of contending nodes. As mentioned earlier, we adopted throughput-based detection to... |

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Citation Context ...t as the normal IEEE 802.11 protocol. Note that our goal in this paper is prevent network collapse, in an efficient way, rather than finding the optimal contention window for a network of N = C nodes =-=[25]-=-, [17]. However, our adaptive cheating algorithm leads to the same optimal point, without explicit knowledge of the number of contending nodes. As mentioned earlier, we adopted throughput-based detect... |

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Citation Context ...gorithm that exhibits the same drawback: it requires to change the current protocol. Game theory has been applied in the study of optimal routing [7], [8], [9], congestion control [10], power control =-=[11]-=-, [12], as well as incentive engineering in wireless access networks [13]. III. SYSTEM MODEL We consider N wireless nodes that are willing to transmit data to N designated receivers (one per sender). ... |

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Citation Context ...orski [6] proposes a misbehaviour-resilient backoff algorithm that exhibits the same drawback: it requires to change the current protocol. Game theory has been applied in the study of optimal routing =-=[7]-=-, [8], [9], congestion control [10], power control [11], [12], as well as incentive engineering in wireless access networks [13]. III. SYSTEM MODEL We consider N wireless nodes that are willing to tra... |

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Citation Context ...resilient backoff algorithm that exhibits the same drawback: it requires to change the current protocol. Game theory has been applied in the study of optimal routing [7], [8], [9], congestion control =-=[10]-=-, power control [11], [12], as well as incentive engineering in wireless access networks [13]. III. SYSTEM MODEL We consider N wireless nodes that are willing to transmit data to N designated receiver... |

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Citation Context ... [6] proposes a misbehaviour-resilient backoff algorithm that exhibits the same drawback: it requires to change the current protocol. Game theory has been applied in the study of optimal routing [7], =-=[8]-=-, [9], congestion control [10], power control [11], [12], as well as incentive engineering in wireless access networks [13]. III. SYSTEM MODEL We consider N wireless nodes that are willing to transmit... |

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Citation Context ...m that exhibits the same drawback: it requires to change the current protocol. Game theory has been applied in the study of optimal routing [7], [8], [9], congestion control [10], power control [11], =-=[12]-=-, as well as incentive engineering in wireless access networks [13]. III. SYSTEM MODEL We consider N wireless nodes that are willing to transmit data to N designated receivers (one per sender). In thi... |

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Citation Context .... They consider two frameworks: team work and non-cooperative game. Jin and Kesidis [4] study noncooperative equilibria of Aloha networks for heterogeneous users. For IEEE 802.11, Kyasanur and Vaidya =-=[5]-=- propose that the receiver assigns the backoff value to be used by the sender, so the former can detect any misbehavior of the latter. If the sender deviates from the assigned value, it will be assign... |

86 | DOMINO: A System to Detect Greedy Behavior
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Citation Context ... is assumed that all nodes respect the rules of the protocol. However, we claim that this assumption is less and less appropriate, because the network adapters are becoming more and more programmable =-=[1]-=-. As a result, today a user can modify the behavior of his wireless interface very easily. In this paper, we study the stability and efficiency of wireless networks that contain one or several selfish... |

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Citation Context ..., it characterizes that node as a deviating cheater. Let ri and rj be the measured throughput of nodes i and j, respectively. Due to the inherent short-time unfairness of the IEEE 802.11 MAC protocol =-=[24]-=-, and in order to increase the efficiency of the detection mechanism, we introduce two parameters: the observation time-window size Tobs, in seconds, and the tolerance margin ɛ, in percentage of throu... |

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Citation Context ...RELATED WORK The problem of non-cooperative nodes in wireless (wired) networks has been widely addressed on the network layer, whereas little work has been done on the MAC layer. MacKenzie and Wicker =-=[2]-=- study the problem of selfish users in Aloha from a game-theoretic point of view. They analyze the stabilitysof the system (Nash equilibrium), and calculate the transmission probabilities that optimiz... |

45 |
Equilibria of a Noncooperative Game for Heterogeneous Users of an ALOHA Network
- Jin, Kesidis
(Show Context)
Citation Context ... “game” with partial information, where the transmission probability is adapted according to collision feedback only. They consider two frameworks: team work and non-cooperative game. Jin and Kesidis =-=[4]-=- study noncooperative equilibria of Aloha networks for heterogeneous users. For IEEE 802.11, Kyasanur and Vaidya [5] propose that the receiver assigns the backoff value to be used by the sender, so th... |

33 |
Multiple access in ad-hoc wireless lans with noncooperative stations
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Citation Context ...ate its deviation. As mentioned by the authors, this mechanism has several limitations such as the possible collusion between sender and receiver, and the fundamental change to the protocol. Konorski =-=[6]-=- proposes a misbehaviour-resilient backoff algorithm that exhibits the same drawback: it requires to change the current protocol. Game theory has been applied in the study of optimal routing [7], [8],... |

31 |
Slotted Aloha as a Stochastic Game with Partial Information
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Citation Context ...ach node’s throughput. They assume that all nodes have the same transmission rates and costs. Moreover, every node has an aprioriknowledge about the total number of nodes in the system. Altman et al. =-=[3]-=- reconsider the same Aloha “game” with partial information, where the transmission probability is adapted according to collision feedback only. They consider two frameworks: team work and non-cooperat... |

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Citation Context ...s clearly 3 ), and (iii) the solution should result in system optimal allocation of the available capacity. To derive such a solution we use the Nash bargaining framework from cooperative game theory =-=[20]-=-. The Nash bargaining framework is used to model a situation in which the players negotiate on which point of the set of joint feasible payoffs R they will agree upon. In our case, R ≡{r =(r1,...,rC) ... |

20 | Optimal routing control: repeated game approach
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Citation Context ...proposes a misbehaviour-resilient backoff algorithm that exhibits the same drawback: it requires to change the current protocol. Game theory has been applied in the study of optimal routing [7], [8], =-=[9]-=-, congestion control [10], power control [11], [12], as well as incentive engineering in wireless access networks [13]. III. SYSTEM MODEL We consider N wireless nodes that are willing to transmit data... |

14 | Incentive Engineering in Wireless LAN based Access Networks
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(Show Context)
Citation Context ...t protocol. Game theory has been applied in the study of optimal routing [7], [8], [9], congestion control [10], power control [11], [12], as well as incentive engineering in wireless access networks =-=[13]-=-. III. SYSTEM MODEL We consider N wireless nodes that are willing to transmit data to N designated receivers (one per sender). In this study, we assume all the nodes to be within the same communicatio... |

9 | On Cheating in CSMA/CA Ad Hoc Networks
- ˇCagalj, Ganeriwal, et al.
- 2004
(Show Context)
Citation Context ...ell-behaved and cheating nodes’ access probabilities. As mentioned in Section III, cheater i fixes his contention windows to some value Wi. Consequently, cheater i accessing probability calculates as =-=[18]-=-: Throughput (Mbits/s) 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 Cheater, Simulation Cheater, Analytical Well-behaved, Simulation Well-behaved, Analytical 0 5 10 15 20 25 30 Contention window (WX ) of cheat... |