Incentive mechanism for P2P file sharing based on social network and game theory

Wu, Tin Yu; Lee, Wei-Tsong; Guizani, Nadra; Wang, Tzu-Ming

doi:10.1016/j.jnca.2013.10.006

Cited by 53 publications

(20 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The game theory is used to deal with the rational providers in the smart cloud storage service selection process. To solve the free-rider phenomenon in the P2P file-sharing applications, Wu et al [24] propose a Novel Incentive Mechanism (NIM) based on social network and game theory, which can restrain the number of free riders efficiently and encourage the nodes to contribute resources as much as possible. Esposito et al [25] use the game theory to promote truth-telling ones among service providers in the smart cloud storage service selection.…”

Section: Related Workmentioning

confidence: 99%

A routing defense mechanism using evolutionary game theory for Delay Tolerant Networks

Guo

Wang

Cheng

et al. 2016

Applied Soft Computing

View full text Add to dashboard Cite

Abstract-Delay Tolerant Networks (DTNs) often suffer from intermittent disruption due to factors such as mobility and energy. Though lots of routing algorithms in DTNs have been proposed in the last few years, the routing security problems have not attracted enough attention. DTNs are still facing the threats from different kinds of routing attacks. In this paper, a general purpose defense mechanism is proposed against various routing attacks on DTNs. The defense mechanism is based on the routing path information acquired from the forwarded messages and the acknowledgment (ACK), and it is suitable for different routing schemes. Evolutionary game theory is applied with the defense mechanism to analyze and facilitate the strategy changes of the nodes in the networks. Simulation results show that the proposed evolutionary game theory based defense scheme can achieve high average delivery ratio, low network overhead and low average transmission delay in various routing attack scenarios. By introducing the game theory, the networks can avoid being attacked and provide normal transmission service. The network can reach evolutionary strategy stable (ESS) under special conditions after evolution. The initial parameters will affect the convergence speed and the final ESS, but the initial ratio of the nodes choosing different strategies can only affect the game process.

show abstract

Section: Related Workmentioning

confidence: 99%

A routing defense mechanism using evolutionary game theory for Delay Tolerant Networks

Guo

Wang

Cheng

et al. 2016

Applied Soft Computing

View full text Add to dashboard Cite

show abstract

“…John von Neumann proposes game theory in 1928, the game theory is an significant instrument in many fields [14][15][16][17][18][19][20]. Analyze rational players' strategic game and research competitive mathematical theories and methods are the most important function for game theory [14,15,20].…”

Section: Background and Related Workmentioning

confidence: 99%

“…Analyze rational players' strategic game and research competitive mathematical theories and methods are the most important function for game theory [14,15,20]. The Nash-equilibrant of Prisoner's Dilemma (PD) game is a famous topic in the studies, it is defection, and cooperation cannot exist in well-mixed population [12,14,16].…”

Section: Background and Related Workmentioning

confidence: 99%

An incentive game based evolutionary model for crowd sensing networks

Liu

Ota

Liu

et al. 2015

Peer-to-Peer Netw. Appl.

View full text Add to dashboard Cite

Crowd sensing networks can be used for large scale sensing of the physical world or other information service by leveraging the available sensors on the phones. The collector hopes to collect as much as sensed data at relatively low cost. However, the sensing participants want to earn much money at low cost. This paper examines the evolutionary process among participants sensing networks and proposes an evolutionary game model to depict collaborative game phenomenon in the crowd sensing networks based on the principles of game theory in economics. A effectively incentive mechanism is established through corrected the penalty function of the game model accordance with the cooperation rates of the participant, and corrected the game times in accordance with it's payoff. The collector controls the process of game by adjusting the price function. We find that the proposed incentive game based evolutionary model can help decision makers simulate evolutionary process under various scenarios. The crowd sensing networks structure significantly influence cooperation ratio and the total number of participant involved in the game, and the distribution of population with different game strategy. Through evolutionary game model, the manager can select an optimal price to facilitate the system reach equilibrium state quickly, and get the number of participants involved in the game. The incentive game based evolutionary model in crowd sensing networks provides valuable decision-making support to managers.

show abstract

“…Their model found each community's unique evolutionary stable strategy (ESS)and provided its existence conditions. Wu et al [6] proposed an incentive mechanism based on game theory and social networks to determine the availability of packets. Zuo et al [7] introduced an evolutionary, game-based routing model to eliminate selfish routing behaviors and improve the routing efficiency in peer-to-peer (P2P) networks.…”

Section: Introductionmentioning

confidence: 99%

An Active Defense Model with Low Power Consumption and Deviation for Wireless Sensor Networks Utilizing Evolutionary Game Theory

2018

View full text Add to dashboard Cite

In wireless sensors networks, nodes may be easily captured and act non-cooperatively, for example by not defending forwarding packets in response to their own limited resources. If most of these nodes are obtained by attackers, and an attack by an internal malicious node occurs, the entire network will be paralyzed and not be able to provide normal service. Low power consumption indicates that the rational sensor nodes tend to be very close to the mean; high power consumption indicates that the rational sensor nodes are spread out over a large range of values. This paper offers an active defense model for wireless sensor networks based on evolutionary game theory. We use evolutionary game theory to analyze the reliability and stability of a wireless sensor network with malicious nodes. Adding a defense model into the strategy space of the rational nodes and establishing a preventive mechanism forces the malicious node to abandon the attack and even switch to cooperative strategies. Thus, this paper argues that the stability and reliability of wireless sensor networks can be improved. Numerical experiments were conducted to evaluate the proposed defense model, and these results verified our conclusions based on a theoretical analysis that showed that, compared with the existing algorithms, our approach has lower energy consumption, lower deviation, and a higher probability to quickly switch each node to cooperative strategies.

show abstract

Incentive mechanism for P2P file sharing based on social network and game theory

Cited by 53 publications

References 15 publications

A routing defense mechanism using evolutionary game theory for Delay Tolerant Networks

A routing defense mechanism using evolutionary game theory for Delay Tolerant Networks

An incentive game based evolutionary model for crowd sensing networks

An Active Defense Model with Low Power Consumption and Deviation for Wireless Sensor Networks Utilizing Evolutionary Game Theory

Contact Info

Product

Resources

About