A game-theoretic incentive scheme for social-aware routing in selfish mobile social networks

Jedari, Behrouz; Liu, Li; Qiu, Tie; Rahim, Azizur; Xia, Feng

doi:10.1016/j.future.2016.06.020

Cited by 42 publications

(22 citation statements)

References 39 publications

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“…For example, in Wu et al, a finite‐horizon bargaining game is employed to model the process of packet forwarding in OppNets. GISSO motivates selfish nodes to participate in data forwarding in mobile social networks (MSNs). It is also based on a finite‐horizon bargaining game among nodes for message aware delivery for MSNs.…”

Section: Related Workmentioning

confidence: 99%

“…We evaluate EBIS against two benchmarked incentive‐based mechanisms: SENSE and GISSO . These two approaches have been chosen because they are highly cited in the literature and represent a sample of the recent and successful approaches dealing with the same problem.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Our main contribution can be summarized as follows: We use an evolutionary game‐theoretic approach of an alternating‐offers bargaining game to incentivize nodes to cooperate in messages delivering. We validate the effectiveness of our algorithm through simulation and demonstrate its advantages over GISSO, which is a well‐known model that is based on a classical alternating‐offers game. …”

Section: Introductionmentioning

confidence: 99%

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An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

Nazih

Benamar

Younis

2020

Int J Communication

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Opportunistic networking enables users to communicate in an environment where connectivity is intermittent or unstable. However, such networking scheme assumes that mobile nodes voluntary cooperate, which cannot be guaranteed. Some nodes can simply exhibit selfish behavior and thus diminish the effectiveness of the approach. In this paper, a game scenario is formulated in which the nodes try to convince each other to participate in packets forwarding. Each node is considered as a player in this game. When a node comes in the communication range of another, a bargaining game starts between them as part of the message forwarding process. Both players try to have a mutual agreement on a price for message forwarding. We present a new incentive mechanism called evolutionary bargaining-based incentive scheme (EBIS) to motivate selfish nodes to cooperate in data forwarding. In EBIS, a node negotiates with other nodes to obtain an agreeable amount of credit for its forwarding service. Nodes apply a sequential bargaining game and then adapt their strategies using an evolutionary model to maximize the probability of reaching an agreement. Unlike classical bargaining games, nodes in our model are boundedly rational. In addition, we use the evolutionary stable strategy (ESS) concept to determine the adaptive strategies for the nodes. The comparison of EBIS with a benchmarked model demonstrates that EBIS performs better in terms of packet delivery ratio and average latency. K E Y W O R D Salternating-offers bargaining game, bounded rationality, evolutionary game theory, opportunistic networks

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Section: Related Workmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

Nazih

Benamar

Younis

2020

Int J Communication

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“…In Jedari et al, the authors propose an incentive scheme to enhance the cooperation among socially selfish nodes using both the credit and reputation. Here, a sender negotiates with a relay node to buy its forwarding service by paying an amount of credit.…”

Section: Related Workmentioning

confidence: 99%

“…This section presents the comparative performance of the proposed MHS through simulation. The competitor schemes are T‐PROPHET (T‐PROP), Sig4UDD, GISSO, and BubbleRap (BeRap) . Among these schemes, T‐PROP, Sig4UDD, and GISSO are representatives of the reputation‐based selfishness‐aware schemes, whereas BeRap is representative of conventional social‐based data forwarding schemes.…”

Section: Performance Evaluationmentioning

confidence: 99%

Social‐based reputation‐aware data forwarding for improved multicast delivery in the presence of selfish nodes in DTNs

Roy

Acharya

Bit

2019

Int J Communication

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Delay/disruption tolerant networks (DTNs) are potentially applicable in the challenged scenarios like post-disaster environments. In such networks, data forwarding generally relies on the mutual cooperation of the nodes. However, in reality, despite the availability of necessary resources for data forwarding, a node could misbehave by dropping messages received from other nodes with whom it has no strong social ties. Such a node is called a socially selfish node, which would cause a poor delivery ratio in the network. In this paper, we aim to address the problem of multicast data forwarding in the presence of such selfish nodes, by means of efficient relay selection in DTNs. First, we define a realistic reputation model, in contrast to existing models, to define the socially selfish/misbehaving nodes in the network. Further, a game-theoretic analysis is carried out that implies data forwarding cost is also an influential parameter in handling selfishness/misbehavior. Subsequently, the problem is formulated as a constrained optimization problem, which is NP hard. Therefore, a heuristic is proposed by combining the reputation of a node and the cost of message forwarding to appropriately identify relay nodes, thus improve the performance of the multicast message delivery in the network. We utilize a social metric, centrality to minimize the message forwarding cost in terms of the number of relay nodes. Finally, the comparative performance evaluation in ONE simulator with practical scenarios shows the superiority of the proposed scheme over the other prominent schemes. KEYWORDScentrality, delay tolerant networks, multicast, reputation, selfishness/misbehavior Int J Commun Syst. 2020;33:e4235.wileyonlinelibrary.com/journal/dac

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Social identity–aware opportunistic routing in mobile social networks

Wang

Hao

et al. 2018

Trans Emerging Tel Tech

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Mobile social networks, as a type of delay‐tolerant networks, are composed of nodes with different social properties in which information can be shared among them through opportunistic links. In such networks, it is important to analyze social properties of mobile nodes for transmitting information because they lack a stable source‐to‐destination delivery path and connect intermittently. Many social‐aware routing algorithms have been proposed to address these problems. However, these algorithms fail to achieve an optimal performance since they ignored an important social property, social identity. In this paper, we propose a social identity–aware opportunistic routing algorithm by considering social identities and social influences of mobile nodes in mobile social networks. It is shown that the social identity–aware opportunistic routing algorithm substantially improves the routing performance compared with the existing algorithms according to the simulation results in 2 real‐world human contact traces.

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A game-theoretic incentive scheme for social-aware routing in selfish mobile social networks

Cited by 42 publications

References 39 publications

An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

Social‐based reputation‐aware data forwarding for improved multicast delivery in the presence of selfish nodes in DTNs

Social identity–aware opportunistic routing in mobile social networks

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