• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Node Incentive Mechanism in Selfish Opportunistic Network

Vol. 13, No.3, March 31, 2019
10.3837/tiis.2019.03.021, Download Paper (Free):


In opportunistic network, the behavior of a node is autonomous and has social attributes such as selfishness.If a node wants to forward information to another node, it is bound to be limited by the node's own resources such as cache, power, and energy.Therefore, in the process of communication, some nodes do not help to forward information of other nodes because of their selfish behavior. This will lead to the inability to complete cooperation, greatly reduce the success rate of message transmission, increase network delay, and affect the overall network performance. This article proposes a hybrid incentive mechanism (Mim) based on the Reputation mechanism and the Credit mechanism.The selfishness model, energy model (The energy in the article exists in the form of electricity) and transaction model constitute our Mim mechanism. The Mim classifies the selfishness of nodes and constantly pay attention to changes in node energy, and manage the wealth of both sides of the node by introducing the Central Money Management Center. By calculating the selfishness of the node, the currency trading model is used to differentiate pricing of the node's services. Simulation results show that by using the Mim, the information delivery rate in the network and the fairness of node transactions are improved. At the same time, it also greatly increases the average life of the network.


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Cite this article

[IEEE Style]
Hao-tian WANG, Zhi-gang Chen, Jia WU and Lei-lei WANG, "Node Incentive Mechanism in Selfish Opportunistic Network," KSII Transactions on Internet and Information Systems, vol. 13, no. 3, pp. 1481-1501, 2019. DOI: 10.3837/tiis.2019.03.021

[ACM Style]
WANG, H., Chen, Z., WU, J., and WANG, L. 2019. Node Incentive Mechanism in Selfish Opportunistic Network. KSII Transactions on Internet and Information Systems, 13, 3, (2019), 1481-1501. DOI: 10.3837/tiis.2019.03.021