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| Content Provider | ACM Digital Library |
|---|---|
| Author | Ohata, Yuri Shigeno, Hiroshi Kamimoto, Takashi Shinohara, Ryoki |
| Abstract | In mobile ad hoc networks (MANETs), non-cooperative nodes can refuse to forward packets to conserve their own resources despite MANETs depend on the nodes for delivering packets. To motivate nodes to forward packets, incentive systems using reputation and virtual credit have been proposed. However, we cannot use the systems for a long time, because they cannot regulate the virtual credit in the network. In this paper, we propose Cooperation Incentive System Balancing Virtual Credit (CIBC). CIBC decides the costs nodes pay to request their packets to be forwarded based on node reputations and the total amount of virtual credit in the network. Here, we introduce a method to calculate new node reputations which considers the number of times that nodes drop packets in order to motivate nodes to always forward packets. Moreover, source nodes preferentially request other nodes that do not have much credit to forward packets so that they can earn credit and prevent some nodes from getting too much credit. In this way, CIBC can regulate the amount of virtual credit in the network and prevent some nodes from getting excessive amounts of virtual credit so that more nodes are motivated to be cooperative. We evaluate CIBC by simulation, and the results show that CIBC can maintain the motivation of nodes to be cooperative while also regulating the amount of virtual credit in the network and suppressing differences in amounts of virtual credit between nodes to be within a reasonable range. |
| Starting Page | 218 |
| Ending Page | 226 |
| Page Count | 9 |
| File Format | |
| ISBN | 9781450347501 |
| DOI | 10.1145/2994374.2994385 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-11-28 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Incentive Virtual credit Selfish nodes Mobile ad hoc networks |
| Content Type | Text |
| Resource Type | Article |
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