Reputation and Credit based Incentive Mechanism For Data-centric Message Delivery in Delay-tolerant Networks

Speaker:  Sanjay Kumar Madria – Rolla, MO, United States
Topic(s):  Security and Privacy

Abstract

In Delay Tolerant Networks (DTNs), to ensure successful message delivery, contribution of mobile nodes in relaying in an opportunistic fashion is essential. In our proposed data-centric dissemination protocol here, messages (images) are annotated with keywords by the source, and then intermediate nodes are presented with an option of adding keyword-based annotations to create higher content strength messages enroute toward the destination. Therefore, the message contents like images get enriched as the ground situation evolves and learned by these intermediate nodes, such as in a disaster situation, or in a battlefield. Due to limited battery and storage capacity in mobile devices, nodes might turn selfish and do not participate in relaying or improving the quality of messages. Thus, additionally, an incentive mechanism is proposed in this talk which considers factors like message quality, level of interests, battery usage, etc. for the calculation of incentives. At the same time, in order to prevent the nodes from turning malicious by adding inappropriate message tags in pursuit of acquiring more incentive, a distributed reputation model (DRM) is developed and integrated with the proposed incentive scheme. DRM takes into account inputs from the intermediate users like ratings of the message quality, relevance of annotations in the message, etc. The proposed scheme thus ensures avoidance of congestion due to uncooperative or selfish nodes in the system. The performance evaluations show that the approach delivers more high priority and quality messages with reduced traffic with a slightly lower message delivery ratio compared to a more recent DTN routing like ChitChat, where a source forwards a message to intermediate nodes, which meet or exceed the matching strength of keyword-based interests. 

About this Lecture

Number of Slides:  30
Duration:  60 minutes
Languages Available:  English
Last Updated: 

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