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Incentives and reputation management on D2D ecosystems
PhD Thesis Proposal Defence Title: "Incentives and reputation management on D2D ecosystems" by Mr. Dimitrios CHATZOPOULOS Abstract: The proliferation of computationally capable mobile devices that are equipped with many sensors and network interfaces gave birth to device-to-device (D2D) ecosystems, where mobile devices connect directly with each other. Devices can exploit these direct communications for exchanging resources and assisting each other with the execution of demanding and context-aware tasks. In this context, the concepts of wisdom of crowd and collective intelligence have been utilized by mobile application developers to achieve distributed computation. The profitability of this method heavily depends on users' interactions and their willingness to share resources. Thus, different applications need to adopt mechanisms that motivate peers to collaborate and defray the costs of participating ones who share their resources. Although credit-based incentive schemes have been proposed for the compensation of mobile users and reputation mechanisms for the marginalization of selfish and malicious users, both are designed to operate via a centralised authority. In this thesis proposal, we advance the state of the art by presenting three works related to (i) the resource exchange, (ii) the reputation, and (iii) the credit transfer between mobile users, which do not rely on any centralised authority. In the first work, we introduce a framework that integrates an incentive scheme and a reputation mechanism for computation offloading in D2D ecosystems. The incentive scheme is a cryptocurrency, named FlopCoin, which is maintained by users called miners who are sharing their cloudlet resources for tasks of other users. In the second work, we present OPENRP, a lightweight and scalable system middleware that provides a unified interface to crowd computing and opportunistic networking applications. OPENRP evaluates and updates the reputation of participating peers based on their mutual opportunistic interactions and chooses the best peers with whom a device should collaborate. In the third work, we propose LocalCoin, an alternative cryptocurrency that requires minimal computational resources, produces low data traffic, and works with off-the-shelf mobile devices. LocalCoin features (i) a lightweight proof-of-work scheme and (ii) a distributed blockchain, replacing the computational hardness that is at the root of Bitcoin's security with the social hardness of ensuring that all witnesses to a transaction are colluders. The quality of the three proposals is depicted through extensive simulations on real traces. In the first work, we show how collaborating devices get rewarded while selfish ones get sidelined. In the second work, we show that the traffic generated by the applications is lower compared to two benchmark strategies. Finally, in the last work we prove that under the assumption of sufficient number of mobile users and properly selected tuning parameters the probability of double spending in LocalCoin is close to zero. Date: Friday, 8 December 2017 Time: 2:00pm - 4:00pm Venue: Room 5501 (lifts 25/26) Committee Members: Dr. Pan Hui (Supervisor) Dr. Brahim Bensaou (Chairperson) Prof. Gary Chan Dr. Dimitrios Papadopoulos **** ALL are Welcome ****