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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 ****