Incentives and reputation management on D2D ecosystems

PhD Thesis Proposal Defence

Title: "Incentives and reputation management on D2D ecosystems"




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 

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 ****