Topics: Mobile ad-hoc networks; Mobile computing services; Self-organizing networks
Authors: Peter Danielis, Sylvia T. Kouyoumdjieva and Gunnar Karlsson (KTH Royal Institute of Technology, Sweden)
Presenter Bio: Peter Danielis has worked as post doctorand at the Institute of Applied
Microelectronics and Computer Engineering at the University of Rostock,
Germany, since October 2012. He received his MSc degree in information
technology and his PhD in communication technology at the University of
Rostock.
Currently, he works in the research fellowships project "A reliable
distributed computing system for mobile cloud computing" at KTH
Stockholm, EE/LCN until August 2016.
His research interests include peer-to-peer/decentralized wired and
wireless communication, real-time communication in the Internet of
Things/in industrial automation environments, and the design of digital
circuits and systems with HDLs.
Abstract:
Distributed aggregation algorithms have
traditionally been applied to environments with no or rather low rates
of node churn.
The proliferation of mobile devices in recent years introduces high
mobility and node churn to these environments, thus imposing a new
dimension on the problem of distributed aggregation in terms of
scalability and convergence speed.
To address this, we present DiVote, a distributed voting protocol for
mobile device-to-device communication. We investigate a particular use
case, in which pedestrians equipped with mobile phones roam around in an
urban area and participate in a distributed yes/no poll, which has both
spatial and temporal relevance to the community. Each node casts a vote
and collects votes from other participants in the system whenever in
communication range; votes are immediately integrated into a local
estimate. The objective of DiVote is to produce a precise mapping of the
local estimate to the anticipated global voting result while preserving
node privacy. Since mobile devices may have limited resources allocated
for mobile sensing activities, DiVote utilizes D-GAP compression. We
evaluate the proposed protocol via extensive trace-driven simulations of
realistic pedestrian behavior, and demonstrate that it scales well with
the number of nodes in the system. Furthermore, in densely populated
areas the local estimate of participants does not deviate by more than
2.5 % from the global result. Finally, in certain scenarios the
achievable compression rate of DiVote is at least 19 % for realistic
vote distributions.
