22nd International Conference on Distributed Computing and Networking
Jan 5th-8th, 2021 Nara, JapanVirtual Conference
KEYNOTE SPEECH 1
January 5, 8:00-9:00 (UTC+9)
Network Decomposition and Distributed Derandomization
This keynote talk will provide an overview of a recent line of work
[Rozhoň and Ghaffari at STOC 2020; Ghaffari, Harris, and Kuhn at
FOCS 2018; and Ghaffari, Kuhn, and Maus at STOC 2017], which
presented the first efficient deterministic network decomposition algorithm
as well as a general derandomization result for distributed
graph algorithms. Informally, the derandomization result shows
that any (locally-checkable) graph problem that admits an efficient
randomized distributed algorithm also admits an efficient deterministic
distributed algorithm. These results resolve several central and
decades-old open problems in distributed graph algorithms.
ETH Zurich, Switzerland
Mohsen Ghaffari is an Assistant Professor in the Computer Science
department of ETH Zurich. Before joining ETH in 2016, he received
his PhD from MIT. Mohsen’s research is focused on distributed
algorithms and parallel algorithms, and his work on these areas has
been honored by several best paper awards (at conferences such as
PODC, SODA, DISC, and ICALP), the 2017 ACM-EATCS Principles
of Distributed Computing dissertation award, and an honorable
mention of ACM’s 2017 Doctoral Dissertation award.
5G commercial service was launched globally. Study and development
for technologies toward evolution of 5G are ongoing taking
into account issues in initial 5G and coming market needs. Research
on beyond 5G/6G initiated in the world.
5G is expected to provide new value as a basic technology supporting
future industry and society, along with artificial intelligence
(AI) and the Internet of Things (IoT), as well as further upgrading
of the multimedia communication services with its technical features
such as high speed, high capacity, low latency, and massive
In the future, while 5G is expected to be utilized in various
industrial fields, conducting research and development aiming at
the further future of 5G is desirable by looking at future market
trends, needs, social problems, and technological evolution. The
mobile communication system has been evolving technically every
decade, while the services of mobile communications have changed
greatly in cycles of approximately 20 years. Therefore, the "Third
Wave" initiated by 5G is expected to become a larger wave through
the "5G evolution and 6G", and will support industry and society in
NTT DOCOMO published the white paper on "5G evolution and
6G" in January, 2020 and updated in July, 2020. In this presentation,
contents of the white paper and our latest study results on "5G
evolution and 6G" will be explained.
Senior Vice President,
General Manager of 6G Laboratories,
NTT DOCOMO, INC.,
Mr. Takehiro Nakamura joined NTT Laboratories in 1990. He is
now SVP and General Manager of the 6G Laboratories in NTT
DOCOMO, INC. Mr. Nakamura has been engaged in the standardization
activities for the W-CDMA, HSPA, LTE/LTE-Advanced and
5G at ARIB in Japan since 1997. He has been the Acting Chairman
of Strategy & Planning Committee of 5G Mobile Communications
Promotion Forum (5GMF) in Japan since October 2014. Mr. Nakamura
has also been contributing to standardization activities in
3GPP since1999, including as a contributor to 3GPP TSG-RAN as
chairman from April 2009 to March 2013. He is also very active
in standardization of C-V2X/Connected Car in ARIB and ITS Infocommunications
Forum in Japan. He is now a leader of Cellular
System Task Group of ITS Info-communications Forum.
Quorum systems are a key abstraction in distributed fault-tolerant
computing for capturing trust assumptions. They can be found at
the core of many algorithms for implementing reliable broadcasts,
shared memory, consensus and other problems. This talk introduces
asymmetric Byzantine quorum systems that model subjective
trust. Every process is free to choose which combinations of other
processes it trusts and which ones it considers faulty.
Asymmetric quorum systems strictly generalize standard Byzantine
quorum systems, which have only one global trust assumption
for all processes. The talk presents also several protocols that tolerate
Byzantine faults with asymmetric trust, such as shared-register
implementations and reliable Byzantine broadcasts.
Consensus is arguably one of the most important notions in
distributed computing and also relevant for practical systems. We
also showhowto realize consensus protocols with asymmetric trust,
illustrating our approach for protocols in partially synchronous
systems and for asynchronous protocols that use randomization
with asymmetric trust.
Asymmetric quorum systems offer a way to understand some
ideas behind the Ripple and Stellar blockchain protocols, which aim
at relaxing symmetric trust assumptions and permit flexible trust.
The presentation is based on joint work with Björn Tackmann
and Luca Zanolini.
University of Bern, Switzerland
Christian Cachin is a professor of computer science at the University
of Bern, where he leads the cryptology and data security
research group since 2019. Prior to that he worked for IBM Research
- Zurich during more than 20 years. He has held visiting positions
at MIT and at EPFL and has taught at several universities during
his career in industrial research. He graduated with a Ph.D. in
Computer Science from ETH Zurich in 1997. He is an ACM Fellow,
an IEEE Fellow, recipient of multiple IBM Outstanding Technical
Achievement Awards, and has also served as the President of the
International Association for Cryptologic Research (IACR) from
With a background in cryptography, he is interested in all aspects
of security in distributed systems and especially in cryptographic
protocols, consistency, consensus, blockchains, and cloudcomputing
security. He has developed many cryptographic protocols,
particularly for achieving consensus and for executing distributed
cryptographic operations over the Internet. In the area
of cloud computing, he has contributed to standards in storage
security and developed protocols for key management.
He co-authored a textbook on distributed computing titled “Introduction
to Reliable and Secure Distributed Programming”. While
at IBM Research he made essential contributions to the development
of Hyperledger Fabric, a blockchain platform aimed business
Building next-generation healthcare systems using distributed machine learning
Medicine stands apart from other areas where AI can be applied.
While we have seen advances in other fields with lots of data, it
is not the volume of data that makes medicine so hard, it is the
challenges arising from extracting actionable information from the
complexity of the data. It is these challenges that make medicine the
most exciting area for anyone who is really interested in the frontiers
of machine learning – giving us real-world problems where
the solutions are ones that are societally important and which potentially
impact on us all. Think Covid 19!
In this talk I will show how AI and machine learning are transforming
medicine and more generally healthcare and how medicine
is driving newadvances in machine learning, including newmethodologies
in automated machine learning, interpretable and explainable
machine learning, dynamic forecasting, causal inference and
distributed machine learning. I will also discuss our experiences
in implementing such AI solutions nationally, in the UK, in order
to fight the current Covid 19 pandemic as well as how they can be
adapted for international use.
Mihaela van der Schaar
University of Cambridge and University of California Los Angeles
Mihaela van der Schaar is the John Humphrey Plummer Professor
of Machine Learning, Artificial Intelligence and Medicine at the
University of Cambridge, a Fellow at The Alan Turing Institute in
London, and a Chancellor’s Professor at UCLA.
Mihaela was elected IEEE Fellow in 2009. She has received numerous
awards, including the Oon Prize on Preventative Medicine
from the University of Cambridge (2018), a National Science Foundation
CAREER Award (2004), 3 IBM Faculty Awards, the IBM
Exploratory Stream Analytics Innovation Award, the Philips Make
a Difference Award and several best paper awards, including the
IEEE Darlington Award.
Mihaela’swork has also led to 35 USA patents (many widely cited
and adopted in standards) and 45+ contributions to international
standards for which she received 3 International ISO (International
Organization for Standardization) Awards.
In 2019, she was identified by National Endowment for Science,
Technology and the Arts as the most-cited female AI researcher
in the UK. She was also elected as a 2019 "Star in Computer Networking
and Communications" by N2Women. Her research expertise
spans signal and image processing, communication networks,
network science, multimedia, game theory, distributed systems,
machine learning and AI.
Mihaela’s research focus is on machine learning, AI and operations
research for healthcare and medicine.
Lukas Kencl obtained a PhD. degree in Communication Networks from EPFL, Switzerland (2003) and MSc. in Computer Science from Charles University, Prague (1995). Since 2016 he is Head of Global Connectivity Architecture at the Electrolux Group Technology Organization (GTO), where he is responsible for architecture and cybersecurity leadership and R&D contributions in the fields of networking, cybersecurity, software/firmware, cloud computing and data analytics, as part of the company's growing participation in the IoT ecosystem. He leads a team of architects designing innovative systems for connected consumer appliances, represents Electrolux in standardizaton efforts and manages the GTO Prague site. He also maintains affiliation to Czech Technical University in Prague (CTU), where he supervises multiple doctoral students. Previously, he was Director of the R&D Centre for Network Applications (RDC) at FEE CTU, Prague (2007-16), Senior Researcher at Intel Research, Cambridge, UK (2003-6) and a Pre-Doc at IBM Research-Zurich (1999-2003). Dr. Kencl is co-inventor of multiple networking patents and co-author of more than 60 publications in the networking domain. He was General Chair of IFIP Networking 2012 and TPC Chair of IGBSG 2016 and frequently acts at TPC member at various IEEE and ACM conferences.
Autonomous Distributed Systems of Myopic Mobile Robots with Lights
The cooperation of swarming autonomous mobile robots has received
significant interests in recent years. The common goal of
research on it is to clarify the minimum capabilities for robots to
achieve a given task. Thus, algorithms for mobile robots have been
considered on a theoretical model with negative assumptions about
each robot capabilities. Concerning the assumptions, each robot
is identical (i.e., all robots run the same algorithm), anonymous
(i.e., each robot has no IDs to distinguish two robots), oblivious (i.e.,
each robot has no memory to record past situation) and silent (i.e.,
each robot has no direct means of communication).
In the initial model described above, because of fundamentally
weak capabilities, it is known that most tasks cannot be solved
without some additional assumptions even if the model considers
the unlimited visibility. However, we may not need to assume completely
oblivious robots considering their implementations on real
devices because persistent memory is widely available. Thus, recently,
luminous robots have attracted attention in order to improve
robot capability. A luminous robot maintains a non-volatile
visible light, and emits the chosen light color among a set of colors
to other robots. That is, a luminous robot uses the light to memorize
its state and communicate with other robots. On the other hand,
for the assumption of unlimited visibility of the initial model, each
robot has a too strong observation device. Therefore, several recent
studies focus on myopic robots to consider the implementation of
the robot system. A myopic robot has limited visibility, i.e.,
it can take a snapshot only within a certain fixed distance.
In this talk, we consider myopic robots with lights as a more
realistic model and briefly show some recent results on the model.
Graduate School of Advanced Science and Engineering, Hiroshima University,
Sayaka Kamei received the B.E., M.E., and D.E. degrees in computer
science from Hiroshima University in 2001, 2003, and 2006,
respectively. She worked at the Tottori University of Environmental
Studies and Hiroshima University as an assistant professor from
2006-2008 and 2008-2012, respectively. Now, she is an associate professor
of the Graduate School of Advanced Science and Engineering,
Hiroshima University. Her research interests include distributed
algorithms. She is a member of the IEEE, IEEE Computer Society,
ACM, IEICE, and IPSJ.