Programme
| Time | Subject (Click for info) |
|---|---|
| 09:00-09:25 |
Opening speech (Slides)Sasu Tarkoma, University of Helsinki & Aaron Yi Ding, TU Munich
A welcoming speech from Head of the
Department of
Computer Science
|
| 09:25-09:50 |
HIIT and Research on “Augmented Research”Petri Myllymäki, HIIT/ University of Helsinki HIIT’s Focus Area - Augmented Research
|
| 09:50-10:15 |
Challenges and potential solutions for 5G securityValtteri Niemi, University of Helsinki
Development of 5G technologies has now reached a
point
where study of security issues has been started
in the
standardization forum 3GPP. In the talk, we go
through some
of the key security and privacy issues that have
been
identified so far and discuss potential
solutions.
Viewpoints of some industry players such as
mobile operators
and cellular network vendors are also
highlighted.
|
| 10:15-10:45 |
Coffee BreakCoffee, tea and snacks
|
Mobile Offloading
Session Chair:
Aaron Yi Ding
,
TU Munich
| 10:45-11:10 |
Mobile Content Offloading in Database-Assisted White Space NetworksJussi Kangasharju, University of Helsinki
Mobile data offloading leverages more
affordable or even free network capacity to
reduce the traffic experienced by cellular
operators through their limited over-the-air
resources. One way to harvest free capacity
is to employ the white space, namely,
frequencies that are assigned to licensed users
but are not actively utilized, as long as no
harmful interference is generated. In this talk,
we characterize the benefits of harnessing node
contacts for mobile content offloading through
dynamic spectrum access assisted by a white
space database (WSDB). We take a content-centric
approach and model the selection of distributors
among the subscribers of each content served
through a base station. We formulate an
optimization problem to maximize the offloading
gain based on realistic settings. We show that
such a problem is NP-hard and devise efficient
heuristics for practical mobile data offloading.
Our results show that the offloading gain
allowed by white space is significant even when
WSDB data are inaccurate.
|
| 11:10-11:35 |
Diffusing Your Mobile Apps: Extending In-Network Function Virtualisation to Mobile Function Offloading (Slides)Liang Wang, University of Cambridge
We propose INFv – the first offloading
system able to cache, migrate and dynamically
execute on demand functionality from mobile
devices in ISP networks. INFv is motivated by
the huge disparity between the limited battery
capacity of user devices and the ever-growing
energy demands of mod- ern mobile apps. It aims
to bridge this gap by extending the promising
NFV paradigm to mobile applications in order to
exploit in-network resources.
In this talk, we present the overall design, key algorithms, and state-of-the-art technologies adopted in the INFv system, a careful study of over 20K Google Play apps, as well as thorough evaluations with realistic settings. In addition to a significant improvement in battery life (i.e., up to 6.9x energy reduction) and execution time (up to 4x faster), INFv has two distinct advantages over previous systems: 1) a non-intrusive offloading mechanism transparent to exist- ing apps; 2) an inherent network subsystem to effectively balance computation load and exploit the proximity of in- network resources. Both advantages together enable a scalable and incremental deployment of computation offloading framework in practice. |
| 11:35-12:00 |
Social-aware Hybrid Mobile Offloading: A Contribution for Edge and Fog Computing? (Slides )Huber Flores, University of Oulu
The exploitation of an opportunistic
infrastructure via computational offloading
is a critical component towards the adoption
of new paradigms such as edge and fog computing.
Computational offloading is a promising
technique to aid the processing of a mobile
device. By offloading a computational task a
device can save energy and increase the
performance of the mobile applications.
Unfortunately, in classical offloading systems,
the opportunistic moments to offload a task are
sporadic and short-term. In this talk, we explore
a hybrid system that merges cloudlet,
Device-to-Device (D2D) and remote cloud models
in order to increase the spectrum of
opportunistic offloading. We analyze and
evaluate our system in the wild and found
that in a realistic environment, a mobile
is always co-located to a source that provides
offloading support. This suggests that a device
can schedule the processing of tasks in
coordination with other devices, potentially
more powerful, instead of handling the
processing of the tasks by itself.
|
| 12:00-13:00 |
LunchLunch served in the Main Building Unicafé
restaurant
|
Edge Networking
Session Chair:
Sasu Tarkoma
,
University of Helsinki
| 13:00-13:25 |
Pervasive Computing at the network edge and beyond (Slides)Stephan Sigg, Aalto University We discuss the implementation of pervasive
services at the network edge and beyond. In
particular, we consider the calculation of
mathematical functions through simultaneous
superimposition in Pervasive environments. We
trade computational load for communication
load for parasitically, reader-powered, or
potentially backscatter smart devices.
Specifically, we present a communication
scheme by which mathematical computations can
be executed at the time of wireless
transmission."
|
| 13:25-13:50 |
Applications at the Edge (Slides)Hannu Flinck, Nokia Bell Labs "This talk describes how mobile edge
computing can bring value to applications by
using up-to-date information available only
at the edge of the radio network. Mobile Edge
Computing (MEC) platform provides additional
value to all parties – developers, operators
and end users through. In the context of
Cellular IoT applications MEC offers fast
reaction times, better reliability and
optimizations for congestion and overload
control of potentially massive amount signaling
caused by these applications. MEC can also proxy
and optimize application level data transport
protocols such as HTTP, TCP and Constrained
Application Protocol, etc. Edge video
orchestration that was deployed at Shanghai
International Circuit demonstrated its
capability clearly. Throughput guidance is a
tool to improve content delivery. It has been
tested extensively in large scale field trials.
Summary of the field trial results will be
provided."
|
| 13:50-14:15 |
Off-the-Shelf Wi-Fi and SDN: How to Create Virtual Wires in the Wi-Fi NetworksSeppo Hätönen, University of Helsinki The Software-Defined Networking mainly
revolves around the concepts of wires and ports.
In general, these do not exist in wireless
networks. Currently, the best proposals to
bring SDN and flow control to the wireless
networks require a dedicated virtual access
point per client. This requires extensive
software modifications to the APs and the APs
may have hardware limitations how many
virtual APs they can support. In this talk, I
present two simple ways to bring SDN to the
wireless networks using off-the-shelf consumer
and enterprise equipment with minimal changes
to the APs and their controlling software."
|
| 14:15-14:45 |
Coffee BreakCoffee, tea and snacks
|
Networking
Session Chair:
Yu Xiao, Aalto University
| 14:45-15:10 |
Open Connect Everywhere: A Glimpse at the Internet Ecosystem through the Lens of the Netflix CDN (Slides)Steve Uhlig, Queen Mary University of London
Netflix has become a worldwide video-streaming
platform and the source of a large amount of
the Internet traffic. It has achieved this
without Building its own datacentres, by
controlling a network of servers deployed at
Internet Echange Points (IXPs) and within
Internet Service Providers (ISPs). Despite its
wide success and novel approach to
infrastructure deployment, we have little
understanding of its deployments and operations.
Through extensive measurements, we reveal
Netflix's footprint, its traffic patterns and
volumes. Our analysis of Netflix's server
deployment exposes the diversity of the Internet
ecosystem world-wide. Our findings also suggest
that the specifics of each regional ecosystem,
coupled with the demand of each local market,
explain the different deployment strategies.
|
| 15:10-15:35 |
A Refactoring Approach for Optimizing Mobile Networks (Slides)Ashwin Rao, University of Helsinki
Mobile networks are expected to serve a wide
range of verticals such as Internet of
Things, however the Long Term Evolution (LTE)
network is optimized for basic mobile
operator services and offers limited services
to other verticals. Furthermore, the network
functions serving an LTE network are largely
implemented as dedicated single function
devices that exchange a large number of
signaling messages for replicating the state
of the mobile devices using the LTE network.
Modularizing these network functions would
enable a refactoring of the LTE network
allowing operators to compose networks that
adapt and evolve with the influx of
verticals. In this article, we present a new
approach for refactoring the network
functions serving LTE networks. In particular,
we show that it is possible to separate and
modularize the control and data planes of LTE
networks without modifying the mobile devices.
With the help of three use-cases, we show that
our refactoring approach can be leveraged to
compose a modular mobile network optimized for
the verticals using its services. We also show
that deploying network functions at the edge
significantly reduces the signals exchanged
within a mobile network.
|
| 15:35-16:00 |
StackMap: Low-Latency Networking with the OS Stack and Dedicated NICs (Slides)Lars Eggert , NetAPP
StackMap leverages the best aspects of
kernel-bypass networking into a new low-latency
OS network service based on the full-featured
TCP kernel implementation, by dedicating network
interfaces to applications and offering an
extended version of the netmap API for zero-copy,
low-overhead data path alongside control path
based on socket API. For small-message,
transactional workloads, StackMap outperforms
baseline Linux by 4 to 78 % in latency and 42
to 133 % in throughput. It also achieves
comparable performance with Seastar, a
highly-optimized user-level TCP/IP stack that
runs on top of DPDK.
|
| 16:00- |
Evening activitiesClick for details For interested participants: We will go and see
a jazz concert at Esplanadi (Link:
JazzEspa) and after that attend a craft beer
festival at the Central Railway Station (Link:
SOPP). The participants are required to pay
for themselves. The concert is free and drinks can
be purchased from the bar nearby. The beer festival
entrance fee is 10€ + 3 € for the glass which you
can keep or return for 2 € remimbursement. Drink
price varies, but is served in small tasting
portions. For additional details, feel free to
contact Lauri
Suomalainen by email or face to face at the
venue.
|
Thursday July 28, 2016
Edge Applications
Session Chair:
Eiko Yoneki,
University of Cambridge
| Time | Subject (Click for info) |
|---|---|
| 09:00-09:25 |
Off the Hook: Real-Time Client-Side Phishing Prevention System (Slides)Samuel Marchel, Aalto University
Phishing is a major problem on the Web. Despite
the significant attention it has received over
the years, there has been no definitive solution
. Existing solutions for steering users away
from phishing websites are typically
server-based and have several drawbacks: they
compromise user privacy, are not robust against
adaptive attackers who serve different content
at different times, and do not provide any
guidance to users after flagging a website as
a phish.
To address these limitations, we present a new phishing prevention system implemented as a client-side application and a browser add-on. It uses information extracted from website visited by the user to detect if it is a phish and warn the user. It also determines the target of the phish and offers to redirect the user there. The underlying technique for phishing detection and target identification relies on two core observations:
|
| 09:25-09:50 |
Enabling Fine-Grained Access Control for Android AppsYao Guo, Peking University
Many Android apps access sensitive personal data
such as location and contacts. The current
permission-based access control cannot control
how sensitive might be used within the same app.
For example, if an app obtains the permission to
access location, it can use it for both
navigation and advertisement. In my talk, I will
present out recent work on how to infer the
purpose of permission uses within an app, as
well as how to provide fine-grained access
control based on purposes and UI components.
|
| 09:50-10:15 |
Mobile Augmented RealityPan Hui, HKUST
Mobile Augmented Reality (MAR) is widely
regarded as one of the most promising
technologies in the next ten years. With MAR,
we are able to blend information from our senses
and mobile devices in myriad ways that were not
possible before. The way to supplement the real
world other than to replace real world with an
artificial environment makes it especially
preferable for applications such as tourism,
navigation, entertainment, advertisement, and
education. In this talk, I will first give an
overview of the MAR research in our HKUST-DT
System and Media Lab and then I will use two
systems that we have developed as examples to
illustrate the research challenges that we have
to face for our research. These two MAR systems
are Ubii – Ubiquitous Interface for Seamless
Interaction between Digital and Physical Worlds,
and Hyperion – A Wearable Augmented Reality
System for Text Extraction and Manipulation in
the Air. I will go through them in details.
|
| 10:15-10:45 |
Coffee BreakCoffee, tea and snacks
|
Mobile and Sensing Applications
Session Chair:
Pan Hui
, HKUST
| 10:45-11:10 |
Understanding the Cyber-Physical Space by Mobile Operator Big DataYong Li, Tsinghua University
By focusing on characterizing the mobile
traffic, web and information usage traces based
on large-scale and long-time mobile big data,
which is collected from the commercial mobile
operator with more than 10 thousand base
stations and 6.5 million users spanning over
some months, we qualitatively visualize and
quantitatively characterize the patio-temporal
human behaviors in the physical-cyber system
including mobility regularity, traffic
consumption patterns, social friendship
activity, online information and commodity
consumption, etc. Based on these fundamental
findings and credible models, we further
investigate how to utilize these important
insights on how to deal with the problems
encountered with the current mobile networks,
urban management, and robust physical-cyber
systems.
|
| 11:10-11:35 |
Contextual factors in mobile security and privacy policy enforcement (Slides)Markus Miettinen, TU Darmstadt
With the increasing popularity of
smartphone-based applications and mobile
computing, the role of context as a factor in
security and privacy enforcement is gaining in
importance, both as an asset to be protected and
as a factor to base security policy decisions
on.
With context we mean any observable features of a mobile device's ambient environment, which the device is able to observe using its on-board sensors. Examples of possible context modalities include, e.g., ambient light, noise level, temperature as well as WiFi and Bluetooth devices in the user's RF environment. While the use of context information opens great opportunities for developing apps, it also involves threats against the user's privacy, as many apps and device features require access to information about the user's context. Contextual data can potentially reveal a lot of private information about the user, if it is revealed to unauthorised parties. However, context can also help in adapting the behaviour of a mobile device and adjusting security and privacy policies according to specific situations. In this talk I will give an introduction to some recent work related to context-based policy enforcement and the use of context in security protocols, in particular as an enabler for proofs-of-presence that are not dependent on a particular infrastructure. |
| 11:35-12:00 |
Context-aware Real-time Population Estimation for Metropolis (Slides)Fengli Xu, Tsinghua University
Achieving accurate, real-time, and spatially
fine-grained population estimation for a
metropolitan city is extremely valuable for a
variety of applications. Previous solutions
look at data generated by human activities,
such as night time lights and phone calls, for
population estimation. However, these mechanisms
cannot achieve both real-time and fine-grained
population estimation because the data sampling
rate is low and spatial granularity chosen is
improper. We address these two problems by
leveraging a key insight — people frequently
use data plan on cellphones and leave mobility
signatures on cellular networks. Therefore, we
are able to exploit these cellular signatures
for real-time population estimation. Extracting
population information from cellular data
records is not easy because the number of users
recorded by a cellular tower is not equal to the
population covered by the tower, and mobile
users’ behavior is spatially and temporally
different, where static estimating model does
not work. We exploit context-aware city
segmentation and dynamic population estimation
model to address these challenges. We show that
the population estimation error is reduced by
22.5% on a cellular dataset that includes 1
million users.
|
| 12:00-13:00 |
LunchLunch served in the Main Building Unicafé
restaurant
|
Internet of Things
Session Chair:
Stephan Sigg
,
Aalto University
| 13:00-13:25 |
Securebox: A Platform for Smarter and Safer Networks (Slides)Ibbad Hafeez, University of Helsinki
The number of connected devices is increasing
exponentially, which has made the job of
managing and securing networks more complex and
demanding than ever before. In this paper, we
present a novel service-based solution for
securing edge networks that are poorly managed
and do not offer adequate security and
management features. Our proposed system
includes a smart gateway Securebox offering
advanced security and network management
features at device level granularity and a
Security and Management Service (SMS) which
provides services including traffic analysis
services, management services for remote device,
network and security policy etc. Instead of
tight coupling with hardware, our system
enables flexible and on-demand deployment of
security services to detect and block malicious
activities in the network. Our proposed system
is easy to deploy, manage and operate different
networks and resolves a number of challenges in
network security management domain.
|
| 13:25-13:50 |
Data Meet at Wireless Edge: Web Caching and IoT caseZhen Cao, Huawei
The increasing computing and storage capacity at
the wireless access nodes (eNodeB and Access
Points) creates opportunities for content
caching at the wireless edge and, therefore,
further reduction of content delivery
latency. However, realizing a large-scale
content caching at the wireless edge entails
significant challenges, due to the difficulties
of managing the vast amount of cached content
and handling redirections among the large number
of nodes. This talk covers a collaborative
content caching at wireless edge nodes by
coupling a low-false-positive hash table to
index the cached content with centralized
content redirection. This architecture is
applicable to both web caching and IoT cases.
|
| 15:50-14:15 |
Enabling Efficient Deep Learning-Based Inferencing on Wearable PlatformsSourav Bhattacharya, Nokia Bell Labs
Breakthroughs from the field of deep learning
are radically changing how sensor data are
interpreted. It is critical that the gains in
inference qualities that deep models afford
become embedded in the future generation of
mobile and IoT applications. However,
significant requirements of memory and
computational power have been the main
bottlenecks in the wide-scale adoption of
these novel computational techniques on resource
constrained wearable and mobile platforms.
In this talk, we present novel design principles that significantly lower the device resources (viz. memory, computation, energy) required by deep learning to overcome severe challenges to their mobile adoption. The main foundations of our approach are based on resource control algorithms and runtime resource scaling of deep model architectures, which are designed for the inference stage. Experiments show that the proposed optimizations allow even large-scale deep learning models to execute efficiently on modern mobile processors and significantly outperform existing solutions, such as cloud-based offloading. |
| 14:15-14:45 |
Coffee BreakCoffee, tea and snacks
|
Localization and Sensing
Session Chair:
Yong Li
,
Tsinghua University
| 14:45-15:10 |
Crowdsourced Indoor Mapping and Navigation (Slides)Yu Xiao, Aalto University
In this talk, we will present, iMoon, an
image-based indoor mapping and navigation
system. We will discuss the opportunities and
challenges of utilizing mobile crowdsensing for
creating fine-grained indoor maps with low cost,
and will introduce the results of our
performance tests and the progress of our user
studies.
|
| 15:10-15:35 |
Deviations of Check-in Locations and Human Mobility Trajectory (Slides )Xichen Wang, Tshingua University
As cluster analysis and visualization on massive
check-in data can clearly reveal the population
spatial distribution and other trajectory
characteristics, lots of work make further
efforts on finding geographic spatial
distribution, population scale, spatial
structure and functional area distribution.
Thus, the validity of check-in locations is of
important significance. This talk focuses on the
investigation of discrepancy of check-in and
network trajectory via a large scale Sina Weibo
data. First, we classify functional area
distribution through the human network accesses.
Then, we provide the observation that the
discrepancy of locations where people access
network, Sina Weibo and check-in locations.
Finally, we will compare the difference of
people posted on web via check-in and their
actual location.
|
| 15:35-16:00 |
Measurement-driven Capability Modeling for Mobile Network in Large-scale Urban EnvironmentJingtao Ding, Tsinghua University
For mobile networks diverse usage scenarios have
different capability requirements on connection
density and user experienced data rate, and
modeling such capability diversity is crucial
to the strategy evaluation in addressing the
problem of high traffic load and scalability of
network resources. Therefore, it is necessary to
build a capability model in two dimensions of
connection density and user experienced data
rate. This talk will be focused on addressing
this challenge based on an investigation of
network capability in large-scale urban
environment. There are mainly three parts:
|
| 19:00- |
Social Dinner at Restaurant SavuClick for details Join the three course dinner in the Restaurant Savu on the island Tervasaari. See the venue page for directions!
|
| Time | Subject (Click for info) |
|---|---|
| 09:00-09:25 |
Security in Connecting Devices to the Cloud (Slides )Tuomas Aura, Aalto University
New Internet of Things applications typically
require smart devices to be connected to the
cloud. I'll discuss some of the issues in
creating a secure connection where one side
may be a device that does not yet know its owner
and the other side is a virtual cloud service
with no physical presence. The configuration
of smart cloud-managed displays and the EAP-NOOB
protocol are used as a case study.
|
| 09:25-09:50 |
Notes on Mobile MalwareAlexey Kirichenko, F-Secure Corporation
F-Secure was one of the very first companies
that seriously invested into anti-malware
protection for mobile devices in the beginning
of 2000-s. We will briefly review the
developments in that domain at large and at
F-Secure and then talk about threat landscape
and challenges of the recent past.
|
| 09:50-10:15 |
Cryptocurrency for a Device-to-Device Ecosystem (Slides)Dimitris Chatzopoulos, HKUST
The popularity of digital currencies, especially
crypto-currencies, has been continuously growing
since the appearance of Bitcoin. Bitcoin is a
peer-to-peer (P2P) cryptocurrency protocol
enabling transactions between individuals
without the need of a trusted authority. Its
network is formed from resources contributed by
individuals known as miners. Users of Bitcoin
currency create transactions that are stored in
a specialised data structure called a block
chain. Bitcoin's security lies in a
proof-of-work scheme, which requires high
computational resources at the miners. These
miners have to be synchronised with any update
in the network, which produces high data traffic
rates. Despite advances in mobile technology,
no cryptocurrencies have been proposed for
mobile devices. This is largely due to the
lower processing capabilities of mobile devices
when compared with conventional computers and
the poorer Internet connectivity to that of the
wired networking. In this 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 replaces
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. It is based on opportunistic
networking rather than relying on infrastructure
and incorporates characteristics of mobile
networks such as users' locations and their
coverage radius in order to employ an
alternative proof-of-work scheme. Local coin
features (i) a lightweight proof-of-work scheme
and (ii) a distributed block chain.
|
| 10:15-10:45 |
Coffee BreakCoffee, tea and snacks
|
Big Data and Applications
Session Chair:
Tuomas Aura,
Aalto University
| 10:45-11:10 |
Carat: Before and After (Slides)Eemil Lagerspetz, University of Helsinki
While Carat is a research project at the
University of Helsinki, with the aim to collect
a large-scale smartphone usage dataset and
produce high quality research with it, the
project needs its flagship smartphone
applications to remain useful and attractive to
their users.
For this purpose, the Carat application has been redesigned with a new look and updated visuals. This talk will cover the new application and issues we have had to overcome in order to make it suit our needs on both iOS and Android. |
| 11:10-11:35 |
Efficient Large-Scale Graph Processing on Single Computer (Slides)Eiko Yoneki, University of Cambridge
One of challenges of emerging big data research
is to perform efficient and robust data
processing with limited memory/computation
power. I will introduce large-scale data
processing from various perspectives: what and
why large data, what technologies apply to big
data, and what are the main challenges. Then,
I would present our recent work on the graph
processing that have billions of vertices and
edges in a commodity single computer. Executing
algorithms results in access to the external
memory (e.g. SSD) and performance of I/O takes
an important role, regardless of the algorithmic
complexity or runtime efficiency of the actual
algorithm in use.
|
| 11:35-12:00 |
User privacy is not Preserved with ID-removed Anonymous Cellular Data (Slides)Zhen Tu, Tshingua University
A large number of cellular network accessing
records are generated by cellular users,
collected by cellular network operators and
applications running on mobile phones, and
publicly released for academic research or
privately sold for commercial purpose. One step
the mobile operators and application vendors
usually do before releasing is removing the
identification(ID) of each entry in the records.
Many cellular operators and applications vendors
believe that such anonymization is sufficient
for preserving the privacy of mobile users.
However, in this paper, we argue and prove that
simply removing the IDs is not sufficient for
preserving mobile users’ privacy. We develop a
mechanism that is able to extract the mobility
patterns of users from cellular records and
associate each record with a user, which means
the ID is recovered, according to their mobility
characteristics. We are able to associate
70%∼ 80% records with a user for two data sets
collected from both mobile application and
mobile operator side at the scale of several
thousands to tens of thousands users. We find
that the number of users released, the temporal
and spatial granularity, and the speed of user
movement are key factors that impact the privacy
of the ID-removed anonymized cellular data.
|
| 12:00-13:00 |
LunchLunch served in the Main Building Unicafé
restaurant
|
Group Discussion
| 13:00-13:25 |
City-Scale Localization with Telco Big DataWeixion Rao, Tongji University
It is still challenging in telecommunication
(telco) industry to accurately locate mobile
devices (MDs) at city-scale using the
measurement report (MR) data. The MR measure
parameters of radio signal strengths when MDs
connect with base stations (BSs) in telco
networks for making/receiving calls or mobile
broadband (MBB) services. In this paper, we
find that the widely-used location based
services (LBSs) have accumulated lots of
over-the-top (OTT) global positioning system
(GPS) data in telco networks, and can be
automatically used as training labels for
learning accurate MR-based positioning systems.
Benefiting from these telco big data, we deploy
a context-aware coarse-to-fine regression (CCR)
model in Spark/Hadoop-based telco big data
platform for city-scale localization of MDs.
Our experiments on real Shanghai city data show
that our model achieves a mean error of 110m and
a median error of 80m, outperforming the
state-of-art range-based and fingerprinting
localization methods.
|
| 13:25-15:00 |
Open DiscussionOpen discussion session to discuss
research ideas and collaborations.
|
| 15:00-15:30 |
Coffee BreakCoffee, tea and snacks
|
Closing Session
| 15:30-15:45 |
Closing SessionSasu Tarkoma & Aaron Yi Ding Conclusion for the workshop
|