The 5th ACM HotPlanet Workshop
LT2 (G/F), Yasumoto International Academic Park, The Chinese University of Hong Kong
Friday, August 16, 2013
Technical Program
Hamed Haddadi and Pan Hui
Smartphones, Crowds, and the Cloud: Population Guided Sensing Systems
Nic Lane (Microsoft Research Asia)
What’s in a Name? Decoding Router Interface Names
Joseph Chabarek and Paul Barford
Trace Selection for Improved WLAN Monitoring
Matteo Sammarco, Miguel Elias M. Campista and Marcelo Dias de Amorim
Internet Atlas: A Geographic Database of the Internet
Ramakrishnan Durairajan, Subhadip Ghosh, Xin Tang, Paul Barford and Brian Eriksson
A Framework for Monitoring and Measuring a Large-Scale Distributed System in Real Time
Lei Zhan, Tom Z. J. Fu, Dah Ming Chiu and Zhibin Lei
Efficient Social Network Data Query Processing on MapReduce
Liu Liu, Jiangtao Yin and Lixin Gao
PIXS: Programmable Intelligence for Cross-Platform Socialization
Pili Hu, Junbo Li and Wing Cheong Lau
Extrapolating Sparse Large-Scale GPS Traces for Contact Evaluation
Andrea Hess and Jörg Ott
Metric Convergence in Social Network Sampling
Christian Doerr and Norbert Blenn
Lessons Learned from the NetSense Smartphone Study
Aaron Striegel, Shu Liu, Lei Meng, Christian Poellabauer, David Hachen and Omar Lizardo
Information Bazaar: a Contextual Evaluation
Bernadette Kamleitner, Stephan Dickert, Marjan Falahrastegar and Hamed Haddadi
It’s Tea Time: Do You Know Where Your Mug Is?
Robert Moore, Bernard Firner, Chenren Xu, Richard Howard, Richard Martin and Yanyong Zhang
Introduction
The last decade has seen a rapid, planet-scale growth in deployment and usage of smart mobile devices, ambient sensors, smartphone applications and advanced communication technologies. This era has prompted for large-scale, planet-wide data collection, storage, processing and dissemination technologies, advancing our knowledge about human behaviour and interactions at a planetary scale. Evolution of such technologies and methodologies, in addition to the high investments in Internet of Things (IoT) deployments in Asia, has inherently led to a number of security, privacy and ethical issues as well as new systems, networking, and application challenges.
This 5th ACM HotPlanet workshop will bring together networking, wireless, mobile computing and systems research to understand the challenges ahead and advance the dialogue on topics related to large-scale measurements and big data analytics centred around individuals. It aims to attract publications on: novel data collection, data analysis and knowledge-discovery methodologies; showcasing demonstrations of innovative real-world ambitious measurement technologies, applications, and large-scale deployment experiences; innovative large-scale mobile sensing systems and big social media data and location traces analytics.
Keynote Speaker
Speaker: Nic Lane — Microsoft Research Asia
Title: Smartphones, Crowds, and the Cloud: Population Guided Sensing Systems
Sensor-enabled smartphones are creating new application domains and transforming existing ones — from mobile health to quantified-self, mobile sensing is radically changing the way we collect and mine information about people’s activities, contexts, and social networks. A number of challenges stand in the way of delivering mobile sensing to the masses. For example, how do we develop mobile sensing systems that are capable of dealing with population diversity at scale; more specifically, how can conventional approaches to classifying high-level human behavior cope with the level of diversity among users (e.g., demographics, behavioral patterns, and lifestyle) and contexts found in large-scale systems.
Over the last few years I have been spearheading the development of population guided sensing systems. These systems are designed to have a deep understanding of both individual and group behaviors and utilize this information to create symbiotic relationships between users and systems. In this talk, I will present two key ideas that can help scale mobile sensing systems from 100s of people to potentially 100s of millions based on population guided sensing. The first idea, Community Similarity Networks (CSN), is an activity recognition framework that incorporates inter-person similarity measurements into the classifier training process. CSN exploits crowdsourced sensor data to personalize classifiers with data contributed from other similar users. Second, I will discuss CrowdSense@Place (CSP), which combines crowd labeling and data collection with a series of multi-modal classifiers to link place visits to place categories (e.g., shopping, gym, and restaurant). These techniques combine to move mobile sensing forward: nailing it before we scale it.
Bio: Nic Lane is a researcher at Microsoft Research Asia (MSRA) working in the mobile and sensing systems group (MASS). Nic received his Ph.D. from Dartmouth College (2011) where he worked with his co-advisors Andrew Campbell and Tanzeem Choudhury at the intersection of machine learning and mobile sensing. His dissertation helped pioneer community-guided techniques for learning models of human behavior that enable mobile sensing systems to better cope with diverse user populations encountered in the real-world. Nic is an experimental computer scientist who builds novel mobile sensing applications and systems based on well-founded computational models. His work has received a number of awards including best paper awards from Ubicomp ‘12, Mobicase ‘12 and PhoneSense ‘11, and a best paper nomination from Ubicomp ‘11. Nic currently serves as member of the TPC of Mobisys, Ubicomp and Sensys.
Topics of Interest
- Big Data analytics (Social Media , mobility traces, prediction techniques, etc.)
- Mobile Sensing systems
- Big Data Privacy & Security
- Large scale measurement methodologies
- Novel social & sensing application
- Open source and virtualized sensing infrastructure
- Cloud computing paradigms for decentralized analysis
- Incentive models for encouraging users and businesses to collect and contribute data
- Profiling, personalisation, geotargeting
- Programming paradigms for large scale data collection
- Data quality issues
- Internet of Things
- Smart energy-aware systems
- Large scale mobile application market experience
- Regulatory, legal and ethical issues in planet-wide data collection
Submission Instructions
HotPlanet 2013 accepts original submissions which are not under review, or published at, previous workshops, conferences, or journals. Submissions may not exceed 6 pages double column, including figures, tables, references, and appendices. Authors are required to use the ACM template for submissions: http://www.acm.org/sigs/publications/proceedings-templates
All submissions will be evaluated via a single-blind review process: please include author names and affiliation in the submission. Register and submit your paper at https://www.easychair.org/conferences/?conf=hotplanet2013
For the first time this year we will introduce a 3-minute-madness session, where participants are invited to present their 3-minute elevator pitch/idea/comment/insight into the topics discussed in the workshop and of interest to participants.
All papers and 3-minute-madness idea presentations will be considered for the best paper and best idea award. The winners will receive a cash award.
Important Dates
Paper Submissions Due:
March 23, 2013 11:59 EST
Acceptance Notification:
April 28, 2013
Camera Ready:
May 25, 2013
Workshop Date:
August 16, 2013
Organizers
- General Chair:
Pan Hui
HKUST/T-labs
- Technical Program Co-Chairs
Emiliano Miluzzo
AT&T Labs - Research, USA
Hamed Haddadi
Queen Mary University of London, UK
- Technical Program Committee
Ian Brown
Oxford Internet Institute, UK
Aline Carneiro Viana
INRIA, France
Wing Cheong Lau
CUHK, Hong Kong
Christos Efstratiou
University of Cambridge, UK
Raghu Ganti
IBM Research, USA
Tristan Henderson
University of St. Andrews, UK
Pan Hui
HKUST/T-labs
Mohamed Ali Kaafar
INRIA/NICTA
Nic Lane
MSR-A, China
Hengchang Liu
UIUC, USA
Mirco Musolesi
University of Birmingham, UK
Konstantina Papagiannaki
Telefonica, Spain
Weixiong Rao
Helsinki University, Finland
Junehwa Song
KAIST, Republic of Korea
Alexander Varshavsky
AT&T Labs - Research, USA
