|IC2E 2015 Tutorials Program
|IC2E 2015 Tutorials
- Tutorial 1: The Social Internet of Things (Monday Morning)
Antonio Iera (Uni Reggio Calabria, Italy),
Giacomo Morabito (Uni Catania, Italy),
Luigi Atzori (Uni Sassari, Italy)
- Tutorial 2: A Hands on Apache Storm Tutorial: for beginners to advanced users (Monday Afternoon)
Bobby Evans (Yahoo, USA)
- Tutorial 3: An Introduction to Cloud Benchmarking (Monday Afternoon)
David Bermbach (TU Berlin, Germany)
- Tutorial 4: MobiSocial (Mobile and Social) Data Management (Thursday Afternoon)
Mohamed Sarwat (Arizona State Uni, USA), Mohamed F. Mokbel (Uni of Minnesota, USA)
Antonio Iera (email@example.com)
Giacomo Morabito (firstname.lastname@example.org)
Luigi Atzori (email@example.com)
All market and technology studies forecast an explosive growth in the number of “things” which will be connected to the Internet. The resulting network is what is commonly known as the “Internet of Things” (IoT).
The IoT poses completely new challenges when compared to the traditional Internet which cannot be faced if the involved objects are just traditional “smart” objects. In fact, the extremely high complexity (huge number of nodes, extreme heterogeneity of their resources and capabilities, uncertainty on their trustworthiness, etc.) of the IoT environment cannot be faced by even very smart objects singularly. Social behavior is the answer found by several creatures to face the complexity of the surrounding environment. Accordingly, recently the concept of Social Internet of Things (SIoT) has been introduced and is the subject of a rapidly increasing research effort.
In this tutorial we will motivate the SIoT introduction, we will provide the basic relevant concepts, will survey the existing literature, and will describe a specific solution in details providing some exemplary applications.
Part 1: Theoretical discussion (2 hours)
- Basic concepts of Internet of Things
- Technologies and Architectures
- IoT open research issues
- Basic notions of Social Networks which may help in addressing IoT issues
- Basic notions of smart objects and their evolutions towards social objects
- Introduction of two different approaches for future IoT
- Social web of things
- Social Internet of things
- Making things socializing: motivations
- Definition of notion of “social relationship” between objects
- Definition of “degrees of social relationship”
- Components and reference architecture, Technological issues
- Applications and scenarios
- Overview of achievable performance
- Main related projects, main research results, main industrial experimentations
- Conclusions & Road Ahead
Part 2: Experiences on a real Social IoT platform (1 hour)
- Presentation of a sample Social IoT based platform
- Architecture, implementation, and Networking primitives
- API for mobile devices, Smart phones, Arduino, Raspberry, etc.
- Demo of simple experiments on the platform (with the participation of some of
the attendees, if they like)
- How a mobile device can join the community of devices
- How two devices, members of the community, discover themselves and
establish a relationship within the platform
Duration: ~180 min
Prof. Antonio Iera, Ph.D. graduated in Computer Engineering at the University of Calabria, Italy, in 1991 and received a Master Diploma in Information Technology from CEFRIEL/Politecnico di Milano, Italy, in 1992 and a Ph.D. degree from the University of Calabria, Italy, in 1996. From 1994 to 1995 he has been with the Mobile Network Division Research Center, Siemens AG – Munich, Germany and since 1997 with the University Mediterranea, Reggio Calabria, where he currently holds the positions of full professor of Telecommunications and Director of the ARTS - Laboratory for Advanced Research into Telecommunication Systems. He served as TPC member of several IEEE International Conferences and has been co-Guest Editor for different special issues in the IEEE Wireless Communications Magazine. Elevated to the IEEE Senior Member status in 2007. His research interests include: Next generation mobile systems, Advanced Systems for Personal Communications, RFID systems and Internet of Things.
Prof. Giacomo Morabito, Ph.D. received the laurea degree in Electrical Engineering and the PhD in Electrical, Computer and Telecommunications Engineering from the Istituto di Informatica e Telecomunicazioni, University of Catania, Catania (Italy), in 1996 and 2000, respectively. From November 1999 to April 2001, he was with the Broadband and Wireless Networking Laboratory of the Georgia Institute of Technology as a Research Engineer. Since April 2001 he is with the Dipartimento di Ingegneria Informatica e delle Telecomunicazioni of the University of Catania where he is currently Associate Professor. He serves (or has served) in the Editorial Boards of Wireless Networks, Computer Networks and IEEE Wireless Communications. Furthermore, he has been editor or co-guest editor of special issues of IEEE Transactions on Multimedia, IEEE Wireless Communication Magazine, Computer Networks and MONET. His research interests focus on analysis and solutions for broadband and wireless networks.
Prof. Luigi Atzori, Ph.D. is associate professor at the University of Cagliari (Italy). His main research topics of interest are in service management in next generation networks, with particular attention to architectural solutions for the Internet of Things, QoS, service-oriented networking, bandwidth management and multimedia networking. He has published more than 100 journal articles and refereed conference papers. Dr. Atzori has received the Telecom Italia award for an outstanding MSc thesis in Telecommunication and has been awarded a Fulbright Scholarship (11/2003-05/2004) to work on video streaming at the Department of Electrical and Computer Engineering, University of Arizona. He is senior member of IEEE, steering committee chair of the IEEE Multimedia Communications Committee (MMTC). He has been the editor for the ACM/Springer Wireless Networks Journal and guest editor for the IEEE Communications Magazine, Monet and Signal Processing: Image Communications journals. He is currently editor of the IEEE IoT Journal, Ad Hoc Networks Journal and Advances on Multimedia.
Bobby Evans (firstname.lastname@example.org)
Apache Storm is a popular low latency distributed stream processing framework. Apache Storm is used everywhere at Yahoo and at many other companies from automatically tagging every image uploaded to Flickr and analyzing trending search queries to monitoring production servers looking for problems. This hands on tutorial is divided into two parts. The first part covers the basics of Storm, its architecture, and walks you through writing a simple application (not just word count). The second part looks more at how to modify Storm and will walk you through adding in a new feature to storm.
Part 1: An introduction to Apache Storm (2 hours)
- Why Stream Processing is Important
- Apache Storm's Architecture
- Trident (Micro Batch Processing on Storm)
- Hands On Example
Part 2: Modifying Apache Storm (1 hour)
- Layout of source code
- Walk through of adding a new feature to Storm
Duration: ~180 min
Bobby Evans is the low latency data processing architect at Yahoo. He is a project management committee member on many big data Apache projects including Storm, Hadoop, Spark, and Tez. His team is responsible for delivering hosted Storm and Spark services to Yahoo.
David Bermbach (email@example.com)
Over the last few years, more and more Cloud Computing offerings have emerged ranging from compute, data storage, and middleware services over platform environments up to ready-to-use applications. Choosing the best offering for a particular use case, is a complex task which involves comparison and trade-off analysis of functional and non-functional service properties; for non-functional quality of service (QoS) properties, this is typically done via benchmarking. Today, a plethora of benchmarking solutions exist for different layers in the cloud stack (IaaS, PaaS, SaaS) which typically address a single QoS dimension – a holistic cloud benchmark even for a single layer in the cloud stack is still missing.
In this tutorial, we will give an overview of existing cloud benchmarking solutions and point-out ways in which these different benchmarks could be used in concert to actually compare clouds as a whole (i.e., for instance Amazon cloud vs. Google cloud) instead of analyzing isolated QoS dimensions of single cloud services.
Topics (1 hour + 1 hour)
- Requirements and key properties of benchmarks and metrics in general
- Performance benchmarks for cloud storage – from TPC to YCSB and recent developments
- Benchmarking approaches for advanced QoS dimensions (e.g., consistency, availability, elasticity)
- Benchmarking approaches for middleware services and compute clouds
- The future of benchmarking: New research directions, holistic cloud benchmarks, and cloud-specific benchmarks
Duration: ~120 min
Dr. David Bermbach is a senior researcher within the Information Systems Engineering research group at TU Berlin in Berlin, Germany. At TU Berlin, he is working on novel cloud benchmarking solutions, building on his strong expertise in the area of consistency benchmarking for cloud datastores. Prior to his current position, he worked as a researcher at KIT and as a lecturer at DHBW both in Karlsruhe, Germany. David has a Diploma in business engineering (2010) and a Ph.D. with distinction in computer science (2014) both from KIT. He received a best paper runner up award at IC2E 2014 and a best paper award at the 2nd International Conference on Cloud Computing, GRIDs, and Virtualization.
Mohamed Sarwat (firstname.lastname@example.org)
Mohamed F. Mokbel (email@example.com)
The rise of the Social Internet, in the past decade, stimulated the invention of human-centered technologies that study and serve humans as individuals and in groups. For instance, social networking services provide ways for individuals to connect and interact with their friends. Also, personalized recommender systems leverage the collaborative social intelligence of all users' opinions to recommend: books, news, movies, or products in general. These social technologies have been enhancing the quality of Internet services and enriching the end-user experience. Furthermore, the Mobile Internet allows hundreds of millions of users to frequently use their mobile devices to access their healthcare information and bank accounts, interact with friends, buy stuff online, search interesting places to visit on-the-go, ask for driving directions, and more. In consequence, everything we do on the MobiSocial Internet leaves breadcrumbs of digital traces that, when managed and analyzed well, could definitely be leveraged to improve life. Services that leverage Mobile and/or Social data have become killer applications in the cloud. Nonetheless, a major challenge that Cloud Service providers face is how to manage (store, index, query) MobiSocial data hosted in the cloud. Unfortunately, classic data management systems are not well adapted to handle data-intensive MobiSocial applications. The tutorial surveys state-of-the-art MobiSocial data management systems and research prototypes from the following perspectives: (1) Geo-tagged Microblog search, location-aware and mobile social news feed queries, and GeoSocial Graph search, (2) Mobile Recommendation Services, and (3) Geo-Crowdsourcing. We finally highlight the risks and threats (e.g., privacy) that result from combining mobility and social networking. We conclude the tutorial by summarizing and presenting open research directions.
Session Details (Half Day):
Part 1 (1 hour)
In the first part, we start by giving a quick overview of social networking services (e.g., Facebook, Twitter), their evolution, and how they impact the society. Similarly, we explain through examples and case studies how the widespread of mobile devices changes the computing paradigm in a way that impacted our daily life. We then illustrate how the marriage of both social networking and mobility technologies has led to the rise of location-based social networking systems. We give a brief history of several attempts to combine social networking and mobility. Therefore, we explain the richness of data generated by merging both social networking and mobility: (1) Social Networking data: represents the friendship between different users (usually represented by a social graph) as well as all sorts of social interactions between users. (2) Spatial/Spatio-temporal data: represents the users geo-locations, venues (e.g., restaurant, gym, and shopping mall) geo-locations and information about users visiting different places at different times. (3) Users Opinions data: represents how much a user likes the places she visits by expressing (e.g., Alice visited restaurant A and gave it a rating of five over five). We then illustrate how different mixes of this data trilogy has been leveraged to explore new trends and by developers to build novel mobile applications.
Part 2 (2 hours)
In the second part of the tutorial, we present the state-of-the-art research in managing MobiSocial data, from the following perspectives: (1) GeoSocial Search and Query Processing: That incorporates both the geo-location and the social awareness in answering queries. We then present several indexing and query processing algorithms that efficiently access geo-tagged social media (e.g., tweets, news feed, social graph entities). (2) Mobile Recommendation Services: We present recent studies which show that geo-location matters in recommender systems, and we manifest several techniques to incorporate the spatial/spatio-temporal information and users opinions data side by side in traditional recommender systems. We also highlight the research works that leverage GeoSocial data points and trajectories for travel and itinerary recommendations. (3) Location-aware Crowdsourcing: We give an overview of the Volunteered Geographic Information (VGI) area and we survey the recent papers that address the Crowdsourcing topic from a geographic perspective. For all aforementioned topics, we present results from recent research work, case studies from hot mobile applications, and the anatomy of built systems. Then, we highlight the main risks that result from combining social networking and mobility (e.g., privacy). Finally, we introduce possible research directions to the audience and we also manifest several resources, e.g., data, software tools, that assist the audience in starting their own research in social networking and mobility.
Duration: ~180 min
Dr. Mohamed Sarwat is an Assistant Professor of Computer Science at Arizona State University. Before joining ASU in August 2014, Mohamed obtained his MSc and PhD degrees in computer science from University of Minnesota in 2011 and 2014, respectively. His research interest lies in the broad area of data management systems. Mohamed is a recipient of the University of Minnesota Doctoral Dissertation Fellowship. His research work has been recognized by the “Best Research Paper Award” in the International Symposium on Spatial and Temporal Databases (SSTD 2011) and a “Best of Conference” citation in the IEEE International Conference on Data Engineering (ICDE 2012). For more details, please visit Mohamed Sarwat home page.
Mohamed F. Mokbel (Ph.D., Purdue University, MS, B.Sc., Alexandria University) is an associate professor in the Department of Computer Science and Engineering, University of Minnesota. His current research interests focus on providing database and platform support for spatio-temporal data, location based services 2.0, personalization, and recommender systems. His research work has been recognized by four best paper awards at IEEE MASS 2008, IEEE MDM 2009, SSTD 2011, and ACM MobiGIS Workshop 2012, and by the NSF CAREER award 2010. Mohamed is/was general co-chair of SSTD 2011, program co-chair of ACM SIGSPAITAL GIS 2008-2010, and MDM 2014, 2011. He has served in the editorial board of IEEE Data Engineering Bulletin, Distributed and Parallel Databases Journal, and Journal of Spatial Information Science. Mohamed is an ACM and IEEE member and a founding member of ACM SIGSPATIAL. For more information, please visit Mohamed F. Mokbel home page