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26th Asian School
Venue: intERLab, AIT
The Asian School of Computer Science is conducted annually by Asian Institute of Technology, Thailand. The purpose of the school is to provide short courses conducted by leading experts in the computer science fields enabling local participations from the Asia Pacific region.
Topics: IoT and Big Data Analytics
IoT-LAB: a First Class Scientific Tool for Large Scale IoT Experiments
We present a precise description IoT-LAB. IoT-LAB provides a very large scale infrastructure facility suitable for testing small wireless sensor devices and heterogeneous communicating objects. IoT-LAB features over 2700 wireless sensor nodes spread across six different sites in France. Nodes are either fixed or mobile and can be allocated in various topologies throughout all sites. A variety of wireless sensors are available, with different processor architectures (MSP430, STM32 and Cortex-A8) and different wireless chips (802.15.4 PHY @ 800 MHz or 2.4 GHz). In addition, “open nodes” can receive custom wireless sensors for inclusion in IoT-LAB testbed.
IoT-LAB's main and most important goal is to offer an accurate open access multi-users scientific tool to support the design, development tuning, and experimentation of real large-scale sensor network/IoT applications. The hardware and software architectures that allow to reserve, configure, deploy embedded software, boot wireless sensor nodes and gather experimental data and monitoring information are described in detail. We also present demonstration examples to illustrate the use of the IoT-LAB testbed.
We introduce the participant to modeling and processing of big data. We will first introduce MapReduce and Hadoop as a flexible tools for analyzing large dataset. We thereafter will describe algorithmic for big data analysis and models calibrations. We will describe locality-sensitive hashing, sparse matrix, dimensionality reduction and illustrate using recommender systems and computational advertisement. Topics of the course include MapReduce, Hadoop, Locality-Sensitive Hashing -- Basics + Applications, Distance Measures, Nearest Neighbors, Frequent Itemsets, Data Stream Mining, Analysis of Large Graphs, Dimensionality Reduction, Clustering, Computational Advertisingm, Recommender Systems.
About the Speakers:
Eric Fleury is a professor at ENS Lyon, Computer Science Department since 2007. The ENS Lyon is one of the four Ecolesnormalessupérieures in France (more about ENS Lyon...).. Eric Fleury is the scientific leader of the INRIA D-NET research team / INRIA Grenoble - Rhône-Alpes research centers . D-NET team is located at ENS Lyon and hosted by IXXI. Eric is also in the scientific board and in the steering comitee of the IXXI: Complex Systems Institute.
From 2003 to 2007, Eric Fleury was a professor at the INSA de Lyon.
He received his Master degree in Computer science from EcoleNormaleSupérieure de Lyon, France in 1992. He received his PhD, degree in Computer Science, 1996 in communication and routing in distributed architectures from EcoleNormaleSupérieure de Lyon , and theHabilitation a Diriger des Recherches specializing in group communication in computer networks in 2002 from the Insa de Lyon. From 1998 to 2003, he was a full research officer at INRIA (the french national institute for research in computer science and control). First in the RESEDAS project in Nancy and then in the ARES project since 2002.
His research interests are in the area of wireless network (ad hoc, sensor), pervasive communication and next generation communication network. Until 2007, he was co-heading the INRIA ARES project and he was the co-director of the CITI Lab (Insa de Lyon). He is coordinator for ENS Lyon, UCBL and INSA de Lyon of the research cluster ISLE (n°2) Rhône-Alpes (Computer, Signal and embeded systems)
Kavé Salamatian, has been a full professor of computer science at University of Savoie from 2009. His main areas of researches are Internet measurement and modelling and networking information theory. He was previously reader at Lancaster University, UK and associate professor at University Pierre et Marie Curie. Kavé has graduated in 1998 from Paris SUD-Orsay university, where he worked on joint source channel coding applied to multimedia transmission over Internet for his PhD. In a former life, he graduated with a MBA, and worked on market floor as a risk analyst and on enjoyed being an urban traffic modeler for some years.