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Home > Node > Optimization of mobile crowd-sensing and recommender system platforms
Optimization of mobile crowd-sensing and recommender system platforms
8 February 2016 - 12:00pm
Ponente(s): 
Iordanis Koutsopoulos, Associate Professor at the Department of Informatics, Athens University of Economics and Business (AUEB)
Lugar: 

Room 1.1/2 IMDEA Networks Institute, Avda. del Mar Mediterráneo 22, 28918 Leganés – Madrid

Organización: 
NETCOM Research Group (Telematics Engineering Department, UC3M); IMDEA Networks Institute

The main themes of the talk are the optimization of mobile crowd-sensing and recommender system platforms from the point of view of the system designer. In the first part of the talk, we first discuss optimization of mobile crowd-sensing campaigns in terms of total expected quality for a set of tasks to be accomplished, and in terms of compensation cost to task contributors. A new twist is the decision-making model of users. We profile users with respect to the impact of different task attributes on their decision-making. We draw on logistic-regression techniques from machine learning to learn from past data and then perform incentive targeting. Another issue to be tackled is strategic behavior of users that may falsify information they provide to the system.

In the second part of the talk, we take a first step towards rethinking recommender systems by exploiting the expected social-network diffusion and withholding recommendation of items that will anyway reach a user through reposting. We formulate the problem of maximizing total user engagement as a post allocation problem and evaluate our approach through real datasets. In the last part of the talk, we outline another direction of interest, namely dynamic computation allocation for streaming data in time-varying wireless networks. This problem is a core one in fog computing architectures where streaming data analytics needs to be performed. It involves dynamic determination of nodes that perform the computation, routing of raw data from sources to computation nodes, and routing of processed data to the destination. We seek to characterize the network performance limits in attainable computation rate. We conclude with a high-level overview of few other research areas and challenges that may constitute our research agenda in the next few years.

About Iordanis Koutsopoulos

Iordanis Koutsopoulos is an Associate Professor at the Department of Informatics, Athens University of Economics and Business (AUEB). He was Assistant Professor (2013-2016) with AUEB. Before that, he was Assistant Professor (2010-2013) and Lecturer (2005-2010) with the Department of Computer Engineering and Communications, University of Thessaly. He received the single-investigator European Research Council (ERC) competition runner-up award for the project RECITAL: Resource Management for Self-coordinated Autonomic Wireless Networks (2012-2015). His research interests are in the general area of network control and optimization, with applications on wireless networks, social and community networks, crowd-sensing systems, smart-grid and cloud computing.

Iordanis Koutsopoulos (S’99-M’03-SM’13) received the Diploma degree in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), Greece, in 1997 and the M.S and Ph.D. degrees in Electrical and Computer Engineering from the University of Maryland, College Park (UMCP), MD, USA, in 1999 and 2002, respectively.

Personal website

This event will be conducted in English