Tutorial 1: Distributed Algorithms for Wireless Multihop Networks

Tutorial 2: Dynamic Spectrum Management in Cognitive Radio Networks

Tutorial 3: Computing with Directional Antennae in WSNs

Tutorial 4: Scalable Data Management and Storage on the Cloud: State of the Art and Emerging Trends

Tutorial 1: Prof. Roger Wattenhofer

Computer Engineering and Networks Laboratory,
ETH Zurich, Switzerland

Distributed Algorithms for Wireless Multihop Networks


Abstract: In the first part of the tutorial we learn the fundamentals of distributed algorithms, also known as message passing algorithms, or the "local" model. A distributed system is represented by a graph. We would like to solve classic combinatorial optimization problems by having the nodes of the graph just talk to their neighbors in the graph. As a running example throughout the first part of the tutorial we will use the so-called Maximal Independent Set (MIS) problem. Together, we figure out and discuss simple deterministic and randomized algorithms to solve the MIS problem in a distributed context. We will discuss applications of the MIS problem, such as coloring. Then we look at some of the state of the art results of the MIS problem and discuss the lower bound technique by Linial, the upper bound technique by Cole and Vishkin, and finally the lower bound by Kuhn et al. In the remainder of the first part of the tutorial we will also look at related problems, and the most important open questions in this area.
In the second part of the tutorial we will look at how to apply the lessons learned from the first part in the context of wireless multihop networks, i.e. ad hoc, sensor, or mesh networks. In particular we discuss in what sense the physical reality is different from the pure local model learned in the first part. Towards this end we will discuss models for connectivity in wireless multihop networks, various interference models, and finally communication models. Again, we will discuss some of the most important open problems.

Speaker's Bio: Roger Wattenhofer is a full professor at the Information Technology and Electrical Engineering Department, ETH Zurich, Switzerland. He received his doctorate in Computer Science in 1998 from ETH Zurich. From 1999 to 2001 he was in the USA, first at Brown University in Providence, RI, then at Microsoft Research in Redmond, WA. He then returned to ETH Zurich, originally as an assistant professor at the Computer Science Department.
Roger Wattenhofer's research interests are a variety of algorithmic and systems aspects in computer science and information technology, currently in particular wireless networks, multi-core systems, peer-to-peer computing, and social networking. He publishes in different communities: distributed computing (e.g., PODC, SPAA, DISC), networking (e.g., MobiCom, MobiHoc, SenSys, IPSN, HotNets), or theory (e.g., STOC, FOCS, SODA, ICALP).

Tutorial 2: Prof. Mainak Chatterjee

Department of Electrical Engineering and Computer Science,
University of Central Florida, USA

Dynamic Spectrum Management in Cognitive Radio Networks


Abstract: Radio spectrum has traditionally been allocated in a static manner. However, recent studies have shown that parts of the radio spectrum are over-utilized while some parts are under-utilized. In order to break away from the inflexibilities and inefficiencies of long-term static allocations, the concept of dynamic spectrum access and management using cognitive radios is being investigated and is expected to be a significant component in next generation wireless systems. It is currently of big interest to radio engineers, policy makers and economists involved in the design, analysis, and optimization of next generation wireless access systems and networks.
In this tutorial, we will first motivate the concept and use of dynamic spectrum access. We will then see how this new paradigm can be made viable through the use of cognitive radios. Our main focus will be Spectrum Management i.e., dynamic spectrum allocation and sharing among primary and secondary users. We will discuss issues related to MAC and distributed/centralized channel access. After a brief introduction to game theory, we will should how game theory can be used as an effective tool to model the competition and cooperation among various cognitive networks. We will also show how different auction models can be used to find the equilibrium price for spectrum trading. We will conclude with IEEE 802.22 which is a cognitive radio based wireless regional area network technology.

Speaker's Bio: Mainak Chatterjee is an Associate Professor in the department of Electrical Engineering and Computer Science, University of Central Florida, Orlando. He received the BSc degree in physics (Hons.) from the University of Calcutta, the ME degree in electrical communication engineering from the Indian Institute of Science, Bangalore, and the PhD degree from the Department of Computer Science and Engineering from the University of Texas at Arlington. His research interests include economic issues in wireless networks, applied game theory, cognitive radio networks, and mobile video delivery. He has published over 100 conferences and journal papers. He got the Best Paper Award in IEEE Globecom 2008. He is the recipient of the AFOSR sponsored Young Investigator Program (YIP) Award. He co-founded the IEEE Workshop on Mobile Video Delivery (MoViD). He serves on the editorial board of Elsevier's Computer Communications and Pervasive and Mobile Computing Journals. He has served as the TPC Co-Chair of several conferences including IEEE WoWMoM 2011, WONS 2010, IEEE MoViD 2009, Cognitive Radio Networks Track of IEEE Globecom 2009 and ICCCN 2008. He also serves on the executive and technical program committee of several international conferences.

Tutorial 3: Prof. Evangelos Kranakis

School of Computer Science,
Carleton University, Ottawa, Canada

Computing with Directional Antennae in Wireless Sensor Networks


Abstract: Directional and omnidirectional are the two types of antennae being used in sensor networking. The former emit greater power in one direction thus achieving increased transmission range and performance as well as reduced interference from unwanted sources. On the contrary, omnidirectional antennae radiate power uniformly in all directions. Regardless of the type of antenna being used the transmission cost of each antenna is proportional to the coverage area of the antenna. By providing a comparative analysis of directional vs omnidirectional antennae the purpose of the tutorial is to understand how the use of directional antennae can improve energy consumption, security, and topology control. In the first part of the tutorial we introduce basic concepts and ideas for 2D and 3D antennae and look at how directional antennae reduce energy consumption and improve security of a sensor network. In the second part, we look specifically at topology control issues, in particular connectivity, neighbor discovery, coverage, routing, and stretch factor, In both parts of the tutorial we discuss and analyze several recent algorithms and study trade-offs on the beam width, range and number of antennae being used per sensor. We also provide directions for future research and give several challenging recent open problems.

Speaker's Bio: Evangelos Kranakis received his B.Sc. in Mathematics from the University of Athens, Greece, and a Ph.D. in Mathematics from the University of Minnesota, USA. He has been in the Mathematics Department of Purdue University, USA, Mathematisches Institut of the University of Heidelberg, Germany, the Computer Science Department of Yale University, USA, at the Computer Science Department of the Universiteit van Amsterdam, and at the Centrum voor Wiskunde en Informatica (CWI) in Amsterdam, The Netherlands. He joined the faculty of the School of Computer Science of Carleton University in the Fall of 1991. He has published in the analysis of algorithms, bioinformatics, communication and data (ad hoc and wireless) networks, computational and combinatorial geometry, distributed computing, and network security. He was director of the School of Computer Science from 1994 to 2000 and has been in the Research Management Committee of MITACS (Mathematics of Information Technology and Complex Systems) since 1998.

Tutorial 4: Dr. Anwitaman Datta

School of Computer Engineering,
NTU, Singapore

Dr. Frederique Elise Oggier

School of Physical and Mathematical Sciences,
NTU, Singapore

Scalable Data Management and Storage on the Cloud: State of the Art and Emerging Trends


Abstract: The rapid growth of the Internet, particularly fuelled by social media and Web 2.0 applications - has necessitated new, scalable mechanisms for data management and storage. These techniques have subsequently organically become the key enabling technologies for the cloud infrastructure. In particular, distributed file systems, primarily based on distributed key-value stores have emerged as a key ingredient facilitating the core data management needs in many such systems - such as Amazon's Dynamo, Facebook's Cassandra, Yahoo's PNUTS!, Google's BigTable, etc. to name a few prominent ones, while abstractions such as map-reduce (and Hadoop framework) and NoSQL systems have emerged for manipulation and querying such stored information. The first half of the tutorial will introduce these state-of-the art data-management mechanisms, and the associated open challenges.
Redundancy is essential for fault-tolerance, however the overheads of storing the huge volume of data involved - in terms of storage space, as well as bandwidth and computational needs, to create and then maintain the redundancy over time, in presence of faults that can occur randomly and continuously, can be huge. Traditional erasure coding techniques, which were originally developed for communication centric applications, help reduce the storage overhead, but do not perform well in terms of repair traffic or necessary computational overheads. New coding techniques tailor made for storage centric applications - some based on network coding concepts (regenerating codes), as well as others (such as Pyramid and self-repairing codes) are emerging - and are posed to play a vital role in providing scalable solutions for storing huge volume of data. The second part of the tutorial will provide a summary of these emerging mechanisms.

Speakers' Bio: Anwitaman Datta did his PhD at EPFL Lausanne before moving to NTU Singapore in 2006, where he is currently an Assistant Professor in the School of Computer Engineering. He is interested in large scale networked distributed information systems and social collaboration networks, self-organization and algorithmic issues of these systems and networks and their scalability, resilience, security and performance. He won the best paper awards at IWSOS 2006, ICDCS 2007 and ICDCN 2011, and is one of the recipients of HP Labs Innovation Research Program award 2008.

Frederique Oggier received her degree Diplome in Mathematics and Computer Science in 2000 from the University of Geneva, Switzerland. She then joined the Swiss Federal Institute of Technology, Lausanne (EPFL), where she graduated from the Doctoral School in Communication Systems (2001), and completed her Ph.D. thesis in Mathematics (2005). She was a postdoctoral visitor at the California Institute of Technology (CalTech) from 2005 till 2007, and at the Research Center for Information Security (RCIS) in Tokyo, Japan, from 2007 to 2008. She is currently an Assistant Professor at the School of Physical and Mathematical Sciences, Nanyang Technological University (NTU), Singapore. She is a recipient of the Singapore NRF Fellowship. Her main research interests are in applied algebra to coding problems arising in wireless communications, distributed networked storage as well as information theoretic security.