Models of user traffic demand are fundamental inputs to the design and engineering of data networks. This talk addresses this requirement in the context of large-scale wireless infrastructures using real-measurement (i.e., empirical) data.

Our proposed models are validated over two different monitoring periods at various levels of spatial aggregation, from individual access points (APs) to the whole network. Based on these models, we generated synthetic traffic for various spatio-temporal granularities and compared them with the empirical data. The comparison clearly illustrates the trade-off between model scalability and accuracy in capturing local-scale traffic dynamics.

This talk will present the evaluation of these models using also systems-based benchmarks, such as the throughput, goodput, delay and jitter per flow in a hotspot AP. Specifically, the performance of the proposed models is very close to the one produced when the empirical traces are used. Moreover, the performance of popular models deviates substantially from the empirical data. These results were verified via both simulations and emulations and using tcp- and udp-based scenarios. The analysis will also highlight the impact of flow sizes, flow interarrivals, and application mixes on the wireless lan performance. Finally, a flexible framework that can be used to generate synthetic traces with different workload characteristics for various performance analysis studies will be presented.

Bio:
Maria Papadopouli (Ph.D. Columbia University, October 2002) is an assistant professor in the Department of Computer Science at University of Crete, a research associate in FORTH-ICS, and an adjunct professor in the University of North Carolina at Chapel Hill (UNC). From July 2002 until June 2006, she was a tenure-track assistant professor at UNC (on leave from July 2004 until June 2006). Her current research interests are in mobile peer-to-peer computing, wireless networks, network modelling and performance analysis, and pervasive computing. She has co-authored a monograph on Peer-to-Peer Computing for Mobile Networks: Information Discovery and Dissemination (Springer 2008). In 2004 and 2005, she was awarded with an IBM Faculty Award.

More information about her research activities can be found at http://www.ics.forth.gr/mobile/.

NetHood (nethood.org) is a new cross-disciplinary project aiming to bring together researchers from social sciences, urban planning, computer science, and networking. The purpose of this collaboration is to design self-organizing online neighborhood communities that will promote face-to-face interactions and a healthy life style, and that will empower local communities with a customizable social communication tool, which will respect their privacy requirements and independence. In this presentation I motivate the need to create such hybrid communities, bridging the virtual with the physical space in the city, and identify some challenging research questions that the Nethood project wishes to address. I then discuss the trade-offs related to the requirement of self-organization at the application and network layers. I focus on the incentives required for users to participate, build trust and share different types of resources, the more distributed the system architecture becomes. I argue that social software can play a critical role for stimulating intrinsic instead of extrinsic human motivations, and contribute this way to both encouraging resource sharing and shaping a strong sense of community. Based on lessons learned from existing web-based online communities, I identify some important principles that should guide the design of social software for building successful self-organizing hybrid communities.

Bio:
Panayotis Antoniadis is a postdoctoral fellow at UMPC Paris Universitas (Paris 6). His main research contributions are in the economic modelling and incentive mechanisms for peer-to-peer systems (2002–2006) and in distributed scheduling algorithms for high-speed switches (2000).He is currently working on resource management mechanisms and federation policies for shared network facilities (IST project Onelab). He is also exploring the role of social software, wireless networks and peer-to-peer systems on the design of sustainable hybrid neighborhood communities and urban planning (project nethood). He received his B.Sc. and M.Sc. degree from the Computer Science Department of University of Crete in 1998 and 2000 respectively and his Ph.D. degree from the Department of Informatics of Athens University of Economics and Business in 2006.

Despite almost a decade of research on peer-to-peer systems, and much interest, potential and development of structured overlays, large scale deployment of such overlays out in the open has generally remained elusive. The first half of this talk will highlight some of the outstanding challenges for such large-scale deployment and recent results and mechanisms to address the same – including on decentralized bootstrapping, ring-less routing and securing structured overlays from various malicious and uncooperative behaviors.

The later half of the talk will delve into some ongoing initiatives (occasionally disjoint from each other) to realize social networking and collaborative applications in a decentralized setting, including using aforementioned structured overlay based infrastructure.

Bio:
Anwitaman Datta did his PhD at EPFL Lausanne before moving to NTU Singapore in 2006 where he is currently an assistant professor. 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 award at ICDCS 2007, is one of the recipients of HP Labs Innovation Research Program award 2008 and serves as a program co-chair of P2P 2009.

We study the complexity of non-cryptographic authenticated broadcast in radio networks in which a fraction of the nodes may be malicious. We present two authenticated broadcast protocols for multi-hop radio networks, neither of which relies on public-key cryptography. The first protocol, RobustRB, combines optimal running time with maximal number of tolerated faulty nodes. Specifically, RobustRB tolerates up to approximately ¼ of the devices in each neighborhood acting maliciously, which is optimal. The protocol is also asymptotically optimal in terms of running time.

In practice, however, the constants hidden in the asymptotic notation can be quite large. With this in mind, we introduce our second protocol, FastRB, which trades some fault tolerance for efficiency. We evaluate both RobustRB and FastRB using the WSNet simulator in the context of three different fault models: crash failures, jamming, and malicious attacks. Both protocols provide a good level of fault tolerance in all three cases, and the FastRB protocol achieves significantly better performance than the RobustRB protocol. Compared to a time-efficient simple epidemic protocol that does not tolerate any faults, the FastRB protocol is less than a factor of ten slower. We therefore believe that the additional overhead for providing fault tolerance in authenticated broadcast is quite reasonable, especially in applications that use authenticated broadcast only when necessary, such distributing an authenticated digest.

Bio:
Dan Alistarh is currently a PhD student in the Distributed Programming Laboratory at EPF Lausanne, under the guidance of Rachid Guerraoui. He received his B.Sc. in Computer Science and Mathematics from Jacobs University Bremen in 2007. His research interests include the complexity of agreement problems in failure-prone distributed systems and communication in wireless sensor networks.

A "dirty little secret" of network measurements is that what we can measure is often not what we want to (or think we) measure. To illustrate, I will discuss some of the main problems and challenges associated with analyzing and modeling measurements collected for the purpose of inferring certain types of Internet-related connectivity structures (e.g., a network provider's physical infrastructure or router-level topology). In particular, I will demonstrate with some concrete examples the need to (i) understand the process by which Internet connectivity measurements are obtained, (ii) explore the sensitivity of inferred graph properties to known ambiguities in the data, and (iii) be more serious/ambitious when it comes to model validation. Ignoring any of these issues is bound to lead to specious models (e.g., preferential attachment-type network models) that quickly collapse when scrutinized by domain experts.

Bio:
Walter Willinger is a member of the Information and Software Systems Research Center at AT&T Labs Research in Florham Park, NJ. He is well-known for his work that led to the discovery of the self-similar ("fractal") nature of Internet traffic. More recently, he has focused on investigating the topological structure of the Internet and on developing a theoretical foundation for the study of large-scale communication networks such as the Internet. He is a Fellow of ACM, IEEE, AT&T, and SIAM and co-recipient of the 1996 IEEE W.R.G. Baker Prize Award and the 1994 W.R. Bennett Prize Paper Award from the IEEE Communications Society.

The Internet is a vast, complicated and quickly evolving infrastructure that continues to grow in importance to the world's socio-economic fabric. Our quest is to develop an empirical understanding of the behavioral and structural characteristics of the Internet, to pave the way for continued growth and diversification of the infrastructure. In the first part of this talk, we will describe our work on DNS traffic monitoring. We develop and apply a new context-aware clustering method that enables DNS analysis to be scaled to expose the desired level of detail of traffic types, and to expose their time varying characteristics. Our application of these methods to a large DNS trace from our campus highlights both the coarse and fine level of detail on unwanted network behavior and the capabilities of our approach to the general problem of traffic classification. In the second part of the talk, we will describe our work on Internet topology discovery from simple passive measurements of IP packet traffic. We describe algorithms that enable 1) traffic sources that share network paths to be clustered accurately without relying on IP address or autonomous system information, 2) topological structure to be inferred accurately with only a small number of active measurements, 3) missing connectivity information to be recovered, which is a serious challenge in the use of passive packet measurements. This new, passive measurement-based approach offers the promise of near real time topology recovery at cost of the potential loss of some accuracy in resultant maps.

Bio:
Paul Barford an associate professor in the computer science department at the University of Wisconsin-Madison where he has been since 2001. He received a BS in electrical engineering from the University of Illinois and a PhD in computer science from Boston University. He is the founder and director of the Wisconsin Advanced Internet Laboratory - a widely used network testbed sponsored by Cisco Systems and the NSF. His research is focused on developing new techniques for gathering information on the structure and dynamic behavior of the Internet. He is also focused on developing new methods for protecting networks and systems from malicious attacks, and is the founder of Nemean Networks, a network security start-up company. Prof. Barford has authored numerous publications in highly competitive journals and conferences. He has served on committees of many conferences including ACM SIGCOMM, SIGMETRICS ('10 TPC chair), IMC ('06 TPC chair), CCS and USENIX Security. He is a member of the ACM Internet Measurement Conference steering committee, an associate editor of IEEE/ACM Transactions on Networking, and a voting member of the Board of Directors of the National LambdaRail.