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Invited Speakers
The invited speakers list (in alphabetic order):
- Phillip B. Gibbons,
http://www.pittsburgh.intel-research.net/people/gibbons/
Title:
Fun with Networks: Social, Sensor, and Shape Shifting
Abstract:
Part of the "fun" in algorithmic research in networking arises from
the emergence of important new network settings. These new settings
bring new algorithmic problems to be formulated and studied. In this
talk, we consider three such settings. First, we consider social
networks and how they can be used in a novel way to defend against
Sybil attacks in P2P distributed systems. In a Sybil attack, a
malicious user creates a very large number of fake identities in order
to out-vote the honest users in collaborative P2P tasks. Our
protocols, SybilGuard and its follow-on SybilLimit, use randomized
routes (a variant of random walks) on a social network topology in
order to reject all but a limited number of votes by fake identities.
Second, we consider wireless sensor networks and how to perform
robust, in-network aggregation in an energy-efficient way. Our
approach, Synopsis Diffusion, seeks to combine the energy-efficiency
of tree-based aggregation with the robustness of gossip-based
aggregation. This is accomplished through the use of
order-and-duplicate-insensitive (ODI) synopses, which enable the
efficient, robust use of the broadcast wireless medium. We present a
theory of ODI synopses, as well as open problems. Finally, we look
ahead to a new network setting arising from modular robotic ensembles
of billions of submillimeter-sized modules, called catoms. Catoms
dynamically form physical shapes by "rolling" across each other under
software control. While we present a few initial results, devising an
effective communication scheme for such networks remains an open
problem.
This talk covers joint work with Casey Helfrich, Michael Kaminsky,
Amit Manjhi, Todd Mowry, Suman Nath, Padmanabhan Pillai, Srinivasan
Seshan, and Haifeng Yu.
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David Harel,
http://www.wisdom.weizmann.ac.il/~harel/
Title:
In Silico Biology, or On Comprehensive and Realistic Modeling
Abstract:
The talk shows the way software and systems engineering, especially of
reactive systems, can be applied beneficially to the life sciences. We
will discuss the idea of comprehensive and realistic computerized
modeling of biological systems. In comprehensive modeling the main
purpose is to understand an entire system in detail, utilizing in the
modeling effort all that is known about the system, and to use that
understanding to analyze and predict behavior in silico. In realistic
modeling the main issue is to model the behavior of actual elements,
making possible totally interactive and modifiable realistic
executions and simulations that reveal emergent properties. I will
address the motivation for such modeling and the philosophy underlying
the techniques for carrying it out, as well as the crucial question of
when such models are to be deemed valid, or complete. The examples I
will present will be from among the biological modeling efforts my
group has been involved in: T cell development in the thymus, lymph
node behavior, organogenesis of the pancreas, fate determination in
the reproductive system of C. elegans , and a generic cell model. I
will also discuss a long-term "grand challenge" --- to model a full
multi-cellular organism.
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Alexander A. Shvartsman,
http://www.engr.uconn.edu/~aas/
Title:
Distributed Cooperation and Adversity: Complexity Trade-Offs
Abstract:
The problem of cooperatively performing a collection of
tasks in a decentralized setting where the computing medium is subject
to undesirable perturbations is one of the fundamental problems in
distributed computing, with applications encompassing such important
areas as Internet supercomputing, parallel simulation, and multi-agent
collaboration. The perturbations in the computing medium are
typically due to processor and software failures (benign or
malicious), communication breakdowns, and unpredictable delays. Such
perturbations become even more prominent when an application needs to
harness massive amounts of available computational resources. To
develop efficient solutions for computation problems based on
distributed cooperation, it is important to understand efficiency
trade-offs characterizing the ability of p processors to cooperate on
t tasks in key models of computation in the presence of adversity. In
this talk we survey historical and recent results for distributed
cooperation roughly grouped along the following topics: (i)
fundamental failure-sensitive bounds for distributed cooperation
problems for synchronous crash-prone processors, (ii) upper and lower
bounds on distributed cooperation in shared-memory models, (iii)
bounds on distributed work in message-passing models and on redundant
work for processors that may experience prolonged absence of
communication.
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