Hi all.
Reminder. This talk is today at 12:30 -- food beforehand.
--Ari
---------- Forwarded message ----------
From: Ariel Rabkin
Date: Mon, Dec 3, 2012 at 6:03 PM
Subject: Zack Ives talk on Wednesday
To: ens@lists.cs.princeton.edu
Zack Ives is visiting us from UPenn. He will be giving a lunch-time (12:30)
talk in rm 302 on December 5.
Let me know if you want to meet with him.
ASPEN: Seamless Declarative Programming across Sensors, Streams, and the
Cloud
Due to advances in semiconductor and communications technology, we are
steadily moving towards a world filled with a plethora of embedded sensing
devices as well as "virtual" sensors within devices -- with the potential
to monitor the environment and to react to or even anticipate changes. The
environment being monitored might be a smart hospital, an entire campus, or
even an office or data center. Often the behaviors we wish to produce
involve combining constantly updating (streaming) data from multiple
heterogeneous sensor and Internet sources. A major challenge is how to
manage the resulting complexity, and to build large-scale, rich monitoring,
learning, and control applications.
In the ASPEN project we have been exploring an approach that seeks to
separate logical dataflow from most of the algorithmic logic -- using a
declarative, SQL-like (but iterative and incremental) programming model to
capture the dataflow, data transformation, and state management needed by
an application, combined with small bits of procedural code to handle
complex logic. Our platform provides distributed query optimization that
takes runtime conditions into account, while also supporting a range of
learning, prediction, and connection-finding algorithms. In this talk I
will describe our basic ASPEN prototype including cluster and sensor
subsystems, and provide an overview of how we address issues of query
optimization, distributed query execution, and incremental recomputation.
Work done jointly with Mengmeng Liu, Svilen Mihaylov, Boon Thau Loo, and
Sudipto Guha
Zachary Ives is an Associate Professor and the Markowitz Faculty Fellow at
the University of Pennsylvania. His research interests include data
integration and sharing, "big data", sensor networks, and data provenance
and authoritativeness. He is a recipient of the NSF CAREER award, and an
alumnus of the DARPA Computer Science Study Panel and Information Science
and Technology advisory panel. He has also been awarded the Christian R.
and Mary F. Lindback Foundation Award for Distinguished Teaching. He serves
as the undergraduate curriculum chair for Penn's Singh Program in Market
and Social Systems Engineering. He is a co-author of the textbook
Principles of Data Integration.
