Managing heterogeneity and approximation in stream- and sensor-based
With the advent of low-cost wireless sensing devices, it is predicted
that the world will quickly move to one in which many environments are
instrumented for reasons of security, scientific monitoring, environmental
control, entertainment, etc. There are many fundamental questions about
how to develop applications in this emerging sensor network world. Perhaps
the most important are how to support rich, complex applications that may
have confidentiality requirements, heterogeneous types of sensors,
different connectivity levels, and timing constraints.
The Aspen (Abstract Sensor Programming Environment) project
focuses on the challenges
in developing a programming environment and runtime system for this
style of environment.
We are investigating a number of complementary topics and ideas:
- New programming model: group-based programming: We are building
upon a declarative style of programming to develop a new language,
group-based programming, for complex sensor applications. The goal
is to combine compositional, database-style declarative computation with
constraints on timing, security, distribution, and actuation in a seamless
way. This work is funded by NSF CNS-0721541.
- Security and privacy: We have studied how sensor network
application security is affected by node-level compromise. We are
developing further language constructs for specifying encryption
levels and other properties for data along certain channels.
- Runtime monitoring and checking: We seek to develop techniques
for monitoring performance and triggering events in response to constraint
violations. This work is funded by NSF CNS-0721541.
- Home health care and hospital applications: We hope to develop a
number of applications useful in home hospice and hospital care, which
monitor patients, and also connect patients with the care they need. This work is funded by NSF CNS-0721541.
- Declarative information integration and query optimization: The
core programming model is based on database query languages. We are
developing techniques for supporting schema mappings over streams,
distributed in-network join computation, and recursive queries
for regions. Importantly, we are developing techniques for performing
distributed, decentralized optimization of such computations. This work is
funded by NSF IIS-0713267.
- Stream algorithms: In a distributed setting, many nodes have
limited resources and must use approximate algorithms to make
decisions and capture synopses of system activity. This work is
funded by NSF IIS-0713267.
- Interfacing to Java code: Many real control systems require
Java, C, or other procedural code for sophisticatd sensor data processing
or decision-making. This work is funded by Lockheed Martin.
- Declarative monitoring and re-optimization: We seek to
build a declarative infrastructure for monitoring distributed query
execution status, plus adaptive re-optimization, using declarative
techniques. This work is funded by Lockheed Martin.
The ASPEN "smart building" demonstration, SmartCIS, won Honorable
Mention for Best Demonstration at ACM SIGMOD 2009.
- Svilen R. Mihaylov, Marie Jacob, Zachary G. Ives, Sudipto Guha. Dynamic Join Optimization in Multi-Hop Wireless Sensor Networks. To appear, VLDB 2010 and Proc. VLDB Endowment 3(1).
- Mengmeng Liu, Nicholas E. Taylor, Wenchao Zhou, Zachary G. Ives, Boon Thau Loo. Maintaining Recursive Views of Regions and Connectivity in Networks. To appear, IEEE Transactions on Knowledge and Data Engineering, Special issue on Best Papers of ICDE.
- Mengmeng Liu, Svilen R. Mihaylov, Zhuowei Bao, Marie Jacob, Zachary G. Ives,
Boon Thau Loo, Sudipto Guha. SmartCIS:
Integrating Digital and Physical Environments. Demonstration
description. SIGMOD 2009.
- Mengmeng Liu, Nicholas E. Taylor, Wenchao Zhou, Zachary Ives, and Boon Thau
Loo. Recursive Computation of Regions and Connectivity in Networks.
- Svilen R. Mihaylov, Marie Jacob, Zachary G. Ives, Sudipto Guha. A
Substrate for In-Network Sensor Data Integration. Workshop on Data Management for
Sensor Networks (DMSN), Auckland, New Zealand, 2008.
- Sebastian Fischmeister, Insup Lee, Robert Trausmuth. Hardware
Acceleration for Verifiable, Adaptive Real-Time Communication. IEEE
International Conference on Emerging Technologies and Factory Automation (TFA),
Hamburg, Germany, September 2008.
- Madhukar Anand, Eric Cronin,
Micah Sherr, Matt Blaze, Zachary
Ives, Insup Lee.
Sensor Network Security: More Interesting Than You
Think, Usenix Workshop on Hot Topics in Security, July 2006.
- Madhukar Anand, Zachary
Ives, Insup Lee.
Vulnerability in Sensor Networks, VLDB Workshop on Data Management for Sensor
Networks, August 2005.
- Prof. Boon Thau Loo
- Prof. Matt Blaze
- Svilen Mihaylov
- Mengmeng Liu
- Marie Jacob
- Prof. Lyle Ungar
- Prof. Dean Foster (Wharton)
- Aaron Evans
- Tak Man Ma
- Ted Paulakis
- Madhukar Anand
- Micah Sherr
- Eric Cronin
Funded in part by a seed grant from ISTAR, the Penn Institute for Strategic
Threat Analysis and Response; NSF IIS-0713267; NSF CNS-0721541.
Last modified: Sun Jan 9 12:03:16 EST 2005