| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | August 30, 2012 |
| Latest Amendment Date: | August 30, 2012 |
| Award Number: | 1218819 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Marilyn McClure
mmcclure@nsf.gov (703)292-5197 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2012 |
| End Date: | September 30, 2016 (Estimated) |
| Total Intended Award Amount: | $300,000.00 |
| Total Awarded Amount to Date: | $300,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1350 BEARDSHEAR HALL AMES IA US 50011-2103 (515)294-5225 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
Coover Hall Ames IA US 50011-3060 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CSR-Computer Systems Research |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This project develops innovative energy-aware resource management algorithms for networked real-time systems, that seek to optimize system-level energy consumption, including both computation and communication. Central to this research is the systematic exploitation of network coding, both at the physical and network layers, to reduce the number of message transmissions and hence reduce the overall energy consumption. Research tasks include: (i) design of energy-aware scheduling algorithms for static and dynamic workloads; (ii) design of energy-aware run-time adaptation algorithms accounting for both workload and channel variations; (iii) performance evaluation of the algorithms through a combination of simulation- and testbed-based experiments under a variety of realistic workloads accounting for various system overheads including those that are due to network coding.
Real-time embedded systems combining sensing, computation, and communication play a prominent role in a variety of current and emerging safety- and mission-critical applications. Such systems typically rely on batteries or other limited energy sources. It is a continuing challenge to satisfy timeliness and reliability constraints in such energy-limited environments. This project investigates the application of incorporating "network coding" -- a technique for combining multiple packets of information into a single message -- as a means of reducing energy consumed for wireless communication, as part of a broader strategy for energy conservation. Besides contributing to technology that will enable functionally richer and long-lived real-time applications, this project develops novel curriculum modules, mentors undergraduate students including under-represented minorities through capstone design projects, and exposes high school students to energy management concepts in real-time applications via testbed demonstrations.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Real-time embedded systems involving sensing, computation, and communication play a prominent role in a variety of current and emerging safety-critical and mission-critical, and Internet of Things (IoT) applications. This project investigated the application of incorporating "network coding" -- a technique for combining multiple packets of information into a single message -- as a means of reducing energy consumed for wireless communication, as part of a broader strategy for energy conservation. In particular, this project developed a sciencific framework for analyzing the tradeoffs between rate (bandwidth), latency (delay), and energy consumption. In addition, it also developed a testbed environment, based on network of smart devices, and conducted research experimentations to quantify the benefits of network coding taking into account encoding-decoding and algorithmic overheads. Our research showed that network coding is indeed a promising technique for energy optimization in networked embedded systems if opportunities for network-coding exist, which are dictated by network topology and traffic pattern.
Besides contributing to technology that will enable functionally richer and long-lived real-time embedded pplications, this project developed a novel curricular module in energy management in real-time embedded systems. This module was integrated into a senior/graduate-level course with hands-on lab experiments that benefitted approximately 200 undergraduate/graduate students during the course of this project. Moreover, the project supported, in part, the Ph.D. dissertation of four graduate students, of which two have already graduated and working in industry. Overall, the project made significant contributions to workforce development in the emerging area of real-time embedded systems and IoT.
Last Modified: 01/06/2017
Modified by: Manimaran Govindarasu
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