September 21, 2007
UCSD CSE accomplishments of research on resource management in HPWREN:
QoS scheduling, routing and power management
The research focus of a UCSD Computer Science and Engineering
team, which is collaborating with the HPWREN project, has been on
providing QoS to various applications in HPWREN while minimizing
the power consumption of battery operated wireless nodes. During
this last period we focused on QoS network scheduling and power
management. The result of our research are three journal papers,
four conference papers, 11 invited talks in industry, conferences
and abroad, approximately $400k of funding obtained from industry
and technology transfer to Sun Microsystems, Qualcomm and Cisco.
One MS thesis has already been completed, while another MS and PhD
are in progress. Two students have been funded directly through
HPWREN funds, and two other students have been involved through
industry funding we have been able to obtain.
The about 4500 acre San Diego State University's Santa
Margarita Ecological Reserve has been chosen as the initial
project testbed for the UC San Diego research. The geographic
layout is well suited for QoS research on access networks, which
can aggregate traffic from many sensors and forward to the
Our distributed scheduling algorithm reduces the interference
of active wireless nodes and limits contention, while decreasing
the power consumption. The simulation and measurements performed
with data we gathered on HPWREN access networks show that with our
scheduling algorithm it is possible to achieve a throughput improvement
of up to 10% and maximum power saving of 85%, while providing more
predictable delay. We can provide even larger power savings on
each node by implementing our novel online learning algorithm to
drive system level power management. We formulate both dynamic power
management (DPM) and dynamic voltage frequency scaling (DVFS)
problems as one of workload characterization and selection, and
solve it using this algorithm. Our results show that the algorithm
adapts really well with changing device and workload characteristics
and achieves an overall performance comparable to the best performing
expert at any point in time. Moreover, it is extremely lightweight
and has almost negligible overhead. For more information on our
work, please see the published papers listed at the end of this
In the next period we will focus on energy efficient and QoS
aware routing methodologies. Preliminary studies of QoS routing
algorithms have already been done during this last year, along with
an initial implementation of routing functionality in Cisco routers
used at HPWREN backbone. During this year we plan to expand this
work to include more sophisticated routing solutions, and to expand
so that routing can be implemented in energy efficient manner on
Publications, Invited talks, Technology transfer and Industry funding
- E. Regini, D. Lim, T. Simunic Rosing, "Distributed scheduling for
heterogeneous wireless sensor networks," submitted to IEEE Transactions
on Mobile Computing, 2007.
- G. Dhiman, T. Simunic Rosing, "Using online learning for system
level power management," submitted to IEEE Transactions on CAD, 2007.
- J. Kim, T. Simunic Rosing, "Power-aware
resource management techniques for low-power embedded systems,"
in Handbook of Real-Time and Embedded Systems, Edited by S.
H. Son, I. Lee, J. Y-T Leung, Taylor-Francis Group LLC, 2006.
- E. Regini, D. Lim, T. Simunic Rosing, "Heterogeneous wireless
network management," Submitted to INFOCOM'08.
- G. Dhiman, T. Simunic Rosing, "Dynamic voltage
scaling using machine learning," ISLPED'07.
- D. Lim, J. Shim, T. Simunic Rosing, T. Javidi, "Scheduling
data delivery in heterogeneous wireless sensor networks," ISM'06.
- G. Dhiman, T. Simunic Rosing, "Dynamic power
management using machine learning," ICCAD'06
- D. Lim, "Heterogeneous wireless network management," MS Thesis,
- E. Regini, "Distributed network management and scheduling, " MS
Thesis, UCSD, In progress.
- G. Dhiman, "Routing under energy and QoS constraints in
heterogeneous wireless sensor networks, " PhD Thesis, UCSD, In Progress.
- Intel, Hillsboro, OR: "Heterogeneous wireless network management,"
- Intel, Hillsboro, OR: "Using machine learning for power management
in wireless networks," July 2007.
- SECON, June 2007: "Heterogeneous wireless sensor network resource
management," Invited talk.
- Qualcomm, San Diego, CA: "HPWREN - challenges and research
opportunities," June 2007.
- Qualcomm, San Diego, CA: "Distributed scheduling in wireless sensor
networks, " June, 2007.
- Sun Microsystems, Menlo Park, CA: "Heterogeneous wireless network
management," December 2006.
- Sun Microsystems, Menlo Park, CA: "Using machine learning for power
management in wireless networks," December 2006.
- HP Labs, Palo Alto, CA, ""Resource Management of Heterogeneous
Wireless Embedded Systems", 2006.
- Ericsson, San Diego, CA: "Heterogeneous sensor networks," 2006.
- IMEC, Belgium, "Resource Management of Heterogeneous Wireless
Embedded Systems", 2005
- DATE'05, Munich, Germany, Special Session Invited paper: "Power
management in wireless environments," 2005.
- Qualcomm, San Diego, CA, summer 2007: student (Edorado Regini) as an
intern implements power management for Qualcomm products
- Sun Microsystems, Menlo Park, CA, summer 2007: student (Gaurav
Dhiman) as an intern works on network resource management implementation
in Solaris kernel networking code
- Cisco, San Jose, CA, summer 2007: student (Ben Lee) works on routing
- Samsung, January 2006: student (Daeseob Lim) implements power
management for Samsung's products.
- Sun Microsystems, 2007 - $58k for research in network routing and
- HP, Qualcomm and Sun Microsystems through CNS, 2006 - $130k for
research in wireless sensor network resource management
- HP, Qualcomm and Sun Microsystems through CNS, 2005 - $60k for
research in heterogeneous network management
- Los Alamos National Lab, 2006, 2007 - $85k for research in power
management in wireless sensor networks
Prof. Tajana Simunic Rosing
Department of Computer Science and Engineering
University of California San Diego
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