Generalized Submodular Optimization for Integrated Networked Sensing Systems - Revision history

Chengjie at 01:44, 1 December 2015

2015-12-01T01:44:21Z

Chengjie: /* Publications */

2015-12-01T01:41:35Z

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Chengjie: /* Publications */

2015-12-01T01:40:24Z

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2015-12-01T01:38:52Z

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Chengjie: /* Publications */

2015-12-01T01:12:58Z

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Chengjie at 00:43, 1 December 2015

2015-12-01T00:43:48Z

Chengjie at 07:22, 29 November 2015

2015-11-29T07:22:44Z

Chengjie: /* Publications */

2015-10-11T08:08:52Z

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2014-06-22T04:47:06Z

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 Due to their resource constraints in bandwidth, memory, and energy, shared sensor networks face a critical need for optimizing the Quality of Monitoring (QoM) through dynamic resource allocation to the contending applications. These emerging QoM optimization problems in shared sensor networks are computationally challenging, as they are discrete and nonlinear. Furthermore, the optimization approach must: 1) deal with multiple resource constraints, 2) scale to large networks, and 3) handle network and environmental dynamics.
-To address these challenges, it is important to exploit the special structure of these optimiza- tion problems for sensing applications. A key observation is that most of the QoM functions of the physical phenomena exhibit diminishing returns when more nodes are allocated to an application, a property known as submodularity. Submodular properties are ubiquitous in distributed sensing applications and have been addressed in the literature. However, most of the existing works that utilize submodularity rely on unique problem structures and restrictive assumptions only applicable to specific applications. Moreover, all existing submodular optimization algorithms assume a centralized control, which limits their scalability. To ensure scalability and deal with network dynamics, it is essential to develop distributed and online algorithms for submodular optimization. In this project, both centralized and distributed algorithms are proposed to solve submodular optimization problems in WSNs. We develop novel distributed approaches that exploit submodularity. By incorporating submodularity into a market-based framework, we provide the first approximation bounds for distributed submodular optimization.
+To address these challenges, it is important to exploit the special structure of these optimiza- tion problems for sensing applications. A key observation is that most of the QoM functions of the physical phenomena exhibit diminishing returns when more nodes are allocated to an application, a property known as submodularity. Submodular properties are ubiquitous in distributed sensing applications and have been addressed in the literature. However, most of the existing works that utilize submodularity rely on unique problem structures and restrictive assumptions only applicable to specific applications. Moreover, all existing submodular optimization algorithms assume a centralized control, which limits their scalability. To ensure scalability and deal with network dynamics, it is essential to develop distributed and online algorithms for submodular optimization. In this project, both centralized and distributed algorithms are proposed to solve submodular optimization problems in WSNs. We develop novel distributed approaches that exploit submodularity. By incorporating submodularity into a market-based framework, we provide the first approximation bounds for distributed submodular optimization. The centralized and distributed algorithms were presented at [http://www.cse.wustl.edu/%7Elu/papers/mobihoc10.pdf MobiHoc'10] and [http://www.cse.wustl.edu/%7Elu/papers/infocom12.pdf INFOCOM'12], respectively.
 == Publications ==

@@ Line 30: / Line 30: @@
 * A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Real-time Scheduling for WirelessHART Networks; IEEE Real-Time Systems Symposium (RTSS '10),  December 2010. [http://www.cse.wustl.edu/%7Elu/papers/rtss10.pdf PDF]
-* Y. Xu, A. Saifullah, Y. Chen, C. Lu and S. Bhattacharya, Near Optimal Multi-Application Allocation in Shared Sensor Networks, ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc'10), September 2010.
+* Y. Xu, A. Saifullah, Y. Chen, C. Lu and S. Bhattacharya, Near Optimal Multi-Application Allocation in Shared Sensor Networks, ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc'10), September 2010. [http://www.cse.wustl.edu/%7Elu/papers/mobihoc10.pdf PDF]
-* S. Bhattacharya, A. Saifullah, C. Lu and G.-C. Roman, Multi-Application Deployment in Shared Sensor Networks Based on Quality of Monitoring, IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'10), April 2010.
+* S. Bhattacharya, A. Saifullah, C. Lu and G.-C. Roman, Multi-Application Deployment in Shared Sensor Networks Based on Quality of Monitoring, IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'10), April 2010. [http://www.cse.wustl.edu/%7Elu/papers/rtas10-umade.pdf PDF]
 == Acknowledgements ==
 This work is supported by the NSF under NeTS Grant [http://nsf.gov/awardsearch/showAward.do?AwardNumber=1017701 CNS-1017701].

@@ Line 29: / Line 29: @@
 * A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Real-time Scheduling for WirelessHART Networks; IEEE Real-Time Systems Symposium (RTSS '10),  December 2010. [http://www.cse.wustl.edu/%7Elu/papers/rtss10.pdf PDF]
 == Acknowledgements ==
 This work is supported by the NSF under NeTS Grant [http://nsf.gov/awardsearch/showAward.do?AwardNumber=1017701 CNS-1017701].

@@ Line 16: / Line 16: @@
 * C. Wu, M. Sha, D. Gunatilaka, A. Saifullah, C. Lu and Y. Chen; Analysis of EDF Scheduling for Wireless Sensor-Actuator Networks, ACM/IEEE International Symposium on Quality of Service (IWQoS'14), May 2014. [http://www.cse.wustl.edu/%7Elu/papers/iwqos14.pdf PDF]
-* A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Distributed Channel Allocation Protocols for Wireless Sensor Networks; IEEE Transactions on Parallel and Distributed Systems, 2013. [http://www.cse.wustl.edu/%7Elu/papers/tpds-channel.pdf]
+* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen, Near Optimal Rate Selection for Wireless Control Systems, ACM Transactions on Embedded Computing Systems, Special Issue on Real-Time and Embedded Technology and Applications, 13(4s), Article 128, April 2014. [http://www.cse.wustl.edu/%7Elu/papers/tecs14-rate-selection.pdf PDF]
-* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen; Near Optimal Rate Selection for Wireless Control Systems, ACM Transactions on Embedded Computing Systems (Special Issue on real-time and embedded systems) 2014 [http://www.cse.wustl.edu/~saifullaha/BIB_Files/TECS-CODESIGN.pdf PDF]
+* A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Distributed Channel Allocation Protocols for Wireless Sensor Networks; IEEE Transactions on Parallel and Distributed Systems, 2013. [http://www.cse.wustl.edu/%7Elu/papers/tpds-channel.pdf PDF]
-* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu, Y. Chen; Near Optimal Rate Selection for Wireless Control Systems; The 18th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '12), April 2012 (Best Paper Nominee). [http://www.cse.wustl.edu/~saifullaha/BIB_Files/CODESIGN_RTAS2012_CAMERA.pdf PDF]
+* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen; Near Optimal Rate Selection for Wireless Control Systems, IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '12), April 2012. (Best Paper Nominee) [http://www.cse.wustl.edu/%7Elu/papers/rtas12-wireless-control.pdf PDF]
 * C. Wu, Y. Xu, Y. Chen, C. Lu; Submodular Game for Distributed Application Allocation in Shared Sensor Networks, The 31st IEEE International Conference on Computer Communications (INFOCOM '12), March 2012. [http://www.cse.wustl.edu/%7Elu/papers/infocom12.pdf PDF]
-* A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Priority Assignment for Real-time Flows in WirelessHART Networks; The 23rd Euromicro Conference on Real-Time Systems (ECRTS '11), July 2011, pp. 35--44. [http://www.cse.wustl.edu/~saifullaha/BIB_Files/ECRTS2011.pdf PDF]
+* A. Saifullah, Y. Xu, C. Lu and Y. Chen; Priority Assignment for Real-time Flows in WirelessHART Networks, Euromicro Conference on Real-Time Systems (ECRTS '11), July 2011. [http://www.cse.wustl.edu/%7Elu/papers/ecrts11-wirelesshart.pdf PDF]
-* A. Saifullah, Y. Xu, C. Lu, and Y. Chen; End-to-End Delay Analysis for Fixed Priority Scheduling in WirelessHART Networks; The 17th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '11), April 2011, pp. 13--22. [http://www.cse.wustl.edu/~saifullaha/BIB_Files/RTAS2011.pdf PDF]
+* A. Saifullah, Y. Xu, C. Lu and Y. Chen; End-to-End Delay Analysis for Fixed Priority Scheduling in WirelessHART Networks, IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '11), April 2011. [http://www.cse.wustl.edu/%7Elu/papers/rtas11-wirelesshart.pdf PDF]
-* A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Real-time Scheduling for WirelessHART Networks; The 31st IEEE Real-Time Systems Symposium (RTSS '10),  November 2010, pp. 150--159. [http://www.cse.wustl.edu/~saifullaha/BIB_Files/RTSS2010.pdf PDF]
+* A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Real-time Scheduling for WirelessHART Networks; IEEE Real-Time Systems Symposium (RTSS '10),  December 2010. [http://www.cse.wustl.edu/%7Elu/papers/rtss10.pdf PDF]
 == Acknowledgements ==
 This work is supported by the NSF under NeTS Grant [http://nsf.gov/awardsearch/showAward.do?AwardNumber=1017701 CNS-1017701].

@@ Line 18: / Line 18: @@
 * A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Distributed Channel Allocation Protocols for Wireless Sensor Networks; IEEE Transactions on Parallel and Distributed Systems, 2013. [http://www.cse.wustl.edu/%7Elu/papers/tpds-channel.pdf]
-* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen; Near Optimal Rate Selection for Wireless Control Systems, ACM Transactions on Embedded Computing Systems (Special Issue on real-time and embedded systems) 2013 [http://www.cse.wustl.edu/~saifullaha/BIB_Files/TECS-CODESIGN.pdf PDF]
+* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen; Near Optimal Rate Selection for Wireless Control Systems, ACM Transactions on Embedded Computing Systems (Special Issue on real-time and embedded systems) 2014 [http://www.cse.wustl.edu/~saifullaha/BIB_Files/TECS-CODESIGN.pdf PDF]
 * A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu, Y. Chen; Near Optimal Rate Selection for Wireless Control Systems; The 18th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS '12), April 2012 (Best Paper Nominee). [http://www.cse.wustl.edu/~saifullaha/BIB_Files/CODESIGN_RTAS2012_CAMERA.pdf PDF]

@@ Line 1: / Line 1: @@
 Faculty:  [http://www.cs.wustl.edu/~ychen/ Yixin Chen], [http://www.cs.wustl.edu/~lu/ Chenyang Lu]
-PhD Student:  [http://www.cse.wustl.edu/~saifullaha/ Abusayeed Saifullah], Paras Tiwari
+PhD Student: Paras Tiwari
-Alumni: [https://sites.google.com/site/sbhatta/ Sangeeta Bhattacharya], [http://www.cs.wustl.edu/~wuchengjie/ Chengjie Wu], [http://youxu.info/ You Xu]
+Alumni: [https://sites.google.com/site/sbhatta/ Sangeeta Bhattacharya],  [http://www.cse.wustl.edu/~saifullaha/ Abusayeed Saifullah], [http://www.cs.wustl.edu/~wuchengjie/ Chengjie Wu], [http://youxu.info/ You Xu]
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@@ Line 10: / Line 10: @@
 Due to their resource constraints in bandwidth, memory, and energy, shared sensor networks face a critical need for optimizing the Quality of Monitoring (QoM) through dynamic resource allocation to the contending applications. These emerging QoM optimization problems in shared sensor networks are computationally challenging, as they are discrete and nonlinear. Furthermore, the optimization approach must: 1) deal with multiple resource constraints, 2) scale to large networks, and 3) handle network and environmental dynamics.
-To address these challenges, it is important to exploit the special structure of these optimiza- tion problems for sensing applications. A key observation is that most of the QoM functions of the physical phenomena exhibit diminishing returns when more nodes are allocated to an application, a property known as submodularity. Submodular properties are ubiquitous in distributed sensing applications and have been addressed in the literature. However, most of the existing works that utilize submodularity rely on unique problem structures and restrictive assumptions only appli- cable to specific applications. Moreover, all existing submodular optimization algorithms assume a centralized control, which limits their scalability. To ensure scalability and deal with network dynamics, it is essential to develop distributed and online algorithms for submodular optimization. In this project, both centralized and distributed algorithms are proposed to solve submodular optimization problems in WSNs. We develop novel distributed approaches that exploit submodularity. By incorporating submodularity into a market-based framework, we provide the first approximation bounds for distributed submodular optimization.
+To address these challenges, it is important to exploit the special structure of these optimiza- tion problems for sensing applications. A key observation is that most of the QoM functions of the physical phenomena exhibit diminishing returns when more nodes are allocated to an application, a property known as submodularity. Submodular properties are ubiquitous in distributed sensing applications and have been addressed in the literature. However, most of the existing works that utilize submodularity rely on unique problem structures and restrictive assumptions only applicable to specific applications. Moreover, all existing submodular optimization algorithms assume a centralized control, which limits their scalability. To ensure scalability and deal with network dynamics, it is essential to develop distributed and online algorithms for submodular optimization. In this project, both centralized and distributed algorithms are proposed to solve submodular optimization problems in WSNs. We develop novel distributed approaches that exploit submodularity. By incorporating submodularity into a market-based framework, we provide the first approximation bounds for distributed submodular optimization.
 == Publications ==

← Older revision		Revision as of 04:45, 22 June 2014
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	* C. Wu, M. Sha, D. Gunatilaka, A. Saifullah, C. Lu and Y. Chen; Analysis of EDF Scheduling for Wireless Sensor-Actuator Networks, ACM/IEEE International Symposium on Quality of Service (IWQoS'14), May 2014. [http://www.cse.wustl.edu/%7Elu/papers/iwqos14.pdf PDF]		* C. Wu, M. Sha, D. Gunatilaka, A. Saifullah, C. Lu and Y. Chen; Analysis of EDF Scheduling for Wireless Sensor-Actuator Networks, ACM/IEEE International Symposium on Quality of Service (IWQoS'14), May 2014. [http://www.cse.wustl.edu/%7Elu/papers/iwqos14.pdf PDF]
		+
		+	* A. Saifullah, Y. Xu, C. Lu, and Y. Chen; Distributed Channel Allocation Protocols for Wireless Sensor Networks; IEEE Transactions on Parallel and Distributed Systems, 2013.
		+	[http://www.cse.wustl.edu/%7Elu/papers/tpds-channel.pdf]

	* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen; Near Optimal Rate Selection for Wireless Control Systems, ACM Transactions on Embedded Computing Systems (Special Issue on real-time and embedded systems) 2013 [http://www.cse.wustl.edu/~saifullaha/BIB_Files/TECS-CODESIGN.pdf PDF]		* A. Saifullah, C. Wu, P. Tiwari, Y. Xu, Y. Fu, C. Lu and Y. Chen; Near Optimal Rate Selection for Wireless Control Systems, ACM Transactions on Embedded Computing Systems (Special Issue on real-time and embedded systems) 2013 [http://www.cse.wustl.edu/~saifullaha/BIB_Files/TECS-CODESIGN.pdf PDF]