[??]
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Felisa Vazquez-Abad, Pinhus Dashevsky, and Matthew P. Johnson.
LP-Based Approaches to Stationary-Constrained Markov Decision Problems.
WODES 2014, Paris, France, May 2014.
[ pdf ]
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[25]
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M.P. Johnson, D. Sarioz, A. Bar-Noy, T. Brown, D. Verma, and C.W.
Wu.
More is more: robust and efficient coverage in denser sensor
deployment.
IEEE Transactions on Sensor Networks, Vol. 8, Iss. 3, August, 2012.
[ pdf ]
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[24]
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M.P. Johnson, A. Bar-Noy, O. Liu, Y. Feng.
Energy peak shaving with local storage.
Sustainable Computing. To appear.
[ pdf ]
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[23]
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M.P. Johnson and A. Bar-Noy.
Pan and scan: configuring cameras for coverage.
IEEE INFOCOM 2011 (acceptance rate: 15.96%), Shanghai, China, April, 2011.
[ pdf ]
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[22]
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Y. Alayev, A. Bar-Noy, M.P. Johnson, L. Kaplan, T. La Porta.
You can't get there from here: sensor scheduling with refocusing delays.
IEEE MASS 2010 (acceptance rate: 27.6%), San Francisco, CA, November, 2010.
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[21]
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F. Chen, M.P. Johnson, Y. Alayev, A. Bar-Noy, and T. La Porta.
Who, when, where: timeslot assignment to mobile clients.
IEEE Transactions on Mobile Computing, Vol. PP, Iss. 99, February, 2011.
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[20]
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M.P. Johnson, H. Rowaihy, D. Pizzocaro, A. Bar-Noy, S. Chalmers, T. La Porta,
and A. Preece.
Sensor-mission assignment in constrained environments.
IEEE Transactions on Parallel and Distributed Systems, Vol. 2, Iss. 11, November, 2010.
[ pdf ]
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[19]
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H. Rowaihy, M.P. Johnson, O. Liu, A. Bar-Noy, T. Brown, and T. La Porta.
Sensor-mission assignment in wireless sensor networks.
ACM Transactions on Sensor Networks, Vol. 6, No. 4, 2010.
[ pdf ]
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[18]
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F. Chen, M.P. Johnson, Y. Alayev, A. Bar-Noy, and T. La Porta.
Who, when, where: timeslot assignment to mobile clients.
In MASS 2009.
[ pdf ]
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[17]
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F. Chen, M.P. Johnson, A. Bar-Noy, I. Fermin, and T. La Porta.
Proactive data dissemination to mission sites.
In SECON 2009.
[ bib |
pdf ]
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[16]
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A. Bar-Noy, T. Brown, M.P. Johnson, and O. Liu.
Cheap or flexible sensor coverage.
In DCOSS 2009.
[ bib ]
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[15]
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H. Rowaihy, M.P. Johnson, D. Pizzocaro, A. Bar-Noy, L. Kaplan, T. La Porta, and
A. Preece.
Detection and localization sensor assignment with exact and fuzzy
locations.
In DCOSS 2009.
[ bib |
pdf ]
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[14]
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S. Eswaran, M. P. Johnson, A. Misra, and T. La Porta.
Adaptive in-network processing for bandwidth and energy constrained
mission-oriented multi-hop wireless networks.
In DCOSS 2009.
[ bib ]
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[13]
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M.P. Johnson, D. Sarioz, A. Bar-Noy, T. Brown, T. La Porta, D. Verma, and C.W.
Wu.
More is more: robust and efficient coverage in denser sensor
deployment.
In INFOCOM 2009.
[ bib |
pdf ]
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[12]
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S. Eswaran, M.P. Johnson, A. Misra, and T. La Porta.
Distributed utility-based rate adaptation protocols for prioritized,
quasi-elastic flows.
ACM SIGMOBILE Mobile Computing and Communications Review
(MC2R), 13(1), January 2009.
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pdf ]
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[11]
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A. Bar-Noy, M.P. Johnson, and O. Liu.
Peak shaving through resource buffering.
In WAOA 2008.
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pdf |
slides ]
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[10]
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H. Rowaihy, M.P. Johnson, T. Brown, A. Bar-Noy, and T. La Porta.
Assigning sensors to competing missions.
In GLOBECOM 2008.
[ bib ]
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[9]
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H. Rowaihy, M.P. Johnson, S. Eswaran, D. Pizzocaro, A. Bar-Noy, T. La Porta, A. Misra, and A.
Preece.
Utility-based joint sensor selection and congestion control for task-oriented WSNs.
In The 2008 Asilomar Conference on Signals, Systems, and Computers.
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[8]
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M. Gomez, A. Preece, M.P. Johnson, G. de Mel, W. Vasconcelos, C. Gibson,
A. Bar-Noy, K. Borowiecki, T. La Porta, D. Pizzocaro, H. Rowaihy, G. Pearson,
and T. Pham.
An ontology-centric approach to sensor-mission assignment.
In EKAW 2008.
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pdf ]
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[7]
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M.P. Johnson, H. Rowaihy, D. Pizzocaro, A. Bar-Noy, S. Chalmers, T. La Porta,
and A. Preece.
Frugal sensor assignment.
In DCOSS 2008.
[ bib |
slides |
pdf ]
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[6]
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A. Bar-Noy, M.P. Johnson, Y. Feng, and O. Liu.
When to reap and when to sow: lowering peak usage with realistic
batteries.
In WEA 2008.
[ bib |
slides |
pdf ]
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[5]
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M.P. Johnson and R. Parikh.
Probabilistic conditionals are almost monotonic.
Review of Symbolic Logic, Vol. 1, No. 1, June 2008.
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pdf ]
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[4]
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A. Bar-Noy, T. Brown, M.P. Johnson, T. La Porta, O. Liu, and H. Rowaihy.
Assigning sensors to missions with demands.
In ALGOSENSORS 2007. Springer LNCS 4837.
[ bib ]
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[3]
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M.P. Johnson and A.P. Kosoresow.
Lower Bounds via Worst-Case Instances via Genetic Algorithms.
World Scientific, 2004.
[ bib ]
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[2]
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M.P. Johnson and A.P. Kosoresow.
Finding worst-case instances, and lower bounds, for np-complete
problems using genetic algorithms.
Proceedings of the 4th Asia-Pacific Conference on Simulated
Evolution And Learning, 2002.
[ bib ]
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[1]
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A.P. Kosoresow and M.P. Johnson.
Finding worst-case instances of, and lower bounds for, online
algorithms using genetic algorithms.
AI 2002: Advances in Artificial Intelligence: 15th Australian
Joint Conference on Artificial Intelligence, Proceedings. LNAI 2557, 2002.
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