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Your search keyword '"Rowaihy, Hosam"' showing total 26 results
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26 results on '"Rowaihy, Hosam"'

2. Detection and Localization Sensor Assignment with Exact and Fuzzy Locations

Author

Rowaihy, Hosam, Johnson, Matthew P., Pizzocaro, Diego, Bar-Noy, Amotz, Kaplan, Lance, La Porta, Thomas, Preece, Alun, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Krishnamachari, Bhaskar, editor, Suri, Subhash, editor, Heinzelman, Wendi, editor, and Mitra, Urbashi, editor

Published
2009
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3. Frugal Sensor Assignment

Author

Johnson, Matthew P., Rowaihy, Hosam, Pizzocaro, Diego, Bar-Noy, Amotz, Chalmers, Stuart, La Porta, Thomas, Preece, Alun, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Nikoletseas, Sotiris E., editor, Chlebus, Bogdan S., editor, Johnson, David B., editor, and Krishnamachari, Bhaskar, editor

Published
2008
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4. An Ontology-Centric Approach to Sensor-Mission Assignment

Author

Gomez, Mario, Preece, Alun, Johnson, Matthew P., de Mel, Geeth, Vasconcelos, Wamberto, Gibson, Christopher, Bar-Noy, Amotz, Borowiecki, Konrad, La Porta, Thomas, Pizzocaro, Diego, Rowaihy, Hosam, Pearson, Gavin, Pham, Tien, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Gangemi, Aldo, editor, and Euzenat, Jérôme, editor

Published
2008
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5. Assigning Sensors to Missions with Demands

Author

Bar-Noy, Amotz, Brown, Theodore, Johnson, Matthew P., La Porta, Thomas, Liu, Ou, Rowaihy, Hosam, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kutyłowski, Mirosław, editor, Cichoń, Jacek, editor, and Kubiak, Przemysław, editor

Published
2008
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8. Frugal Sensor Assignment

Author

Johnson, Matthew P., primary, Rowaihy, Hosam, additional, Pizzocaro, Diego, additional, Bar-Noy, Amotz, additional, Chalmers, Stuart, additional, La Porta, Thomas, additional, and Preece, Alun, additional

Published
2008
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9. An Ontology-Centric Approach to Sensor-Mission Assignment

Author

Gomez, Mario, primary, Preece, Alun, additional, Johnson, Matthew P., additional, de Mel, Geeth, additional, Vasconcelos, Wamberto, additional, Gibson, Christopher, additional, Bar-Noy, Amotz, additional, Borowiecki, Konrad, additional, La Porta, Thomas, additional, Pizzocaro, Diego, additional, Rowaihy, Hosam, additional, Pearson, Gavin, additional, and Pham, Tien, additional

Published
2008
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25. Mitigating Performance Degradation in Congested Sensor Networks.

Author

Kumar, Raju, Crepaldi, Riccardo, Rowaihy, Hosam, Harris III, Albert F., Guohong Cao, Zorzi, Michele, and La Porta, Thomas F.

Subjects
DETECTORS, PHYSICS instruments, WIRELESS communications, TELECOMMUNICATION systems, COMPUTER networks, ALGORITHMS
Abstract

Data generated in wireless sensor networks may not all be alike: some data may be more important than others and hence may have different delivery requirements. In this paper, we address differentiated data delivery in the presence of congestion in wireless sensor networks. We propose a class of algorithms that enforce differentiated routing based on the congested areas of a network and data priority. The basic protocol, called Congestion-Aware Routing (CAR), discovers the congested zone of the network that exists between high-priority data sources and the data sink and, using simple forwarding rules, dedicates this portion of the network to forwarding primarily high-priority traffic. Since CAR requires some overhead for establishing the high-priority routing zone, it is unsuitable for highly mobile data sources. To accommodate these, we define MAC-Enhanced CAR (MCAR), which includes MAC-layer enhancements and a protocol for forming high-priority paths on the fly for each burst of data. MCAR effectively handles the mobility of high-priority data sources, at the expense of degrading the performance of low-priority traffic. We present extensive simulation results for CAR and MCAR, and an implementation of MCAR on a 48-node testbed. [ABSTRACT FROM AUTHOR]

Published
2008
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26. Knowledge-Driven Agile Sensor-Mission Assignment

Author

Preece, Alun David, Pizzocaro, Diego, Borowiecki, Konrad, de Mel, Geeth, Vasconcelos, Wamberto, Johnson, Matthew P., La Porta, Thomas, and Rowaihy, Hosam

Subjects
QA75
Abstract

In this paper, we show how knowledge representation and reasoning techniques can support sensor-mission assignment,\ud proceeding from a high-level specification of information\ud requirements, to the allocation of assets such as sensors and platforms. In our previous work, we showed how assets can be matched to mission tasks by formalising the military missions and means framework in terms of an ontology, and using this ontology to drive a matchmaking process derived from the area of semantic Web services. The work reported here extends the earlier approach in two important ways: (1) by providing a richer and more realistic way for a user to specify their information requirements, and (2) by using the results of the semantic matchmaking process to define the search space for efficient asset allocation algorithms. We accomplish (1) by means of a rule-based representation of the NIIRS approach to relating sensed data to the tasks that data may support. We illustrate (2)by showing how the output of our matching process can drive a well-known efficient combinatorial auction algorithm (CASS). Finally, we summarise the status of our illustration-of-concept\ud application, SAM (Sensor Assignment to Missions), and discuss various roles such an application can play in supporting sensormission assignment.

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