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IEEE International Performance Computing and Communications Conference (2011)
Orlando, FL, USA
Nov. 17, 2011 to Nov. 19, 2011
ISBN: 978-1-4673-0010-0
pp: 1-2
Jervis Pinto , School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, Oregon, USA
Thinh Nguyen , School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, Oregon, USA
Pingan Zhu , School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, Oregon, USA
Alan Fern , School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, Oregon, USA
ABSTRACT
The design of network protocols is a complicated and tedious endeavor. For instance, designing a MAC layer protocol for the 802.11 standard typically involves a number of high-level decisions (e.g., conditions for backoff steps) followed by an individual tuning of numeric parameters (e.g., backoff factors), for a variety of network conditions. A different way to view this design process is that of a designer being forced to fully specify a solution to a complex problem. At the other extreme of the programming spectrum lie Reinforcement Learning techniques which only require a minimal problem specification from the programmer.
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CITATION
Jervis Pinto, Thinh Nguyen, Pingan Zhu, Alan Fern, "Adaptation-based programming for network protocol design: An 802.11x case study (abstract)", IEEE International Performance Computing and Communications Conference, vol. 00, no. , pp. 1-2, 2011, doi:10.1109/PCCC.2011.6108103
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