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Presenter: Jubayer Ahmed
Supervisor: Dr. T. Aaron Gulliver

Date: Thu, August 14, 2014
Time: 13:00:00 - 00:00:00
Place: EOW 430

ABSTRACT

Abstract:

Sequential decoding process in random network coding scenario for a large file with a variation of Gaussian elimination will have high computational complexity where n is the number of blocks comprising the file. Our research has proposed a decoding algorithm based on Method of Four Russians for Multiplication over extension fields (M4RME) and Inversion (M4RIE) for random network coding when certain number of linearly independent packets with its coefficients have arrived at receiver. This research also investigates several algorithms for possible candidates for decoding and found that a Gray code based Method of Four Russians Algorithm is more suitable when our coefficient matrix is dense as the coefficients are chosen randomly over some finite field. The M4RME and M4RIE algorithms have never been applied in random network coding. Our proposed algorithm shows the effectiveness and computational efficiency of using M4RME and M4RIE in decoding process for random network coding. The decoding process is also verified with an implementation of LU decomposition based algorithm over Galois field for finding inverse with combination of matrix multiplication algorithm.