DocumentCode :
3463028
Title :
Parameter learning in lookahead online algorithms for data acknowledgment
Author :
Németh, Tamás ; Gyekiczki, Balázs ; Imreh, Csanád
Author_Institution :
Inst. of Inf., Univ. of Szeged, Szeged, Hungary
fYear :
2011
fDate :
25-27 Aug. 2011
Firstpage :
195
Lastpage :
198
Abstract :
In the communication aspect of a computer network, data is sent by packets. If the communication channel is not completely safe, then the arrival of the packets must be acknowledged. In the data acknowledgment problem the goal is to determine the time of sending acknowledgments. Here we study lookahead online algorithms, where at time t the algorithm knows the arrival time of the packets arriving till time t+c. We present a new algorithm which is based on the idea of learning the optimal value of a parameter. The efficiency of the algorithms is investigated by testing them experimentally, and it is demonstrated that the new parameter learning algorithm performs significantly better than the original one.
Keywords :
computer network security; data handling; parameter estimation; telecommunication channels; communication channel; computer network; data acknowledgment problem; lookahead online algorithms; packets arrival time; parameter optimal value learning algorithm; Algorithm design and analysis; Delay; Educational institutions; Heuristic algorithms; Learning systems; Optimized production technology; Software algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Logistics and Industrial Informatics (LINDI), 2011 3rd IEEE International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4577-1842-7
Type :
conf
DOI :
10.1109/LINDI.2011.6031146
Filename :
6031146
Link To Document :
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