DocumentCode
2558662
Title
A selective-abstraction modeling approach for simplifying computer network studies
Author
Che, Xianhui ; Wells, Ian
Author_Institution
Fac. of Appl. Design & Eng., Swansea Metropolitan Univ., Swansea, UK
fYear
2009
fDate
12-14 Oct. 2009
Firstpage
1
Lastpage
4
Abstract
Modeling and simulation technique is an essential skill on the pathway of learning and researching computer networks. However, the complexity and scale of the network nowadays often challenges the modeling techniques, as high-specification hardware environment is usually required and the simulation can be inevitably time-consuming. The selective abstraction technique leaves out redundant codes and only implements mandatory threads that can have impact on the simulation results. The investigation of this technique is done through a case study of a star-topology local area network which offers collision-free packet switching. Results show that the abstraction approach effectively reduces the length and complication of the source code and also makes the program-debugging process much easier, hence brings users valuable experience in time-saving learning and research throughout computer network study based on modeling and simulations.
Keywords
discrete event simulation; distributed programming; local area networks; packet switching; program debugging; collision-free packet switching; computer network simplification; high-specification hardware environment; program debugging process; selective-abstraction modeling; star-topology local area network; Application software; Computational modeling; Computer networks; Computer simulation; Discrete event simulation; Hardware; Protocols; Telecommunication traffic; Traffic control; Yarn; Modeling study; selective abstraction; simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Ultra Modern Telecommunications & Workshops, 2009. ICUMT '09. International Conference on
Conference_Location
St. Petersburg
Print_ISBN
978-1-4244-3942-3
Electronic_ISBN
978-1-4244-3941-6
Type
conf
DOI
10.1109/ICUMT.2009.5345432
Filename
5345432
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