DocumentCode
2361838
Title
GA-Based on Demand Bandwidth Reservation for Real-Time Traffic in Cellular IP Network
Author
Anbar, Mohammad ; Vidyarthi, D.P.
Author_Institution
Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi, India
fYear
2009
fDate
25-27 Aug. 2009
Firstpage
1935
Lastpage
1942
Abstract
An important challenge in cellular IP networks, which deals with the micro mobility, is providing good quality of service (QoS) to the users especially to the real-time users that are involved in the exchange of real-time packets. Bandwidth reservation for real-time traffic to maximize the connection completion probability (CCP) is an important activity. Genetic algorithm (GA), which is a useful tool in solving optimization problems, is applied in this work to improve the connection completion probability (CCP) in cellular IP networks. Algorithm, used in this model, searches for free available bandwidth in the same cell demanding the bandwidth or in the neighboring cells and allocates it on demand to the cell requesting for it. If it fails in finding free bandwidth, it searches for bandwidth assigned to the nonreal-time users and borrows the bandwidth in order to complete the real-time transaction. Simulation experiments reveal the efficacy of the model.
Keywords
IP networks; cellular radio; genetic algorithms; quality of service; telecommunication traffic; cellular IP network; connection completion probability; demand bandwidth reservation; genetic algorithm; micro mobility; quality of service; real-time packets; real-time traffic; Bandwidth; Cellular networks; Computer networks; Electronic mail; Genetic algorithms; IP networks; Quality of service; Real time systems; Telecommunication traffic; Wireless communication; Bandwidth Reservation; Cellular IP networks; Connection Completion Probability; Genetic Algorithm; Quality of Service;
fLanguage
English
Publisher
ieee
Conference_Titel
INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on
Conference_Location
Seoul
Print_ISBN
978-1-4244-5209-5
Electronic_ISBN
978-0-7695-3769-6
Type
conf
DOI
10.1109/NCM.2009.280
Filename
5331526
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