Wifi-Reports: Improving Wireless Network Selection with Collaboration

2010 ◽  
Vol 9 (12) ◽  
pp. 1713-1731 ◽  
Author(s):  
Jeffrey Pang ◽  
Ben Greenstein ◽  
Michael Kaminsky ◽  
Damon McCoy ◽  
Srinivasan Seshan
Keyword(s):  
Wireless Network ◽  
Network Selection

scholarly journals A network selection scheme for multicast applications in wireless network convergence

2010 ◽  
Vol 12 (11) ◽  
pp. 999-1012 ◽  
Author(s):  
Jaecheol Kim ◽  
Ji Hoon Lee ◽  
Hojin Lee ◽  
Taekyoung Kwon ◽  
Yanghee Choi
Keyword(s):  
Wireless Network ◽  
Network Selection ◽  
Selection Scheme ◽  
Network Convergence

Seamless Handover in Heterogeneous Wireless Network Using Cognitive Advisor Based Decision Making Algorithm

2017 ◽  
Vol 14 (1) ◽  
pp. 517-523
Author(s):  
V Sivasankaran ◽  
V Nagarajan
Keyword(s):  
Wireless Networks ◽  
Wireless Network ◽  
Heterogeneous Wireless Networks ◽  
Optimization Technique ◽  
Vertical Handover ◽  
User Preference ◽  
Network Selection ◽  
Modern Trend ◽  
Mobile Nodes ◽  
Effective Network

An important and modern trend in wireless network is managing and accessing in heterogeneous wireless networks structures effectively. Vertical handover or handoff technology is major and acting vital role in wireless communication, it has key challenging issues in wireless network, while handover gets call drop kind of latency and call quality minimization. So the communication networks needs an efficient and dynamic services and knowledge monitoring management to select network for handover of different network environments (example: WiMAX, WiFi, WLAN, etc.). In this paper we proposed the concepts of knowledgeable monitoring (KM-method), cognitive advisor (CA) and Advanced Handover Optimization (AHO) technique to improve effective network selection for seamless communication, while travels over heterogeneous wireless networks (HWN). KM-method monitoring and manage effective network selection and holding connected mobile nodes inform header files also maintaining re-initiate to next network information (network IP address, user ID, new path, etc.). CAVHO-Cognitive Advisor based Vertical Handover (VSH and V2H) and KM-methods perform and measures velocity and direction of mobility nodes through SRSS sequential Received Strength Signal. Also CA receives the nearest networks details of each another using nearest neighbouring concept with SDT ratio Algorithm. Optimization technique (AHO) performs dynamically balancing the threshold level of speed, load and quality based on Receiving signal strength and user preference. Simulation results of CAVHO Shows it secure and increases the handover probability of access also proposed system reduce delay and improve quality of services and throughput.

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