Paper Info
Title
Classifier Learning and Decision Making for a Connection Manager on a Heterogeneous Network
Abstract
An attractive feature of the Connection Manager Intelligence Agent is its use of network traffic and multi-attribute behavior to locate the best network devices. This study has integrated this agent with a user interface; a network connection handoff; wired and wireless network device drivers; network management applications of the (plug-in) play interface; module-to-module communication authentication; and a DBus for added versatility. To reduce the time that developers of embedded systems spend on the software engineering of this module and to achieve rapid operational efficiency, an Open Source platform, such as MeeGo or Android, must be used. This study has implemented an interactive interface through the function (based on Fuzzy-AHP) of acquisition user behavior and machine designers, boosting iterations for User-Case. The algorithm maintains a set of weights as a distribution class table of cases, as in the parameter learning by user-case; it is quite possible that the expectation---maximization of maximum probability model can be classified by user behavior. In this study, user interaction showed that the agent satisfactorily matched user intent.
Year
DOI
Venue
2014
10.1007/s11277-014-1642-1
Wireless Personal Communications
Keywords
Field
DocType
dbus,decision-making,fuzzy-ahp,heterogeneous network,attribute,seamless network
Wireless network,Android (operating system),Computer science,Networking hardware,Computer network,Network simulation,Real-time computing,Heterogeneous network,Network management,User interface,Network management station
Journal
Volume
Issue
ISSN
77
3
1572-834X
Citations 
PageRank 
References 
2
0.41
17
Authors
4
Name
Order
Citations
PageRank
Sheng-Tzong Cheng129344.23
Chih-Wei Hsu23011268.01
Gwo-Jiun Horng39923.82
Jian-Pan Li4154.05