期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 41, 期 10, 页码 4996-5008出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2014.01.024
关键词
Expert system; Fuzzy control; Flow control; Offloading; Real-time traffic; WLAN
类别
资金
- Renesas Mobile Europe Ltd.
- VTT Technical Research Centre of Finland
- Internet of Things program of DIGILE - Tekes
The paper explores delay-based congestion and flow control and the offloading of real-time traffic from wireless local area networks (WLANs) to mobile cellular networks (MCNs) in multihomed devices. The control system developed is based on an embedded hierarchical expert system. It adjusts transceivers' traffic flow(s) for prevailing network conditions to achieve application-dependent delay and throughput limits. In wireless networks, delay and throughput depend on the packet size, packet transmission interval, and node connection density. Therefore, the controller on the destination node monitors average one-way delay and the change of one-way delay of the incoming traffic. On this basis, it adjusts the packet size and transmission interval of the source node by transmitting a control command to the source. If the prevailing level of traffic in the network exceeds its capacity despite of the control actions taken, devices prepare for developed asynchronous offloading of traffic to another access network. The control model was validated via simulation of Voice over Internet Protocol (VoIP) traffic in the OMNeT++ network simulator. The results demonstrate that the expert system developed is able to regulate packet sizes to match the prevailing application-dependent optimum and transfer traffic to another network if the network exceed its capacity no matter the control actions taken. Although this work is motivated mainly by issues of congestion and flow control of WLAN systems and the simulations and results were prepared for the IEEE 802.11b system, the approach and techniques are not limited to these systems, but they are applicable for other packet switched access networks (PSANs), too. (C) 2014 Elsevier Ltd. All rights reserved.
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