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Information Technology Journal

Year: 2014 | Volume: 13 | Issue: 16 | Page No.: 2581-2587
Research Article

Adaptive Traffic Offloading Method Based on OWN in Overlay Networks with LTE and WLAN

Yangchun Li
Beijing Key Laboratory of Network System Architecture and Convergence, College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, Peoples Republic of China
Zhaoming Lu
Beijing Key Laboratory of Network System Architecture and Convergence, College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, Peoples Republic of China
Xiangming Wen
Beijing Key Laboratory of Network System Architecture and Convergence, College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, Peoples Republic of China
Traffic overload problem in the cellular networks has become crucial. In order to approach the problem of increasing traffic, an adaptive traffic offloading method based on a combination of Open Wireless Networks (OWN) and a biologically inspired attractor selection model is proposed in this study. This method provides a pragmatic way to keep load balance and reduce selfishness. Thus, it can improve the overall performance in overlay networks with 3GPP Long Term Evolution (LTE) and Wireless Local Area Networks (WLAN). Firstly, based on discrete Markov Modulated Poisson Process (dMMPP), a queuing model is considered to obtain the real-time network status in both LTE and WLAN. Secondly, by following the OWN architecture to develop the attractor selection model for offloading at the right time in order to accommodate unpredictable traffic demands in fluctuating environment. The whole wireless network can be managed in an autonomous, load balancing and robust manner by the global control which is under OWN and the autonomous decision of attractor selection. The simulation results demonstrate that the proposed mechanism can reach a tradeoff between the system delay and the handover times by realizing efficient traffic offloading.
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