Context-aware network selection

A Trigger-based Dynamic Load Balancing Method for WLANs Using Virtualized Network Interfaces

masahiro-ka.poster

We propose a method for dynamic load balancing in wireless LANs (WLANs), which adapts association topology dynamically based on traffic
conditions, while keeping the handoff overhead negligible using
virtualized wireless network interfaces (WNICs). In large-scale WLANs,
there are many locations that each station (STA) can discover multiple
access points (APs). In these locations, the conventional approach to
the AP selection in which each station connects to the AP with
the strongest Received Signal Strength Indication (RSSI) may suffer from
imbalanced load among APs. To address this issue, a number of AP
selection schemes have been proposed, which achieve load balancing by
changing some STA-AP associations. However, since stations cannot
communicate during handoff, frequent changes of STA-AP associations
will result in serious deterioration of the communication quality.
Therefore, in the existing schemes, we face a problem that it is
difficult to decide appropriate timing of association
changes. Nevertheless, this problem was not considered as a major
concern in the literature. In this paper, we propose a method for
trigger-based dynamic load balancing in WLANs. In the proposed method,
to minimize the handoff overhead, the WNIC on a station is virtualized
and connected to multiple APs simultaneously. Using this approach, we
propose a method that continuously monitors changes in traffic
conditions and that switches STA-AP associations at appropriate timing
based on the monitored results. We evaluate the effectiveness of our
method in terms of aggregated throughput and fairness using the ns-3
simulator. Compared with the result in the traditional AP selection
method, aggregated throughput is improved by about 11\%,
while increasing the Jain’s fairness index by about 19\% in our method.

Published Paper

  • Kawada, M., Tamai, M., Yasumoto, K.: A Trigger-based Dynamic Load Balancing Method for WLANs Using Virtualized Network Interfaces, Proc. of IEEE WCNC 2013, pp. 1109-1114 (Apr. 2013).

 

Wi-Fi Offloading for Outdoor Mobile Users Using Access Points in Vehicles

tasuku-fPoster

With the increasing popularity of smart-phone, 3G networks are currently overloaded with mobile data traffic. Due to this explosion of data traffic, communication quality deteriorate and communication failure occurs. To solve this problem, there are Wi-Fi offloading methods to offload mobile data traffic to WiFi netowork. However,there is a problem that Outdoor mobile user like a waking pedestrian cannot offload mobile data, since they are out of Wi-Fi access point area. In this paper, we propose a new WiFi offloading method which uses the vehicle passing near the user as a relay node. mobile user sends a data to a vehicle running near the user via Wi-Fi. Second,in order to deliver the data to node on the Internet, the vehicle sends the data via Wi-Fi AP opportunistically encountered. In addition, we focus on the fact that contact duration between vehicles and pedestrians is likely to be higher near the intersection. In order to increase the probability of successful data reception at a mobile user from the Internetf, we propose a method which selects a vehicle awith a higher probability of encountering the mobile user.

 

Adaptive wireless network selection method based on user’s context

In this paper, we propose the adaptive wireless network selection method using user’s context. And we also propose the flamework which support to develop original network selection application for android with the new combination of user’s context and trigger easily. We show the proposed method can achive a lot of network selection scinarios which conventional method can’t.

Published Papers

  • Yutaka Arakawa, Hiroshi Miyake, Yusuke Yamaguchi, Shigeaki Tagashira and Akira Fukuda, “Application-Layer Active Wireless Network Switching on a Smartphone, ” The Second Workshop on Smart Mobile Applications (SmartApps’12) in PERVASIVE2012, June 19, 2012.

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