Optimization of AP Placement and Channel Assignment in Wireless LANs
LCN '02 Proceedings of the 27th Annual IEEE Conference on Local Computer Networks
Weighted coloring based channel assignment for WLANs
ACM SIGMOBILE Mobile Computing and Communications Review
Distributed channel management in uncoordinated wireless environments
Proceedings of the 12th annual international conference on Mobile computing and networking
Traffic-aware channel assignment in wireless LANs
ACM SIGMOBILE Mobile Computing and Communications Review
MDG: measurement-driven guidelines for 802.11 WLAN design
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Designing high performance enterprise Wi-Fi networks
NSDI'08 Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation
Traffic-aware dynamic spectrum access
Proceedings of the 4th Annual International Conference on Wireless Internet
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IEEE 802.11 WLANs are becoming more and more popular in homes and urban areas. As opposed to traditional WLANs, the access points (APs) in these networks are often deployed by network non-specialists in an uncoordinated manner, leading to unplanned topology, interference and unsatisfactory throughput performance. We consider in this paper a distributed channel assignment algorithm for uncoordinated WLANs, where APs can self-configure their operating channels to minimize interference. We propose an efficient, simple and distributed algorithm termed CACAO (Client-Assisted Channel Assignment Optimization). In CACAO, an AP makes use of the traffic information fed back by its clients to make channel assignment decision. This leads to better knowledge on network environment and better channel assignment decision at the APs. We conduct extensive simulation study and comparisons using Network Simulator 2 (NS2). Our results show that CACAO out-performs other traditional and recent schemes in terms of throughput with similar level of fairness. Furthermore, it converges quite fast to reduce interference to a low level.