Research Article
Optimal Scheduling for Dynamic Channel Allocation in Wireless LANs
@INPROCEEDINGS{10.1109/COMSWA.2007.382627, author={S. Jamaloddin Golestani and Rajeev Rastogi and Mark Smith}, title={Optimal Scheduling for Dynamic Channel Allocation in Wireless LANs}, proceedings={2nd International IEEE Conference on Communication System Software and Middleware}, publisher={IEEE}, proceedings_a={COMSWARE}, year={2007}, month={7}, keywords={Cellular networks Channel allocation Geometry Interference Optimal scheduling Radio spectrum management Telephony Throughput Wireless LAN Wireless networks}, doi={10.1109/COMSWA.2007.382627} }- S. Jamaloddin Golestani
Rajeev Rastogi
Mark Smith
Year: 2007
Optimal Scheduling for Dynamic Channel Allocation in Wireless LANs
COMSWARE
IEEE
DOI: 10.1109/COMSWA.2007.382627
Abstract
Channel allocation schemes that have been used in cellular wireless networks have limited applicability to wireless LANs (WLANs) because of the small number of available channels and irregular cell geometries in WLAN environments. In this paper, we propose a dynamic, frame-based channel allocation architecture for WLANs. In this architecture, time is divided into a sequence of consecutive frames (in the order of milliseconds), and in each frame, only a non-interfering subset of access points (APs) is activated. Under broad traffic assumptions, we prove that the attainable system throughput can be optimized by scheduling APs and allocating channels in each frame such that a weighted sum of queue sizes at the activated APs is maximized. This optimality criterion for AP scheduling and channel allocation leads to a novel graph problem which is a variant of the well-known maximum independent set problem. We develop an approximation algorithm that has quadratic time complexity (in the number of APs) and, under certain conditions, yields a constant (6) factor approximation bound. Using the ns2 simulator we conducted experiments to compare our frame-based approach to static channel allocation. Results of our simulation indicate that our approach is able to deliver system throughput improvements of more than 50%.
