Scheduling for next generation WLANs: filling the gap between offered and observed data rates

In wireless networks, opportunistic scheduling is used to increase system throughput by exploiting multi-user diversity. Although recent advances have increased physical layer data rates supported in wireless local area networks (WLANs), actual throughput realized are significantly lower due to overhead. Accordingly, the frame aggregation concept is used in next generation WLANs to improve efficiency. However, with frame aggregation, traditional opportunistic schemes are no longer optimal. In this paper, we propose schedulers that take queue and channel conditions into account jointly, to maximize throughput observed at the users for next generation WLANs. We also extend this work to design two schedulers that perform block scheduling for maximizing network throughput over multiple transmission sequences. For these schedulers, which make decisions over long time durations, we model the system using queueing theory and determine users' temporal access proportions according to this model. Through detailed simulations, we show that all our proposed algorithms offer significant throughput improvement, better fairness, and much lower delay compared with traditional opportunistic schedulers, facilitating the practical use of the evolving standard for next generation wireless networks

A control theoretic approach to achieve proportional fairness in 802.11e EDCA WLANs

This paper considers proportional fairness amongst ACs in an EDCA WLAN for provision of distinct QoS requirements and priority parameters. A detailed theoretical analysis is provided to derive the optimal station attempt probability which leads to a proportional fair allocation of station throughputs. The desirable fairness can be achieved using a centralised adaptive control approach. This approach is based on multivariable statespace control theory and uses the Linear Quadratic Integral (LQI) controller to periodically update CWmin till the optimal fair point of operation. Performance evaluation demonstrates that the control approach has high accuracy performance and fast convergence speed for general network scenarios. To our knowledge this might be the first time that a closed-loop control system is designed for EDCA WLANs to achieve proportional fairness

CA-AQM: Channel-Aware Active Queue Management for Wireless Networks

In a wireless network, data transmission suffers from varied signal strengths and channel bit error rates. To ensure successful packet reception under different channel conditions, automatic bit rate control schemes are implemented to adjust the transmission bit rates based on the perceived channel conditions. This leads to a wireless network with diverse bit rates. On the other hand, TCP is unaware of such {\em rate diversity} when it performs flow rate control in wireless networks. Experiments show that the throughput of flows in a wireless network are driven by the one with the lowest bit rate, (i.e., the one with the worst channel condition). This does not only lead to low channel utilization, but also fluctuated performance for all flows independent of their individual channel conditions. To address this problem, we conduct an optimization-based analytical study of such behavior of TCP. Based on this optimization framework, we present a joint flow control and active queue management solution. The presented channel-aware active queue management (CA-AQM) provides congestion signals for flow control not only based on the queue length but also the channel condition and the transmission bit rate. Theoretical analysis shows that our solution isolates the performance of individual flows with diverse bit rates. Further, it stabilizes the queue lengths and provides a time-fair channel allocation. Test-bed experiments validate our theoretical claims over a multi-rate wireless network testbed