In this paper, we present a generic plug-and-play controller that ensures fair and efficient operation of IEEE 802.11 infrastructure wireless local area networks with multiple co-channel access points, without any change to hardware firmware of the network devices. Our controller addresses performance issues of TCP transfers in multi-AP WLANs, by overlaying a coarse time-slicing scheduler on top of a cascaded fair queuing scheduler. The time slices and queue weights, used in our controller, are obtained from the solution of a constrained utility optimization formulation. A study of the impact of coarse time-slicing on TCP is also presented in this paper. We present an improved algorithm for adaptation of the service rate of the fair queuing scheduler and provide experimental results to illustrate its efficacy. We also present the changes that need to be incorporated to the proposed approach, to handle short-lived and interactive TCP flows. Finally, we report the results of experiments performed on a real testbed, demonstrating the efficacy of our controller.
In @cite_2 , introduce MIDAS, a management framework that addresses under-served links by throttling traffic to the interfering links. Based on the notion of Activity Share'' that they introduce, the authors propose a method to assess the potential throughput gain that the under-served link can experience, when hindering transmissions are rate-limited. MIDAS limits the rate at which traffic is sent to the interfering links, so that the under-served link's activity share improves. While MIDAS improves the air time'' of under-served links, there are no flow-level system objectives that drive the target activity share. Such flow-level system objectives are indispensable in networks with Quality-of-Service (QoS) guarantees.
@cite_2
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We consider the problem of resource allocation in downlink OFDMA systems for multi service and unknown environment. Due to users' mobility and intercell interference, the base station cannot predict neither the Signal to Noise Ratio (SNR) of each user in future time slots nor their probability distribution functions. In addition, the traffic is bursty in general with unknown arrival. The probability distribution functions of the SNR, channel state and traffic arrival density are then unknown. Achieving a multi service Quality of Service (QoS) while optimizing the performance of the system (e.g. total throughput) is a hard and interesting task since it depends on the unknown future traffic and SNR values. In this paper we solve this problem by modeling the multiuser queuing system as a discrete time linear dynamic system. We develop a robust H∞ controller to regulate the queues of different users. The queues and Packet Drop Rates (PDR) are controlled by proposing a minimum data rate according to the demanded service type of each user. The data rate vector proposed by the controller is then fed as a constraint to an instantaneous resource allocation framework. This instantaneous problem is formulated as a convex optimization problem for instantaneous subcarrier and power allocation decisions. Simulation results show small delays and better fairness among users.