Recent experimental studies confirm the prevalence of the widely known performance anomaly problem in current Wi-Fi networks, and report on the severe network utility degradation caused by this phenomenon. Although a large body of work addressed this issue, we attribute the refusal of prior solutions to their poor implementation feasibility with off-the-shelf hardware and their imprecise modelling of the 802.11 protocol. Their applicability is further challenged today by very high throughput enhancements (802.11n ac) whereby link speeds can vary by two orders of magnitude. Unlike earlier approaches, in this paper we introduce the first rigorous analytical model of 802.11 stations' throughput and airtime in multi-rate settings, without sacrificing accuracy for tractability. We use the proportional-fair allocation criterion to formulate network utility maximisation as a convex optimisation problem for which we give a closed-form solution. We present a fully functional light-weight implementation of our scheme on commodity access points and evaluate this extensively via experiments in a real deployment, over a broad range of network conditions. Results demonstrate that our proposal achieves up to 100 utility gains, can double video streaming goodput and reduces TCP download times by 8x.
@cite_33 undertakes an empirical study to find the contention window settings that achieve proportional fairness, but lacks analytical support and is limited to static scenarios. Heusse propose to control stations' transmission opportunities based on the observed number of idle slots, to tackle airtime fairness @cite_20 ; however, the implementation requires precise time synchronisation and is tightly coupled to specific hardware and a proprietary closed-source firmware @cite_32 . Lee implement O-DCF @cite_0 , whereby a station's packet rate is adjusted according to the MCS employed, to improve network utility. This approach requires introducing an additional queueing layer between application and driver. Similarly, individual queues are introduced and controlled for each destination in WiFox @cite_30 . ADWISER @cite_7 tackles rate anomaly only in the , by introducing a dedicated network entity that performs scheduling before the AP. * 0.5em
@cite_30 @cite_33 @cite_7 @cite_32 @cite_0 @cite_20
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We consider wireless LANs such as IEEE 802.11 operating in the unlicensed radio spectrum. While their nominal bit rates have increased considerably, the MAC layer remains practically unchanged despite much research effort spent on improving its performance. We observe that most proposals for tuning the access method focus on a single aspect and disregard others. Our objective is to define an access method optimized for throughput and fairness, able to dynamically adapt to physical channel conditions, to operate near optimum for a wide range of error rates, and to provide equal time shares when hosts use different bit rates.We propose a novel access method derived from 802.11 DCF [2] (Distributed Coordination Function) in which all hosts use similar values of the contention window CW to benefit from good short-term access fairness. We call our method Idle Sense, because each host observes the mean number of idle slots between transmission attempts to dynamically control its contention window. Unlike other proposals, Idle Sense enables each host to estimate its frame error rate, which can be used for switching to the right bit rate. We present simulations showing how the method leads to high throughput, low collision overhead, and low delay. The method also features fast reactivity and time-fair channel allocation. We investigate the optimal selection of minimum contention window values to achieve proportional fairness in a multirate IEEE 802.11e test-bed. Unlike other approaches, the proposed model accounts for the contention-based nature of 802.11's MAC layer operation and considers the case where stations can have different weights corresponding to different throughput classes. Our test-bed evaluation considers both the long-term throughput achieved by wireless stations and the short-term fairness. When all stations have the same transmission rate, optimality is achieved when a station's throughput is proportional to its weight factor, and the optimal minimum contention windows also maximize the aggregate throughput. When stations have different transmission rates, the optimal minimum contention window for high rate stations is smaller than for low rate stations. Furthermore, we compare proportional fairness with time-based fairness, which can be achieved by adjusting packet sizes so that low and high rate stations have equal successful transmission times, or by adjusting the transmission opportunity (TXOP)limit so that high rate stations transmit multiple back-to-back packets and thus occupy the channel for the same time as low rate stations that transmit a single packet. The test-bed experiments show that when stations have different transmission rates and the same weight, proportional fairness achieves higher performance than the time-based fairness approaches, in terms of both aggregate utility and throughput. 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. This paper studies the use of the proportional fairness (PF) utility function as the basis for capacity allocation and scheduling in multi-channel multi-rate wireless networks. Examples of applications include (i) access point (AP) association and transmission scheduling in large-scale IEEE 802.11 networks; and (ii) subcarrier assignment and transmission scheduling in orthogonal frequency division multiplexing (OFDM) cellular networks. The contributions of this paper are twofold. First, we study the fundamental properties and physical economic interpretation of PF. We show by general mathematical arguments that PF leads to equal airtime allocation to individual users for the single-channel case; and equal equivalent airtime allocation to individual users for the multi-channel case, where the equivalent airtime enjoyed by a user is a weighted sum of the airtimes enjoyed by the user on all channels, with the weight of a channel being the price or value of that channel. In addition, we establish the Pareto efficiency of PF solutions and derive characteristics of PF solutions that are useful for the construction of PF algorithms. Second, we generate numerical results for application (i) above. We find that the PF solution simultaneously achieves higher system throughput, better fairness, and lower outage probability with respect to the default AP-association and medium access control (MAC) protocol adopted in today's 802.11 commercial products.