We consider several WLAN stations associated at rates r1, r2, ..., rk with an Access Point. Each station is downloading a long file from a local server, located on the LAN to which the AP is attached. We model these simultaneous TCP-controlled transfers using a Markov Chain. Our analytical approach leads to a procedure to compute aggregate download throughput numerically, and the results match simulations very well.
In the first group, all WLAN entities (STAs and the AP) are assumed to be , , each entity is backlogged permanently. Bianchi @cite_9 , @cite_4 and @cite_10 consider this saturated traffic model. However, our interest is in modelling aggregate throughput, and the saturated traffic model does not capture the situation well.
@cite_10 @cite_9 @cite_4
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Many wireless local area network (WLAN) performance estimations are done with the assumption of uniformly distributed stations (STAs). In practice, on the contrary STAs are distributed unevenly among access points (APs), causing hot-spots and under utilized APs in a wireless network. Considering a WLAN is made up of multiple APs, having some APs carrying excessive loads (i.e. hot-spots) degrades both the considered APs as well as the overall network performance. The system performance can be improved by associating incoming STAs effectively throughout the network, in a sense to balance the network load evenly between APs and relieve the hot-spot congestion. Currently employed user association method in IEEE 802.11 WLANs considers only the received signal strength of APs at STAs, and associates STAs to the closest (in signal strength sense) AP, ignoring its load and interference value.Novel user association algorithms are required for congestion relief and network performance improvement. In this work, a new distributed association algorithm taking into consideration not only the received signal strength of the APs at STAs but also AP loadings and interference is proposed. A new AP load calculation method acknowledging the interference between STAs and APs is presented. Our simulations demonstrate that the proposed algorithm can improve the overall system throughput performance more than 50 and offers a better load distribution across the network compared to conventional association algorithm. Analysis of the 802.11 CSMA CA mechanism has received considerable attention recently. Bianchi presented an analytic model under a saturated traffic assumption. Bianchi's model is accurate, but typical network conditions are nonsaturated and heterogeneous. We present an extension of his model to a nonsaturated environment. The model's predictions, validated against simulation, accurately capture many interesting features of nonsaturated operation. For example, the model predicts that peak throughput occurs prior to saturation. Our model allows stations to have different traffic arrival rates, enabling us to address the question of fairness between competing flows. Although we use a specific arrival process, it encompasses a wide range of interesting traffic types including, in particular, VoIP. The network scenario is that of an infrastructure IEEE 802.11 WLAN with a single AP with which several stations (STAs) are associated. The AP has a finite size buffer for storing packets. In this scenario, we consider TCP-controlled upload and download file transfers between the STAs and a server on the wireline LAN (e.g., 100Mbps Ethernet) to which the AP is connected. In such a situation, it is well known that because of packet losses due to finite buffers at the AP, upload file transfers obtain larger throughputs than download transfers. We provide an analytical model for estimating the upload and download throughputs as a function of the buffer size at the AP. We provide models for the undelayed and delayed ACK cases for a TCP that performs loss recovery only by timeout, and also for TCP Reno. The models are validated in comparison with NS2 simulations. Throughput analysis of bulk TCP downloads in cases where all WLAN stations are associated at the same rate with the AP is available in the literature. In this paper,we extend the analysis to TCP uploads for the case of multirate associations. The approach is based on a two-dimensional semi- Markov model for the number of backlogged stations. Analytical results are in excellent agreement with simulations performed using QUALNET 4.5.