We obtain an association policy for STAs in an IEEE 802.11 WLAN by taking into account explicitly two aspects of practical importance: (a) TCP-controlled short file downloads interspersed with read times (motivated by web browsing), and (b) different STAs associated with an AP at possibly different rates (depending on distance from the AP). Our approach is based on two steps. First, we consider an analytical model to obtain the aggregate AP throughput for long TCP-controlled file downloads when STAs are associated at k different rates r1, r2, : : :, rk; this extends earlier work in the literature. Second, we present a 2-node closed queueing network model to approximate the expected average-sized file download time for a user who shares the AP with other users associated at a multiplicity of rates. These analytical results motivate the proposed association policy, called the Estimated Delay based Association (EDA) policy: Associate with the AP at which the expected file download time is the least. Simulations indicate that for a web-browsing type traffic scenario, EDA outperforms other policies that have been proposed earlier; the extent of improvement ranges from 12.8 to 46.4 for a 9-AP network. To the best of our knowledge, this is the first work that proposes an association policy tailored specifically for web browsing. Apart from this, our analytical results could be of independent interest
From the extensive literature on association in WLANs, several themes can be discerned. In the first group, a newcomer STA assesses each AP (that it can hear) by finding out the per-STA throughput received by STAs associated with it currently @cite_12 , @cite_18 and @cite_3 . In these papers, the authors derive expressions for aggregate AP throughput (with UDP traffic), taking into account the number of STAs associated, as well as the probability of packet loss due to collisions. From this, the per-STA throughput can be calculated, and the newcomer associates with the AP for which the per-STA throughput is the highest.
@cite_18 @cite_3 @cite_12
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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. Most wireless local area network performance estimations are done with the assumption of uniformly distributed (UD) users. In practice, however, stations (STAs) are distributed unevenly among access points (APs) in an extended service area, causing congested hot-spots (HS) and under-utilized APs. Considering a typical network is made up of multiple APs, having some nodes carrying excessive loads degrades the overall network performance. The system performance can be improved by associating STAs efficiently throughout the network, in a sense sharing the network resources fairly among APs and thus relieving congestion. The association algorithm currently employed in IEEE 802.11 systems, that is specifically designed for residential and small office environments, takes into account signal strength as the only parameter and associates STAs to the closest (in signal strength sense) AP, ignoring its load. Novel user association algorithms are required to solve the problems commonly seen in corporate network environments spanning multiple APs, namely congestion relief and resource sharing. In this work, a distributed and online association algorithm is proposed that demonstrates improved average throughput performance, a balanced load distribution as well as fairness across the network compared to the conventional algorithm. Copyright © 2008 John Wiley & Sons, Ltd. 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. In many IEEE 802.11 WLAN deployments, wireless clients have a choice of access points (AP) to connect to. In current systems, clients associate with the access point with the strongest signal to noise ratio. However, such an association mechanism can lead to unequal load sharing, resulting in diminished system performance. In this paper, we first provide a numerical approach based on stochastic dynamic programming to find the optimal client-AP association algorithm for a small topology consisting of two access points. Using the value iteration algorithm, we determine the optimal association rule for the two-AP topology. Next, utilizing the insights obtained from the optimal association rule for the two-AP case, we propose a near-optimal heuristic that we call RAT. We test the efficacy of RAT by considering more realistic arrival patterns and a larger topology. Our results show that RAT performs very well in these scenarios as well. Moreover, RAT lends itself to a fairly simple implementation.