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
@cite_4: The traffic load of wireless LANs is often unevenly distributed among the access points (APs), which results in unfair bandwidth allocation among users. We argue that the load imbalance and consequent unfair bandwidth allocation can be greatly reduced by intelligent association control. In this paper, we present an efficient solution to determine the user-AP associations for max-min fair bandwidth allocation. We show the strong correlation between fairness and load balancing, which enables us to use load balancing techniques for obtaining optimal max-min fair bandwidth allocation. As this problem is NP-hard, we devise algorithms that achieve constant-factor approximation. In our algorithms, we first compute a fractional association solution, in which users can be associated with multiple APs simultaneously. This solution guarantees the fairest bandwidth allocation in terms of max-min fairness. Then, by utilizing a rounding method, we obtain the integral solution from the fractional solution. We also consider time fairness and present a polynomial-time algorithm for optimal integral solution. We further extend our schemes for the on-line case where users may join and leave dynamically. Our simulations demonstrate that the proposed algorithms achieve close to optimal load balancing (i.e., max-min fairness) and they outperform commonly used heuristics.
@cite_22: The popularity of IEEE 802.11 WLANs has led to dense deployments in urban areas. High density leads to sub-optimal performance unless the interfering networks learn how to optimally use and share the spectrum. This paper proposes two fully distributed algorithms that allow (i) multiple interfering 802.11 access points to select their operating frequency in order to minimize interference, and (ii) users to choose the access point they attach to, in order to get their fair share of the whole network bandwidth. The proposed algorithms rely on Gibbs sampler, and do not require explicit coordination among the wireless devices. They only require the participating wireless nodes to measure local quantities such as interference and transmission delay. The algorithms are shown to lead to optimal bandwidth sharing, where optimality is defined according to the minimal potential delay. We analytically prove the convergence of the proposed algorithms, and study their performance by simulation.
@cite_7: In wireless local area networks, often a station can potentially associate with more than one access point (AP). Therefore, a relevant question is which AP to select 'best' from a list of candidate ones. In IEEE 802.11, the user simply associates to the AP with the strongest received signal strength. However, this may result in a significant load imbalance between several APs. Moreover, the multi-rate flexibility provided by several IEEE 802.11 variants can cause low bit rate stations to negatively affect high bit rate ones and consequently degrade the overall network throughput. This paper investigates the various aspects of 'best' AP selection for IEEE 802.11 systems. In detail, we first derive a new decision metric which can be used for AP selection. Using this metric, we propose two new selection mechanisms which are decentralised in the sense that the decision is performed by each station, given appropriate status information of each AP. In fact, only few bytes of status information have to be added to the Beacon and Probe Response frames which does not impose significant overhead. We show that our mechanism improves mean quality of service of all stations and better utilises network resources compared to the conventional one implemented today in IEEE 802.11 devices. Also, the schemes are appealing in terms of stability and provide their performance improvement even for denser or lighter network configurations.
@cite_2: 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.
@cite_20: 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.
In the second group, we have association policies that start from the throughputs that individual STAs are getting at present @cite_22 , @cite_7 , @cite_20 , @cite_2 and @cite_4 . For each STA associated with an AP, the ratio of throughput to the physical rate of association is obtained, and this fraction is added over all the STAs. This leads to a figure of merit for each AP, and the newcomer chooses the AP with the highest figure of merit.