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
In the third group, the selection of the AP is made by considering Jain's fairness index @math , @math and @math , corresponding to @math , @math and @math respectively. The AP selected is the one for which the Jain Fairness Index is the highest @cite_6 . In the fourth group, @math is mapped to an expression for AP load @math , and the AP which is least loaded is selected. A variation considers a map from the vector of throughputs @math and the vector of rates of association to the load @cite_28 . Finally, some association policies base their choice on maximizing the minimum element of @math , @math and @math ( max-min fairness''), or maximizing the sum of the logarithms of the elements of @math , @math , @cite_0 , @cite_14 , @cite_13 , @cite_15 , and @cite_1 .
@cite_14 @cite_28 @cite_1 @cite_6 @cite_0 @cite_15 @cite_13
2143690081 2165715302 2949649421 1968587024
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. In multi-rate wireless LANs, throughput-based fair bandwidth allocation can lead to drastically reduced aggregate throughput. To balance aggregate throughput while serving users in a fair manner, proportional fair or time-based fair scheduling has been proposed to apply at each access point (AP). However, since a realistic deployment of wireless LANs can consist of a network of APs, this paper considers proportional fairness in this much wider setting. Our technique is to intelligently associate users with APs to achieve optimal proportional fairness in a network of APs. We propose two approximation algorithms for periodical offline optimization. Our algorithms are the first approximation algorithms in the literature with a tight worst-case guarantee for the NP-hard problem. Our simulation results demonstrate that our algorithms can obtain an aggregate throughput which can be as much as 2.3 times more than that of the max-min fair allocation in 802.11b. While maintaining aggregate throughput, our approximation algorithms outperform the default user-AP association method in the 802.11b standard significantly in terms of fairness. In this paper, we study the two choice balls and bins process when balls are not allowed to choose any two random bins, but only bins that are connected by an edge in an underlying graph. We show that for @math balls and @math bins, if the graph is almost regular with degree @math , where @math is not too small, the previous bounds on the maximum load continue to hold. Precisely, the maximum load is @math . For general @math -regular graphs, we show that the maximum load is @math and also provide an almost matching lower bound of @math . V "o cking [Voc99] showed that the maximum bin size with @math choice load balancing can be further improved to @math by breaking ties to the left. This requires @math random bin choices. We show that such bounds can be achieved by making only two random accesses and querying @math contiguous bins in each access. By grouping a sequence of @math bins into @math groups, each of @math consecutive bins, if each ball chooses two groups at random and inserts the new ball into the least-loaded bin in the lesser loaded group, then the maximum load is @math with high probability. For the mobile users (MUs) installed with IEEE 802.11 wireless adapters, the default best-signal-strength-based access point (AP) selection is limited since it does not consider fairness and multi-rate issues. In this paper, we propose a distributed AP selection algorithm for newly joining MU and already associated MUs to be adaptive to their joining order and the dynamic wireless environment. We also prove the stability of proposed algorithm and analyze its complexity. Finally, with extensive evaluations, we show that proposed scheme can greatly improve the fairness without significantly sacrificing the efficiency.