AP Association for Proportional Fairness in Multirate WLANs

Li, Wei; Wang, Shengling; Cui, Yong; Cheng, Xiuzhen; Ran, Xin; Al-Rodhaan, Mznah; Al-Dhelaan, Abdullah

doi:10.1109/tnet.2013.2245145

Cited by 86 publications

(79 citation statements)

References 27 publications

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“…Load balance in WLANs is different from that of the cable distributed system, which is mainly embodied to control AP association and handoff, and makes the load balanced among APs [20]. In the IEEE 802.11 standard, the conventional AP association scheme based on RSSI often leads STAs to make associations with congested APs, while leaving adjacent APs to carry very light load or even to be idle, which results in significant bandwidth waste [13].…”

Section: Load Balancementioning

confidence: 99%

Joint AP Association and Bandwidth Allocation Optimization Algorithm in High-Dense WLANs

2018

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Regarding access point (AP) overload and performance anomaly which is caused by mobile terminals with different bitrates, a joint AP association and bandwidth allocation optimization algorithm is presented in this paper. Meanwhile, load balancing and proportional fairness are analyzed and formulated as an optimization model. Then, we present a Fair Bandwidth Allocation algorithm based on clients' Business Priority (FBA-BP), which allocates bandwidth based on the bandwidth demand of clients and their business priority. Furthermore, we propose a Categorized AP Association algorithm based on clients' demands (CAA-BD), which classifies APs by different types of clients and chooses an optimal associating AP for a new client according to AP categories and the aggregated demand transmission time that are calculated by the FBA-BP algorithm. The CAA-BD can achieve load balance and solve the performance anomaly caused by multi-rate clients coexisting. The simulation results show that our proposed algorithm obtains significant performance in terms of AP utilization, throughput, transmission delay and channel fairness in different client density levels compared with the categorized and Strong Signal First (SSF) algorithms.

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Section: Load Balancementioning

confidence: 99%

Joint AP Association and Bandwidth Allocation Optimization Algorithm in High-Dense WLANs

2018

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“…Works on distributed or centralized solutions of the user-BS association problem in HetSNets [6][7][8][9][10][11][12][13][14][15][16] and works on the link activation problem [? ], [17], [18].…”

Section: B Related Workmentioning

confidence: 99%

“…However, both proposed optimal method and heuristic algorithm have high complexity. The work in [8] studies the user-BS association problem for fairness and load balancing (see [14][15][16] for more papers on fairness and load balancing). It solves the user-BS association problem by relaxation and rounding techniques which remove the combinatorial nature of the problem.…”

Section: B Related Workmentioning

confidence: 99%

User–Base-Station Association in HetSNets: Complexity and Efficient Algorithms

Mlika

Goonewardena

Ajib

et al. 2017

IEEE Trans. Veh. Technol.

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Abstract-This work considers the problem of user association to small-cell base stations (SBSs) in a heterogeneous and small-cell network (HetSNet). Two optimization problems are investigated, which are maximizing the set of associated users to the SBSs (the unweighted problem) and maximizing the set of weighted associated users to the SBSs (the weighted problem), under signal-to-interference-plus-noise ratio constraints. Both problems are formulated as linear integer programs. The weighted problem is known to be NP-hard and, in this paper, the unweighted problem is proved to be NP-hard as well. Therefore, this paper develops two heuristic polynomial-time algorithms to solve both problems. The computational complexity of the proposed algorithms is evaluated and is shown to be far more efficient than the complexity of the optimal brute-force (BF) algorithm. Moreover, the paper benchmarks the performance of the proposed algorithms against the BF algorithm, the branchand-bound CPLEX-based algorithm and state-of-the-art algorithms, through numerical simulations. The results demonstrate the close-to-optimal performance of the proposed algorithms. They also show that the weighted problem can be solved to provide solutions that are fair between users or to balance the load among SBSs.

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“…We use simple probability estimation to simulate the effect of different amounts of real-time data. Sharing the same real-time data, both methods will lose 40% accuracy when the number of real-time data reduces from nine to two per location because of the unstable Wi-Fi signals [15]. Although the amount of real-time data is very important to locating accuracy, it will certainly cause more energy consumption.…”

Section: Analysis Of Energy Consumptionmentioning

confidence: 99%

SmartFix: Indoor Locating Optimization Algorithm for Energy-Constrained Wearable Devices

Wang

2017

Wireless Communications and Mobile Computing

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Indoor localization technology based on Wi-Fi has long been a hot research topic in the past decade. Despite numerous solutions, new challenges have arisen along with the trend of smart home and wearable computing. For example, power efficiency needs to be significantly improved for resource-constrained wearable devices, such as smart watch and wristband. For a Wi-Fi-based locating system, most of the energy consumption can be attributed to real-time radio scan; however, simply reducing radio data collection will cause a serious loss of locating accuracy because of unstable Wi-Fi signals. In this paper, we present SmartFix, an optimization algorithm for indoor locating based on Wi-Fi RSS. SmartFix utilizes user motion features, extracts characteristic value from history trajectory, and corrects deviation caused by unstable Wi-Fi signals. We implemented a prototype of SmartFix both on Moto 360 2nd-generation Smartwatch and on HTC One Smartphone. We conducted experiments both in a large open area and in an office hall. Experiment results demonstrate that average locating error is less than 2 meters for more than 80% cases, and energy consumption is only 30% of Wi-Fi fingerprinting method under the same experiment circumstances.

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AP Association for Proportional Fairness in Multirate WLANs

Cited by 86 publications

References 27 publications

Joint AP Association and Bandwidth Allocation Optimization Algorithm in High-Dense WLANs

Joint AP Association and Bandwidth Allocation Optimization Algorithm in High-Dense WLANs

User–Base-Station Association in HetSNets: Complexity and Efficient Algorithms

SmartFix: Indoor Locating Optimization Algorithm for Energy-Constrained Wearable Devices

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