Improvement of Throughput Prediction Method for Access Point in Multi-rate WLANs Considering Media Access Control and Frame Collision

Hamamoto, Ryo; Takano, Chisa; Obata, Hiroyasu; Ishida, Kenji

doi:10.1109/candar.2015.79

Cited by 5 publications

(17 citation statements)

References 12 publications

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Section: Introductionmentioning

confidence: 99%

“…Moreover, we have determined that the predicted value of [14] is nearly equal to the predicted value reported by [9]. In addition, [14] have compared the proposed method with an existing prediction method relative to the calculation cost. [14] has performed a basic evaluation and a performance comparison, not by a network simulator but by the numerCopyright c 2016 The Institute of Electronics, Information and Communication Engineers ical computation.…”

Section: Introductionmentioning

confidence: 99%

“…* * An earlier version of this paper was presented at the 8th International Workshop on ASON 2015 [1].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, [14] have compared the proposed method with an existing prediction method relative to the calculation cost. [14] has performed a basic evaluation and a performance comparison, not by a network simulator but by the numerCopyright c 2016 The Institute of Electronics, Information and Communication Engineers ical computation. However, it is necessary to consider the impact of CSMA/CA in the MAC layer, because throughput is greatly influenced by frame collision.…”

Section: Introductionmentioning

confidence: 99%

“…We have previously proposed a high-speed AP throughput prediction method that considers terminal distribution (placement) [14] in a multi-rate WLAN environment. Moreover, we have determined that the predicted value of [14] is nearly equal to the predicted value reported by [9].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Hamamoto

Takano

Obata

et al. 2016

IEICE Trans. Inf. & Syst.

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SUMMARYWireless Local Area Networks (WLANs) based on the IEEE 802.11 standard have been increasingly used. Access Points (APs) are being established in various public places, such as railway stations and airports, as well as private residences. Moreover, the rate of public WLAN services continues to increase. Throughput prediction of an AP in a multi-rate environment, i.e., predicting the amount of receipt data (including retransmission packets at an AP), is an important issue for wireless network design. Moreover, it is important to solve AP placement and selection problems. To realize the throughput prediction, we have proposed an AP throughput prediction method that considers terminal distribution. We compared the predicted throughput of the proposed method with a method that uses linear order computation and confirmed the performance of the proposed method, not by a network simulator but by the numerical computation. However, it is necessary to consider the impact of CSMA/CA in the MAC layer, because throughput is greatly influenced by frame collision. In this paper, we derive an effective transmission rate considering CSMA/CA and frame collision. We then compare the throughput obtained using the network simulator NS2 with a prediction value calculated by the proposed method. Simulation results show that the maximum relative error of the proposed method is approximately 6% and 15% for UDP and TCP, respectively, while that is approximately 17% and 21% in existing method.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…* * An earlier version of this paper was presented at the 8th International Workshop on ASON 2015 [1].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Hamamoto

Takano

Obata

et al. 2016

IEICE Trans. Inf. & Syst.

Self Cite

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Time Series Optimization for Energy Prediction in Wi-Fi Infrastructures

Rodriguez-Lozano

Gómez–Pulido

Durán-Domínguez

2018

Time Series Analysis and Forecasting

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Context-aware prediction of access points demand in Wi-Fi networks

et al. 2017

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We present a methodology based on matrix factorization and gradient descent to predict the number of sessions established in the access points of a Wi-Fi network according to the users' behavior. As the network considered in this work is monitored and controlled by software in order to manage users and resources in real time, we may consider it as a cyber-physical system that interacts with the physical world through access points, whose demands can be predicted according to users' activity. These predictions are useful for relocating or reinforcing some access points according to the changing physical environment. In this work we propose a prediction model based on machine learning techniques, which is validated by comparing the prediction results with real user's activity. Our experiments collected the activity of 1,095 users demanding 26,673 network sessions during one month in a Wi-Fi network composed of 10 access points, and the results are qualitatively valid with regard to the previous knowledge. We can conclude that our proposal is suitable for predicting the demand of sessions in access points when some devices are removed taking into account the usual activity of the network users.

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Improvement of Throughput Prediction Method for Access Point in Multi-rate WLANs Considering Media Access Control and Frame Collision

Cited by 5 publications

References 12 publications

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Improvement of Throughput Prediction Scheme Considering Terminal Distribution in Multi-Rate WLAN Considering Both CSMA/CA and Frame Collision

Time Series Optimization for Energy Prediction in Wi-Fi Infrastructures

Context-aware prediction of access points demand in Wi-Fi networks

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