scholarly journals The calibration method of a tandem queueing model with PH service time using NS-3 simulation of a multihop wireless network

2021 ◽  
Vol 2091 (1) ◽  
pp. 012030
Author(s):  
A A Larionov ◽  
A A Mukhtarov ◽  
A M Sokolov
Keyword(s):  
Simulation Model ◽  
Wireless Network ◽  
Ieee 802.11 ◽  
Service Time ◽  
Queuing Theory ◽  
Telecommunication Network ◽  
Packet Transmission ◽  
Queuing Network ◽  
Sample Data ◽  
End To End

Abstract End-to-end delay is one of the key characteristics of communication network performance. This characteristic determines the possibility of using the network for various delay-critical applications like voice or video transmission. One of the widely used approaches to estimating delays is the use of the queuing theory. According to this approach, a telecommunication network is modeled using a multiphase queuing system. Communication channels are modeled using service devices, and the incoming traffic is modeled with random distributions of the inter-arrival intervals between packets. The accuracy of this network model directly depends on how well the service time distributions are chosen. These distributions must consider the specifics of complex telecommunication protocols, size distributions of the transmitted packets, and, in case of wireless channels, the rate of collisions and retransmissions. The paper presents a study of the accuracy of estimates of end-to-end delays in a multi-hop wireless network using a queuing network with a phase-type (PH) service time distributions. To calibrate the model, PH distributions are found using the moments-matching method based on sample data on the duration of packet transmission in IEEE 802.11 channels. This sample data was obtained using a simulation model written in NS-3, taking into account the features of the IEEE 802.11 protocol and the presence of collisions in the network. To evaluate the accuracy, end-to-end delays are calculated using the queuing network and the wireless network simulation model. It is shown that it is possible to obtain reasonably accurate estimates for small networks, but with an increase in the size of the network, the accuracy decreases. In conclusion, recommendations are given to improve the accuracy of modeling.

scholarly journals RT-WABest: A novel end-to-end bandwidth estimation tool in IEEE 802.11 wireless network

2017 ◽  
Vol 13 (2) ◽  
pp. 155014771769488 ◽  
Author(s):  
Tan Yang ◽  
Yuehui Jin ◽  
Yufei Chen ◽  
Yudong Jin
Keyword(s):  
Wireless Network ◽  
Ieee 802.11 ◽  
Convergence Time ◽  
Bandwidth Estimation ◽  
Available Bandwidth ◽  
Estimation Techniques ◽  
Wired Networks ◽  
Resource Limited ◽  
End To End

In 802.11 wireless network, a large number of multimedia applications are emerging. Accurate end-to-end bandwidth estimation techniques can help these applications adjust their behavior accordingly, such as stream’s bitrate adaptation, to improve quality of service. However, most current bandwidth estimation techniques are designed for wired networks that have high intrusiveness and consume long convergence time, which cannot be applied in resource-limited wireless network. In this article, we present a novel bandwidth estimation tool for IEEE 802.11 wireless network, which only needs to be deployed in one end of the end-to-end path and estimate available bandwidth based on round-trip-time measurements with low intrusiveness and short convergence time. We compare our tool with another state-of-the-art tool on an IEEE 802.11 wireless testbed, and the experimental results show that our tool has higher accuracy.

Modeling Bus Capacity for Bus Stops Using Queuing Theory and Diffusion Approximation

2021 ◽  
pp. 036119812110302
Author(s):  
Chao Wang ◽  
Weijie Chen ◽  
Yueru Xu ◽  
Zhirui Ye
Keyword(s):  
Approximation Method ◽  
Service Time ◽  
Diffusion Approximation ◽  
Coefficient Of Variation ◽  
Queuing Theory ◽  
Queuing Model ◽  
Bus Stop ◽  
Proposed Model ◽  
Bus Stops ◽  
Bus Service

For bus service quality and line capacity, one critical influencing factor is bus stop capacity. This paper proposes a bus capacity estimation method incorporating diffusion approximation and queuing theory for individual bus stops. A concurrent queuing system between public transportation vehicles and passengers can be used to describe the scenario of a bus stop. For most of the queuing systems, the explicit distributions of basic characteristics (e.g., waiting time, queue length, and busy period) are difficult to obtain. Therefore, the diffusion approximation method was introduced to deal with this theoretical gap in this study. In this method, a continuous diffusion process was applied to estimate the discrete queuing process. The proposed model was validated using relevant data from seven bus stops. As a comparison, two common methods— Highway Capacity Manual (HCM) formula and M/M/S queuing model (i.e., Poisson arrivals, exponential distribution for bus service time, and S number of berths)—were used to estimate the capacity of the bus stop. The mean absolute percentage error (MAPE) of the diffusion approximation method is 7.12%, while the MAPEs of the HCM method and M/M/S queuing model are 16.53% and 10.23%, respectively. Therefore, the proposed model is more accurate and reliable than the others. In addition, the influences of traffic intensity, bus arrival rate, coefficient of variation of bus arrival headway, service time, coefficient of variation of service time, and the number of bus berths on the capacity of bus stops are explored by sensitivity analyses.

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