Prediction of round trip delay for wireless networks by a two-state model

Yasuda, Shinya; Yoshida, Hiroshi

doi:10.1109/wcnc.2018.8377039

Cited by 16 publications

(7 citation statements)

References 14 publications

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“…This intuition matches the fact that any delay in a communication network is defned by a minimum value (the ofset), which is caused by physical and computing limitation factors, with a greater occurrence in the delays close to the ofset and some values with a much lower occurrence in higher delays. Besides this, our intuition was supported by a study on the prediction of RTT for wireless networks [32]. Below, you can fnd the defnition of the ofset Gamma distribution:…”

Section: Alga Resultsmentioning

confidence: 76%

TCP-Based Distributed Offloading Architecture for the Future of Untethered Immersive Experiences in Wireless Networks

Morín

Morales

Pérez

et al. 2022

ACM International Conference on Interactive Media Experiences

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Task ofoading has become a key term in the feld of immersive media technologies: it can enable lighter and cheaper devices while providing them higher remote computational capabilities. In this paper we present our TCP-based ofoading architecture. The architecture, has been specifcally designed for immersive media ofoading tasks with a particular care in reducing any processing overhead which can degrade the network performance. We tested the architecture for diferent ofoading scenarios and conditions on two diferent wireless networks: WiFi and 5G millimeter wave technologies. Besides, to test the network on alternative millimeter wave confgurations, currently not available on the actual 5G millimeter rollouts, we used a 5G Radio Access Network (RAN) real-time emulator. This emulator was also used to test the ofoading architecture for an simulated immersive user sharing network resources with other users. We provide insights of the importance of user prioritization techniques for successful immersive media ofoading. The results show a great performance for the tested immersive media scenarios, highlighting the relevance of millimeter wave technology for the future of immersive media applications.

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Section: Alga Resultsmentioning

confidence: 76%

TCP-Based Distributed Offloading Architecture for the Future of Untethered Immersive Experiences in Wireless Networks

Morín

Morales

Pérez

et al. 2022

ACM International Conference on Interactive Media Experiences

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“…We compare our results with other authors, who also work on prediction the round-trip time in computer networks in Table 1. Note that Yasuda and Yoshida [24] predicted only the distribution characteristics of the RTT values rather than actual values. However, the different datasets used and the different methodologies for evaluation of results do not allow for direct comparison of results.…”

Section: Evaluation and Comparison Of Resultsmentioning

confidence: 99%

“…Aibin [23] used ANN to predict network traffic characteristics in elastic optical networks. Yasuda and Yoshida [24] proposed a two-state Markov process based method to predict the probability density function (PDF) of the round-trip time (RTT) in a mobile/wireless network. Recently, the hybrid methods were successfully adopted for handling time-series data and time-periodic events [25] as well as for supervised learning [26].…”

Section: Introductionmentioning

confidence: 99%

Short time prediction of cloud server round-trip time using a hybrid neuro-fuzzy network

Damaševičius¹,

Sidekerskienė²

2020

AIS

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The paper presents a cloud server roundtrip time prediction approach for cloud datacenters using neuro-fuzzy network with eight probability distribution functions (Normal, Rayleigh, Weibull, Gamma, Birnbaum-Saunders, Extreme Value, and Generalized Pareto) used for fuzzification and defuzzification. We predict the Round-Trip Time (RTT), i.e., the time for a network packet to travel from a client to a server and back. The proposed approach can achieve significant reduction in the short-time RTT prediction error, achieving an accuracy of 79.36%. The approach could be useful for increasing the efficiency of client-cloud systems, for example, when taking effective decisions for computational offloading, and contribute to the development of smart cloud computing.

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“…A review of recent applications revealed that the use could be classified into six major areas. Modeling fading channels, shadowing effects [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 ] and attenuation in wireless networks [ 12 ]; Other forms of modeling such as: binary error modeling [ 13 ], beamforming [ 14 ], spatial deployment modeling [ 15 ], delay [ 16 ], source localization [ 17 ], line of sight interference power [ 18 ], atmospheric turbulence [ 19 , 20 ] and color texture characterization [ 21 ]. Modeling by the direct use of gamma distribution fit via parameter estimation [ 22 , 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

“…Other forms of modeling such as: binary error modeling [ 13 ], beamforming [ 14 ], spatial deployment modeling [ 15 ], delay [ 16 ], source localization [ 17 ], line of sight interference power [ 18 ], atmospheric turbulence [ 19 , 20 ] and color texture characterization [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Approximations for the inverse cumulative distribution function of the gamma distribution used in wireless communication

Okagbue

Adamu

Anake

2020

Heliyon

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The use of quantile functions of probability distributions whose cumulative distribution is intractable is often limited in Monte Carlo simulation, modeling, and random number generation. Gamma distribution is one of such distributions, and that has placed limitations on the use of gamma distribution in modeling fading channels and systems described by the gamma distribution. This is due to the inability to find a suitable closed-form expression for the inverse cumulative distribution function, commonly known as the quantile function (QF). This paper adopted the Quantile mechanics approach to transform the probability density function of the gamma distribution to second-order nonlinear ordinary differential equations (ODEs) whose solution leads to quantile approximation. Closed-form expressions, although complex of the QF, were obtained from the solution of the ODEs for degrees of freedom from one to five. The cases where the degree of freedom is not an integer were obtained, which yielded values closed to the R software values via Monte Carlo simulation. This paper provides an alternative for simulating gamma random variables when the degree of freedom is not an integer. The results obtained are fast, computationally efficient and compare favorably with the machine (R software) values using absolute error and Kullback-Leibler divergence as performance metrics.

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Prediction of round trip delay for wireless networks by a two-state model

Cited by 16 publications

References 14 publications

TCP-Based Distributed Offloading Architecture for the Future of Untethered Immersive Experiences in Wireless Networks

TCP-Based Distributed Offloading Architecture for the Future of Untethered Immersive Experiences in Wireless Networks

Short time prediction of cloud server round-trip time using a hybrid neuro-fuzzy network

Approximations for the inverse cumulative distribution function of the gamma distribution used in wireless communication

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