A Novel Call Admission Control Policy Using Mobility Prediction and Throttle Mechanism for Supporting QoS in Wireless Cellular Networks

Wu, Chih‐Fu; Lee, Liang-Teh; Chang, Hung-Yuan; Tao, Der-Fu

doi:10.1155/2011/190643

Cited by 12 publications

(4 citation statements)

References 19 publications

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“…The drawback of this scheme is that the reserved bandwidth is often wasted in the hot spot area. In (Wu, 2011) the authors optimize some system parameters in terms of Call Dropping Probabilities (CDPs) and Call Blocking Probabilities (CBPs) introducing a prediction algorithm based on data mining approaches, in order to implement a distributed Call Admission Control (CAC) scheme, considering also the throttle flag as indication of the usage of each cell. Through estimation of MHs trajectory and arrival/departure times in (Aljadhai, 2001), a group of future cells is determined: it constitutes the most likely cluster into which a terminal will move.…”

Section: Literature Overviewmentioning

confidence: 99%

Mobility Analysis for Passive Reservations in Vehicular Cellular Networks Based on Dynamic Programming and Roads Compression

Fazio

Tropea

Vozňák

et al. 2016

International Journal of Interdisciplinary Telecommunications and Networking

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The employment of an appropriate Bandwidth Management Scheme (BMS) is needed in wireless networking, given that the main desire of end-users is to take advantage of satisfactory services, in terms of Quality of Service (QoS), especially when a particular charge is paid to meet the requirement. In this paper the authors are interested in investigating how the continuity of services can be guaranteed in QoS networks, when users move from a cell to another one, under an infrastructure cellular coverage. The only way to face this issue is represented by the employment of in-advance bandwidth reservations, although it leads the system to waste bandwidth resources, since they are not used until the mobile host enters the coverage cell where the passive request has been made. A new scheme for predicting user movements is proposed, taking the advantage of the dynamic programming approach, that is able to reduce the number of possible roads to be considered and thereby increasing/decreasing the accuracy/redundancy of the proposed model. Several simulation runs have been carried out in order to assess the effectiveness of the proposed idea.

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Section: Literature Overviewmentioning

confidence: 99%

Mobility Analysis for Passive Reservations in Vehicular Cellular Networks Based on Dynamic Programming and Roads Compression

Fazio

Tropea

Vozňák

et al. 2016

International Journal of Interdisciplinary Telecommunications and Networking

View full text Add to dashboard Cite

show abstract

“…A prediction algorithm based on data mining approaches for optimization of system parameters in terms of Call Dropping Probabilities (CDP) and Call Blocking Probabilities (CBP) is introduced in [15], in order to implement a distributed Call Admission Control (CAC) scheme, taking also in account the throttle flag as indication of the usage of each cell.…”

Section: Cac Schemesmentioning

confidence: 99%

A new call admission control scheme based on pattern prediction for mobile wireless cellular networks

Santamaria

Lupia

2015

2015 Wireless Telecommunications Symposium (WTS)

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Recently, cellular networking has become really popular, because of its different and growing fields of interest. It is able to satisfy user requirements in terms of Quality of Service, especially when mobility is present, managing hand-over issues in an adequate manner. So, it is very important to decide whether a new connection can be accepted into the system, in order to maximize bandwidth utilization while avoiding quality degradations, with more emphasis for non-tolerant applications. In this paper, the attention is not focused on a particular prediction scheme, but it is shown how a statistical approach can enhance system performance. We employ a general predictor (that can be based on Markov theory, neural networks, data mining approach or similars) and then we integrate it with a threshold-based statistical bandwidth multiplexing scheme in order to propose the Prediction-Based MUltipleXing Call Admission Control (PB-MUX CAC) scheme for cellular networks with mobile hosts. It is able to manage users mobility and to mitigate it, minimizing the amount of wasted bandwidth. Many simulation campaigns have been carried-out, giving us the possibility of evaluating the performance of the proposed idea in terms of number of admitted flows, bandwidth utilization and call blocking/dropping probability.

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“…In RRM, call admission control (CAC) is one of the most integral components in which the fundamental purpose is to judge whether radio resource can be assigned to the incoming channel request, according to the current situation of the system. Recently, CAC has been extensively researched and in order to implement the increasing demand for wireless access to packet-based services, and to make network roaming more seamless, there are a variety of CAC algorithms being proposed [1,3,8,16,17].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis and Investigations of Various SVM Kernels Using Cellular Network KPI Data

Philip¹,

Michael²,

Gabriel³

2019

WCMC

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Classification plays a major role in every field in of human endeavors which Support Vector Machine (SVM) happened to be one of the popular algorithms for classification and prediction. However, the performance of SVM is greatly affected by the choice of a kernel function among other factors. In this research work, SVM is employed and evaluated with six different kernels by varying their parameters especially the training ratio to investigate their performance. The training ratio was varied in the proportion of 60-20-20, 40-30-30 and 20-40-40 to obtain higher classification accuracy. Based on the performance result, GRBK and ERBK kernels are capable of classifying datasets at hand accurately with the best specificity and sensitivity values. From the study, the SVM model with GRBF and ERBF kernels are the best suited for call algorithm data at hand in terms of best specificity and sensitivity values, followed by the RBF kernel. Also, the research further indicates that MLP, polynomial and linear kernels have worse performance. Therefore, despite SVMs being limited to making binary classifications, their superior properties of scalability and generalization capability give them an advantage in other domains.

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A Novel Call Admission Control Policy Using Mobility Prediction and Throttle Mechanism for Supporting QoS in Wireless Cellular Networks

Cited by 12 publications

References 19 publications

Mobility Analysis for Passive Reservations in Vehicular Cellular Networks Based on Dynamic Programming and Roads Compression

Mobility Analysis for Passive Reservations in Vehicular Cellular Networks Based on Dynamic Programming and Roads Compression

A new call admission control scheme based on pattern prediction for mobile wireless cellular networks

Comparative Analysis and Investigations of Various SVM Kernels Using Cellular Network KPI Data

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