Fifth Generation Vehicular Cloud Computing (5G-VCC) systems use heterogeneous network access technologies to fulfill the requirements of modern vehicular services. Efficient network selection algorithms are required to satisfy the constraints of Driver Assistance (DA) services, Passengers Entertainment and Information (PEnI) services and Medical (MED) services that provided to vehicular users. The presence of MED services affects the importance of other services in situations where patients with immediate health status exist within the vehicle. This paper proposes a network selection scheme which considers the patient health status to adapt the importance of each service. The scheme consists of two Fuzzy Multi Attribute Decision Making (FMADM) algorithms: the Trapezoidal Fuzzy Adaptive Analytic Network Process (TF-AANP) to calculate the relative importance of each vehicular service and the selection criteria, as well as the Trapezoidal Fuzzy Topsis with Adaptive Criteria Weights (TFT-ACW) to accomplish the ranking of the candidate networks. Both algorithms use Interval-Valued Trapezoidal Fuzzy Numbers (IVTFN). Performance evaluation shows that the suggested method outperforms existing algorithms by satisfying the constraints of MED services when the patient health status becomes immediate.
Throughput in cooperative wireless networksjournalBEEI
Cognitive radio networks emerge as a solution to fixed allocation issues and spectrum scarcity through the dynamic access to spectrum. In cognitive networks, users must make intelligent decisions based on spectrum variation and actions taken by other users. Under this dynamic, cooperative systems can significantly improve quality of service parameters. This article presents the comparative study of the multi-criteria decision-making algorithms SAW and FFAHP through four levels of cooperation (10%, 20%, 50%, 80% y 100%) established between secondary users. The results show the performance evaluation obtained through of simulations and experimental measurements. The analysis is carried out based on throughput, depending on the class of service and the type of traffic.
Performance Enhancement of MIMO-OFDM using Redundant Residue Number System IJECEIAES
Telecommunication industry requires high capacity networks with high data rates which are achieved through utilization of Multiple-Input-MultipleOutput (MIMO) communication along with Orthogonal Frequency Division Multiplexing (OFDM) system. Still, the communication channel suffers from noise, interference or distortion due to hardware design limitations, and channel environment, and to combat these challenges, and achieve enhanced performance; various error control techniques are implemented to enable the receiver to detect any possible received errors and correct it and thus; for a certain transmitted signal power the system would have lower Bit Error Rate (BER). The provided research focuses on Redundant Residue Number System (RRNS) coding as a Forward Error Correction (FEC) scheme that improves the performance of MIMO-OFDM based wireless communications in comparison with current methods as Low-Density Parity Check (LDPC) coders at the transmitter side or equalizers at receiver side. The Bit Error Rate (BER) performance over the system was measured using MATLAB tool for different simulated channel conditions, including the effect of signal amplitude reduction and multipath delay spreading. Simulation results had shown that RRNS coding scheme provides an enhancement in system performance over conventional error detection and correction coding schemes by utilizing the distinct features of Residue Number System (RNS).
SYNTHETICAL ENLARGEMENT OF MFCC BASED TRAINING SETS FOR EMOTION RECOGNITIONcsandit
Emotional state recognition through speech is being a very interesting research topic nowadays.
Using subliminal information of speech, it is possible to recognize the emotional state of the
person. One of the main problems in the design of automatic emotion recognition systems is the
small number of available patterns. This fact makes the learning process more difficult, due to
the generalization problems that arise under these conditions.
In this work we propose a solution to this problem consisting in enlarging the training set
through the creation the new virtual patterns. In the case of emotional speech, most of the
emotional information is included in speed and pitch variations. So, a change in the average
pitch that does not modify neither the speed nor the pitch variations does not affect the
expressed emotion. Thus, we use this prior information in order to create new patterns applying
a pitch shift modification in the feature extraction process of the classification system. For this
purpose, we propose a frequency scaling modification of the Mel Frequency Cepstral
Coefficients, used to classify the emotion. This proposed process allows us to synthetically
increase the number of available patterns in thetraining set, thus increasing the generalization
capability of the system and reducing the test error.
Failure prediction of e-banking application system using adaptive neuro fuzzy...IJECEIAES
Problems often faced by IT operation unit is the difficulty in determining the cause of the failure of an incident such as slowing access to the internet banking url, non-functioning of some features of m-banking or even the cessation of the entire e-banking service. The proposed method to modify ANFIS with Fuzzy C-Means Clustering (FCM) approach is applied to detect four typical kinds of faults that may happen in the e-banking system, which are application response times, transaction per second, server utilization and network performance. Input data is obtained from the e-banking monitoring results throughout 2017 that become data training and data testing. The study shows that an ANFIS modeling with FCM optimized input has a RMSE 0.006 and increased accuracy by 1.27% compared to ANFIS without FCM optimization.
F EATURE S ELECTION USING F ISHER ’ S R ATIO T ECHNIQUE FOR A UTOMATIC ...IJCI JOURNAL
Automatic Speech Recognition (ASR) involves mainly
two steps; feature extraction and classification
(pattern recognition). Mel Frequency Cepstral Coeff
icient (MFCC) is used as one of the prominent featu
re
extraction techniques in ASR. Usually, the set of a
ll 12 MFCC coefficients is used as the feature vect
or in
the classification step. But the question is whethe
r the same or improved classification accuracy can
be
achieved by using a subset of 12 MFCC as feature ve
ctor. In this paper, Fisher’s ratio technique is us
ed for
selecting a subset of 12 MFCC coefficients that con
tribute more in discriminating a pattern. The selec
ted
coefficients are used in classification with Hidden
Markov Model (HMM) algorithm. The classification
accuracies that we get by using 12 coefficients and
by using the selected coefficients are compare
Throughput in cooperative wireless networksjournalBEEI
Cognitive radio networks emerge as a solution to fixed allocation issues and spectrum scarcity through the dynamic access to spectrum. In cognitive networks, users must make intelligent decisions based on spectrum variation and actions taken by other users. Under this dynamic, cooperative systems can significantly improve quality of service parameters. This article presents the comparative study of the multi-criteria decision-making algorithms SAW and FFAHP through four levels of cooperation (10%, 20%, 50%, 80% y 100%) established between secondary users. The results show the performance evaluation obtained through of simulations and experimental measurements. The analysis is carried out based on throughput, depending on the class of service and the type of traffic.
Performance Enhancement of MIMO-OFDM using Redundant Residue Number System IJECEIAES
Telecommunication industry requires high capacity networks with high data rates which are achieved through utilization of Multiple-Input-MultipleOutput (MIMO) communication along with Orthogonal Frequency Division Multiplexing (OFDM) system. Still, the communication channel suffers from noise, interference or distortion due to hardware design limitations, and channel environment, and to combat these challenges, and achieve enhanced performance; various error control techniques are implemented to enable the receiver to detect any possible received errors and correct it and thus; for a certain transmitted signal power the system would have lower Bit Error Rate (BER). The provided research focuses on Redundant Residue Number System (RRNS) coding as a Forward Error Correction (FEC) scheme that improves the performance of MIMO-OFDM based wireless communications in comparison with current methods as Low-Density Parity Check (LDPC) coders at the transmitter side or equalizers at receiver side. The Bit Error Rate (BER) performance over the system was measured using MATLAB tool for different simulated channel conditions, including the effect of signal amplitude reduction and multipath delay spreading. Simulation results had shown that RRNS coding scheme provides an enhancement in system performance over conventional error detection and correction coding schemes by utilizing the distinct features of Residue Number System (RNS).
SYNTHETICAL ENLARGEMENT OF MFCC BASED TRAINING SETS FOR EMOTION RECOGNITIONcsandit
Emotional state recognition through speech is being a very interesting research topic nowadays.
Using subliminal information of speech, it is possible to recognize the emotional state of the
person. One of the main problems in the design of automatic emotion recognition systems is the
small number of available patterns. This fact makes the learning process more difficult, due to
the generalization problems that arise under these conditions.
In this work we propose a solution to this problem consisting in enlarging the training set
through the creation the new virtual patterns. In the case of emotional speech, most of the
emotional information is included in speed and pitch variations. So, a change in the average
pitch that does not modify neither the speed nor the pitch variations does not affect the
expressed emotion. Thus, we use this prior information in order to create new patterns applying
a pitch shift modification in the feature extraction process of the classification system. For this
purpose, we propose a frequency scaling modification of the Mel Frequency Cepstral
Coefficients, used to classify the emotion. This proposed process allows us to synthetically
increase the number of available patterns in thetraining set, thus increasing the generalization
capability of the system and reducing the test error.
Failure prediction of e-banking application system using adaptive neuro fuzzy...IJECEIAES
Problems often faced by IT operation unit is the difficulty in determining the cause of the failure of an incident such as slowing access to the internet banking url, non-functioning of some features of m-banking or even the cessation of the entire e-banking service. The proposed method to modify ANFIS with Fuzzy C-Means Clustering (FCM) approach is applied to detect four typical kinds of faults that may happen in the e-banking system, which are application response times, transaction per second, server utilization and network performance. Input data is obtained from the e-banking monitoring results throughout 2017 that become data training and data testing. The study shows that an ANFIS modeling with FCM optimized input has a RMSE 0.006 and increased accuracy by 1.27% compared to ANFIS without FCM optimization.
F EATURE S ELECTION USING F ISHER ’ S R ATIO T ECHNIQUE FOR A UTOMATIC ...IJCI JOURNAL
Automatic Speech Recognition (ASR) involves mainly
two steps; feature extraction and classification
(pattern recognition). Mel Frequency Cepstral Coeff
icient (MFCC) is used as one of the prominent featu
re
extraction techniques in ASR. Usually, the set of a
ll 12 MFCC coefficients is used as the feature vect
or in
the classification step. But the question is whethe
r the same or improved classification accuracy can
be
achieved by using a subset of 12 MFCC as feature ve
ctor. In this paper, Fisher’s ratio technique is us
ed for
selecting a subset of 12 MFCC coefficients that con
tribute more in discriminating a pattern. The selec
ted
coefficients are used in classification with Hidden
Markov Model (HMM) algorithm. The classification
accuracies that we get by using 12 coefficients and
by using the selected coefficients are compare
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd::Imageproc...sunda2011
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd
IEEE projects, final year projects, students project, be project, engineering projects, academic project, project center in madurai, trichy, chennai, kollam, coimbatore
Microstrip circular patch array antenna for electronic toll collectioneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Spectral opportunity selection based on the hybrid algorithm AHP-ELECTRETELKOMNIKA JOURNAL
Due to an ever-growing demand for spectrum and the fast-paced developmentof wireless applications, technologies such as cognitive radio enablethe efficient use of the spectrum. The objective of the present article is todesign an algorithm capable of choosing the best channel for data transmission.It uses quantitative methods that can modify behavior by changing qualityparameters in the channel. To achieve this task, a hybrid decision-makingalgorithm is designed that combinesanalytical hierarchy process(AHP)algorithms and adjusts the weights of each channel parameter, using a prioritytable. TheElimination Et Choix Tranduisant La Realité(ELECTRE)algorithm processes the information from each channel through a weightmatrix and then delivers the most favorable result for the transmitted data. Theresults reveal that the hybrid AHP-ELECTRE algorithm has a suitableperformance, which improves the throughput rate by 14% compared to similaralternatives.
Hybrid multi objectives genetic algorithms and immigrants scheme for dynamic ...khalil IBRAHIM
the main concept of intelligent optimization techniques, artificial neural networks, and new genetic algorithms to solve the multi-objective multicast routing problems with shortest path (SP) problem that used in the addresses networks and improve all processes addressing in the wireless communications based on multi-objective optimization. The most important characteristics in mobile wireless networks is the topology dynamics and the network topology changes over time, the routing problem (SPRP) in mobile ad hoc networks (MANETs) turns out to be a dynamic optimization problem[13], the hybrid immigrants multiple-objective genetic algorithm (HIMOGAs) in the real- world are dynamic in nature, that has objective functions, constraints, and parameters, the dynamic optimization problems (DOPs) are a big challenges to evolutionary multi-objective, since any environmental change may affect the objective vector, constraints, and parameters, HIMOGA for the optimization goal is to track the moving of parameters and get a sequence of approximations solutions over time. The quantity of services (QoS) is supporting guarantee for all data traffic and getting the maximizing utilization for network, the QoS based on multicast routing offers significant challenges, and increases to use an efficient multicast routing protocol that will be able to check multicast routing and satisfying QoS constraints, The author propose to use HIMOGAs and SP algorithm to solve multicast problem that produces new generation wireless networks with immigrants schema to get high-quality solutions after each change and satisfying all objectives.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Text Independent Speaker Identification Using Imfcc Integrated With IcaIOSR Journals
Abstract: Over the years, more research work has been reported in literature regarding text independent
speaker identification using MFC coefficients. MFCC is one of the best methods modeled on human auditory
system. Murali et al (2011) [1] has developed a Text independent speaker identification using MFC coefficients
which follows Generalized Gaussian mixer model. MFCC, because of its filter bank structure it captures the
characteristics of information more effectively in lower frequency region than higher region, because of this,
valuable information in high frequency region may be lost. In this paper we rectify the above problem by
retrieving the information in high frequency region by inverting the Mel bank structure. The dimensionality and
dependency of above features were reduced by integrating with ICA. Here Text Independent Speaker
Identification system is developed by using Generalized Gaussian Mixer Model .By the experimentation, it was
observed that this model outperforms the earlier existing models.
Keywords: Independent Component Analysis; Generalized Gaussian Mixer Model; Inverted Mel frequency
cepstral coefficients; Bayesian classifier; EM algorithm.
Optimal Coefficient Selection For Medical Image FusionIJERA Editor
Medical image fusion is one of the major research fields in image processing. Medical imaging has become a
vital component in major clinical applications such as detection/ diagnosis and treatment. Joint analysis of
medical data collected from same patient using different modalities is required in many clinical applications.
This paper introduces an optimal fusion technique for multiscale-decomposition based fusion of medical images
and measuring its performance with existing fusion techniques. This approach incorporates genetic algorithm
for optimal coefficient selection and employ various multiscale filters for noise removal. Experiments
demonstrate that proposed fusion technique generate better results than existing rules. The performance of
proposed system is found to be superior to existing schemes used in this literature.
Towards a formal analysis of the multi-robot task allocation problem using se...journalBEEI
Nowadays, the multi-robot task allocation problem is one of the most challenging problems in multi-robot systems. It concerns the optimal assignment of a set of tasks to several robots while optimizing a given criterion subject to some constraints. This problem is very complex, particularly when handling large groups of robots and tasks. We propose a formal analysis of the task allocation problem in a multi-robot system, based on set theory concepts. We believe that this analysis will help researchers understand the nature of the problem, its time complexity, and consequently develop efficient solutions. Also, we used that formal analysis to formulate two well-known taxonomies of multi-robot task allocation problems. Finally, a generic solving scheme of multi-robot task allocation problems is proposed and illustrated on assigning papers to reviewers within a journal.
Comparison of Neural Network Training Functions for Hematoma Classification i...IOSR Journals
Classification is one of the most important task in application areas of artificial neural networks
(ANN).Training neural networks is a complex task in the supervised learning field of research. The main
difficulty in adopting ANN is to find the most appropriate combination of learning, transfer and training
function for the classification task. We compared the performances of three types of training algorithms in feed
forward neural network for brain hematoma classification. In this work we have selected Gradient Descent
based backpropagation, Gradient Descent with momentum, Resilence backpropogation algorithms. Under
conjugate based algorithms, Scaled Conjugate back propagation, Conjugate Gradient backpropagation with
Polak-Riebreupdates(CGP) and Conjugate Gradient backpropagation with Fletcher-Reeves updates (CGF).The
last category is Quasi Newton based algorithm, under this BFGS, Levenberg-Marquardt algorithms are
selected. Proposed work compared training algorithm on the basis of mean square error, accuracy, rate of
convergence and correctness of the classification. Our conclusion about the training functions is based on the
simulation results
APPLYING DYNAMIC MODEL FOR MULTIPLE MANOEUVRING TARGET TRACKING USING PARTICL...IJITCA Journal
In this paper, we applied a dynamic model for manoeuvring targets in SIR particle filter algorithm for improving tracking accuracy of multiple manoeuvring targets. In our proposed approach, a color distribution model is used to detect changes of target's model . Our proposed approach controls
deformation of target's model. If deformation of target's model is larger than a predetermined threshold,then the model will be updated. Global Nearest Neighbor (GNN) algorithm is used as data association algorithm. We named our proposed method as Deformation Detection Particle Filter (DDPF) . DDPF
approach is compared with basic SIR-PF algorithm on real airshow videos. Comparisons results show that, the basic SIR-PF algorithm is not able to track the manoeuvring targets when the rotation or scaling is occurred in target' s model. However, DDPF approach updates target's model when the rotation or
scaling is occurred. Thus, the proposed approach is able to track the manoeuvring targets more efficiently
and accurately.
The purpose research is to develop the decision model of Multi-Criteria Group Decision Making (MCGDM) into Interval Value Fuzzy Multi-Criteria Group Decision Making (IV-FMCGDM), while the specific purpose is to construct decision-making model of Adaptive Interval Value Fuzzy Analytic Hierarchy Process (AIV- FAHP) uses Triangular Fuzzy Number (TFN) and group decision aggregation functions using Interval Value Geometric Means Aggregation (IV-GMA). The novelty research is to study the concept of group decision making by improving the middle point on the Interval Value Triangular Fuzzy Number (IV TFN). It provides more accurate modeling, and better rating performance, and more effective linguistic representation. This research produced a new decision-making model and algorithm based on AIV-FAHP used to measure the quality of e-learning.
A VHO Scheme for supporting Healthcare Services in 5G Vehicular Cloud Computi...University of Piraeus
Fifth Generation Vehicular Cloud Computing (5G-VCC) systems use heterogeneous network access technologies in order to fulfill the requirements of modern services, including medical services with strict constraints. Therefore, the need for efficient Vertical Handover (VHO) management schemes must be addressed. In this paper, a VHO management scheme for supporting medical services in 5G-VCC systems, is described. It consists of the VHO initiation and the network selection processes, while at the same time, the vehicle’s velocity, its current connection type, as well as the status of the onboard patient’s health, are considered. Specifically, during the VHO initiation process the necessity to perform handover is evaluated. Subsequently, the network selection process selects the appropriate network alternative considering both medical service requirements and patients’ health status. The proposed scheme is applied to a 5G-VCC system which includes Long Term Evolution (LTE) and Worldwide Interoperability Microwave Access (WiMAX) Macrocells and Femtocells, as well as Wireless Access for Vehicular Environment Road Side Units (WAVE RSUs). Performance evaluation shows that the proposed algorithm outperforms existing VHO management schemes.
A Vertical Handover Management Scheme for VANET Cloud Computing SystemsUniversity of Piraeus
Vehicular Cloud Computing (VCC) systems use heterogeneous network access technologies in order to fulfill the requirements of modern services. Therefore, the need for efficient Vertical Handover (VHO) management schemes must be addressed. In this paper a VHO management scheme for VCC systems is described. The proposed method takes into account the vehicles velocity as well as its current connection type and applies a two step VHO algorithm to reduce operations’ costs and optimize mobility management. Accordingly, as a first step a VHO initiation process evaluates the necessity to perform handover and subsequently a network selection process selects the appropriate network alternative considering both vehicular service requirements and operators’ policies. The proposed scheme is applied to a VCC system which includes Long Term Evolution (LTE) Macrocells and Femtocells as well as 802.11p Road Side Units (RSUs). Performance evaluation shows that the suggested algorithm ensures the Always Best Connection (ABC) principle, while at the same time outperforms existing VHO management schemes.
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd::Imageproc...sunda2011
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd
IEEE projects, final year projects, students project, be project, engineering projects, academic project, project center in madurai, trichy, chennai, kollam, coimbatore
Microstrip circular patch array antenna for electronic toll collectioneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Spectral opportunity selection based on the hybrid algorithm AHP-ELECTRETELKOMNIKA JOURNAL
Due to an ever-growing demand for spectrum and the fast-paced developmentof wireless applications, technologies such as cognitive radio enablethe efficient use of the spectrum. The objective of the present article is todesign an algorithm capable of choosing the best channel for data transmission.It uses quantitative methods that can modify behavior by changing qualityparameters in the channel. To achieve this task, a hybrid decision-makingalgorithm is designed that combinesanalytical hierarchy process(AHP)algorithms and adjusts the weights of each channel parameter, using a prioritytable. TheElimination Et Choix Tranduisant La Realité(ELECTRE)algorithm processes the information from each channel through a weightmatrix and then delivers the most favorable result for the transmitted data. Theresults reveal that the hybrid AHP-ELECTRE algorithm has a suitableperformance, which improves the throughput rate by 14% compared to similaralternatives.
Hybrid multi objectives genetic algorithms and immigrants scheme for dynamic ...khalil IBRAHIM
the main concept of intelligent optimization techniques, artificial neural networks, and new genetic algorithms to solve the multi-objective multicast routing problems with shortest path (SP) problem that used in the addresses networks and improve all processes addressing in the wireless communications based on multi-objective optimization. The most important characteristics in mobile wireless networks is the topology dynamics and the network topology changes over time, the routing problem (SPRP) in mobile ad hoc networks (MANETs) turns out to be a dynamic optimization problem[13], the hybrid immigrants multiple-objective genetic algorithm (HIMOGAs) in the real- world are dynamic in nature, that has objective functions, constraints, and parameters, the dynamic optimization problems (DOPs) are a big challenges to evolutionary multi-objective, since any environmental change may affect the objective vector, constraints, and parameters, HIMOGA for the optimization goal is to track the moving of parameters and get a sequence of approximations solutions over time. The quantity of services (QoS) is supporting guarantee for all data traffic and getting the maximizing utilization for network, the QoS based on multicast routing offers significant challenges, and increases to use an efficient multicast routing protocol that will be able to check multicast routing and satisfying QoS constraints, The author propose to use HIMOGAs and SP algorithm to solve multicast problem that produces new generation wireless networks with immigrants schema to get high-quality solutions after each change and satisfying all objectives.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Text Independent Speaker Identification Using Imfcc Integrated With IcaIOSR Journals
Abstract: Over the years, more research work has been reported in literature regarding text independent
speaker identification using MFC coefficients. MFCC is one of the best methods modeled on human auditory
system. Murali et al (2011) [1] has developed a Text independent speaker identification using MFC coefficients
which follows Generalized Gaussian mixer model. MFCC, because of its filter bank structure it captures the
characteristics of information more effectively in lower frequency region than higher region, because of this,
valuable information in high frequency region may be lost. In this paper we rectify the above problem by
retrieving the information in high frequency region by inverting the Mel bank structure. The dimensionality and
dependency of above features were reduced by integrating with ICA. Here Text Independent Speaker
Identification system is developed by using Generalized Gaussian Mixer Model .By the experimentation, it was
observed that this model outperforms the earlier existing models.
Keywords: Independent Component Analysis; Generalized Gaussian Mixer Model; Inverted Mel frequency
cepstral coefficients; Bayesian classifier; EM algorithm.
Optimal Coefficient Selection For Medical Image FusionIJERA Editor
Medical image fusion is one of the major research fields in image processing. Medical imaging has become a
vital component in major clinical applications such as detection/ diagnosis and treatment. Joint analysis of
medical data collected from same patient using different modalities is required in many clinical applications.
This paper introduces an optimal fusion technique for multiscale-decomposition based fusion of medical images
and measuring its performance with existing fusion techniques. This approach incorporates genetic algorithm
for optimal coefficient selection and employ various multiscale filters for noise removal. Experiments
demonstrate that proposed fusion technique generate better results than existing rules. The performance of
proposed system is found to be superior to existing schemes used in this literature.
Towards a formal analysis of the multi-robot task allocation problem using se...journalBEEI
Nowadays, the multi-robot task allocation problem is one of the most challenging problems in multi-robot systems. It concerns the optimal assignment of a set of tasks to several robots while optimizing a given criterion subject to some constraints. This problem is very complex, particularly when handling large groups of robots and tasks. We propose a formal analysis of the task allocation problem in a multi-robot system, based on set theory concepts. We believe that this analysis will help researchers understand the nature of the problem, its time complexity, and consequently develop efficient solutions. Also, we used that formal analysis to formulate two well-known taxonomies of multi-robot task allocation problems. Finally, a generic solving scheme of multi-robot task allocation problems is proposed and illustrated on assigning papers to reviewers within a journal.
Comparison of Neural Network Training Functions for Hematoma Classification i...IOSR Journals
Classification is one of the most important task in application areas of artificial neural networks
(ANN).Training neural networks is a complex task in the supervised learning field of research. The main
difficulty in adopting ANN is to find the most appropriate combination of learning, transfer and training
function for the classification task. We compared the performances of three types of training algorithms in feed
forward neural network for brain hematoma classification. In this work we have selected Gradient Descent
based backpropagation, Gradient Descent with momentum, Resilence backpropogation algorithms. Under
conjugate based algorithms, Scaled Conjugate back propagation, Conjugate Gradient backpropagation with
Polak-Riebreupdates(CGP) and Conjugate Gradient backpropagation with Fletcher-Reeves updates (CGF).The
last category is Quasi Newton based algorithm, under this BFGS, Levenberg-Marquardt algorithms are
selected. Proposed work compared training algorithm on the basis of mean square error, accuracy, rate of
convergence and correctness of the classification. Our conclusion about the training functions is based on the
simulation results
APPLYING DYNAMIC MODEL FOR MULTIPLE MANOEUVRING TARGET TRACKING USING PARTICL...IJITCA Journal
In this paper, we applied a dynamic model for manoeuvring targets in SIR particle filter algorithm for improving tracking accuracy of multiple manoeuvring targets. In our proposed approach, a color distribution model is used to detect changes of target's model . Our proposed approach controls
deformation of target's model. If deformation of target's model is larger than a predetermined threshold,then the model will be updated. Global Nearest Neighbor (GNN) algorithm is used as data association algorithm. We named our proposed method as Deformation Detection Particle Filter (DDPF) . DDPF
approach is compared with basic SIR-PF algorithm on real airshow videos. Comparisons results show that, the basic SIR-PF algorithm is not able to track the manoeuvring targets when the rotation or scaling is occurred in target' s model. However, DDPF approach updates target's model when the rotation or
scaling is occurred. Thus, the proposed approach is able to track the manoeuvring targets more efficiently
and accurately.
The purpose research is to develop the decision model of Multi-Criteria Group Decision Making (MCGDM) into Interval Value Fuzzy Multi-Criteria Group Decision Making (IV-FMCGDM), while the specific purpose is to construct decision-making model of Adaptive Interval Value Fuzzy Analytic Hierarchy Process (AIV- FAHP) uses Triangular Fuzzy Number (TFN) and group decision aggregation functions using Interval Value Geometric Means Aggregation (IV-GMA). The novelty research is to study the concept of group decision making by improving the middle point on the Interval Value Triangular Fuzzy Number (IV TFN). It provides more accurate modeling, and better rating performance, and more effective linguistic representation. This research produced a new decision-making model and algorithm based on AIV-FAHP used to measure the quality of e-learning.
A VHO Scheme for supporting Healthcare Services in 5G Vehicular Cloud Computi...University of Piraeus
Fifth Generation Vehicular Cloud Computing (5G-VCC) systems use heterogeneous network access technologies in order to fulfill the requirements of modern services, including medical services with strict constraints. Therefore, the need for efficient Vertical Handover (VHO) management schemes must be addressed. In this paper, a VHO management scheme for supporting medical services in 5G-VCC systems, is described. It consists of the VHO initiation and the network selection processes, while at the same time, the vehicle’s velocity, its current connection type, as well as the status of the onboard patient’s health, are considered. Specifically, during the VHO initiation process the necessity to perform handover is evaluated. Subsequently, the network selection process selects the appropriate network alternative considering both medical service requirements and patients’ health status. The proposed scheme is applied to a 5G-VCC system which includes Long Term Evolution (LTE) and Worldwide Interoperability Microwave Access (WiMAX) Macrocells and Femtocells, as well as Wireless Access for Vehicular Environment Road Side Units (WAVE RSUs). Performance evaluation shows that the proposed algorithm outperforms existing VHO management schemes.
A Vertical Handover Management Scheme for VANET Cloud Computing SystemsUniversity of Piraeus
Vehicular Cloud Computing (VCC) systems use heterogeneous network access technologies in order to fulfill the requirements of modern services. Therefore, the need for efficient Vertical Handover (VHO) management schemes must be addressed. In this paper a VHO management scheme for VCC systems is described. The proposed method takes into account the vehicles velocity as well as its current connection type and applies a two step VHO algorithm to reduce operations’ costs and optimize mobility management. Accordingly, as a first step a VHO initiation process evaluates the necessity to perform handover and subsequently a network selection process selects the appropriate network alternative considering both vehicular service requirements and operators’ policies. The proposed scheme is applied to a VCC system which includes Long Term Evolution (LTE) Macrocells and Femtocells as well as 802.11p Road Side Units (RSUs). Performance evaluation shows that the suggested algorithm ensures the Always Best Connection (ABC) principle, while at the same time outperforms existing VHO management schemes.
COMPARISON OF WAVELET NETWORK AND LOGISTIC REGRESSION IN PREDICTING ENTERPRIS...ijcsit
Enterprise financial distress or failure includes bankruptcy prediction, financial distress, corporate performance prediction and credit risk estimation. The aim of this paper is that using wavelet networks innon-linear combination prediction to solve ARMA (Auto-Regressive and Moving Average) model problem.ARMA model need estimate the value of all parameters in the model, it has a large amount of computation.Under this aim, the paper provides an extensive review of Wavelet networks and Logistic regression. Itdiscussed the Wavelet neural network structure, Wavelet network model training algorithm, Accuracy rateand error rate (accuracy of classification, Type I error, and Type II error). The main research opportunity exist a proposed of business failure prediction model (wavelet network model and logistic regression
model). The empirical research which is comparison of Wavelet Network and Logistic Regression on training and forecasting sample, the result shows that this wavelet network model is high accurate and the overall prediction accuracy, Type Ⅰerror and Type Ⅱ error, wavelet networks model is better thanlogistic regression model.
A downlink scheduler supporting real time services in LTE cellular networksUniversity of Piraeus
The wide spread of real-time services in wireless networks demands scheduling mechanisms supporting strict Quality of Service (QoS) requirements. Nevertheless, the specifications of the LTE standard for mobile connectivity defined by the 3rd Generation Partnership Project (3GPP) does not impose any specific scheduler for the proper allocation of resources to services. Therefore, several LTE schedulers have been proposed in the literature meeting the QoS requirements of modern services. In this paper a QoS aware scheduler for the LTE downlink is proposed namely the FLS-Advanced (FLSA) aiming at prioritizing real-time traffic. The proposed scheduler has been built on three distinct levels assigning the available radio resources to services according to their requirements. Based on simulation results, the FLSA outperforms in terms of packet loss ratio, attainable throughput and fairness the performance of existing schedulers including PF, MLWDF, EXP/PF, FLS, EXP RULE and LOG RULE.
Classification of Churn and non-Churn Customers in Telecommunication CompaniesCSCJournals
Telecommunication is very important as it serves various activities, services of electronic systems to transmit messages via physical cables, telephones, or cell phones. The two main factors that affect the growth of telecommunications are the rapid growth of modern technology and the market demand and its competition. These two factors in return, create new technologies and products, which open a series of options and offers to customers, in order to satisfy their needs and requirements. However, one crucial problem that commercial companies in general and telecommunication in particular, suffer from is a loss of valuable customers to competitors; this is called customer churn prediction. In this paper, the dynamic training technique is introduced. The dynamic training is used to improve the prediction of performance. This technique is based on two ANN network configurations to minimise the total error of the network to predict two different classes; names churn and non-customers.
IMPROVEMENT OF LTE DOWNLINK SYSTEM PERFORMANCES USING THE LAGRANGE POLYNOMIAL...IJCNCJournal
To achieve a high speed data rate, higher spectral efficiency, improved services and low latency the 3rd
generation partnership project designed LTE standard (Long Term Evolution).the LTE system employs
specific technical as well the technical HARQ, MIMO transmission, OFDM Access or estimation technical.
In this paper we focus our study on downlink LTE channel estimation and specially the interpolation which
is the basis of the estimation of the channel coefficients. Thus, we propose an adaptive method for polynomial interpolation based on Lagrange polynomial. We perform the Downlink LTE system MIMO transmission then compare the obtained results with linear, Sinus Cardinal and polynomial Newton Interpolations. The simulation results show that the Lagrange method outperforms system performance in term of Block Error Rate (BLER) , throughput and EVN(%)vs. Signal to Noise Ratio (SNR).
A Network Selection Algorithm for supporting Drone Services in 5G Network Arc...University of Piraeus
Flying Ad-hoc Networks (FANETs) use 5G network access technologies to fulfill the requirements of their services. In this environment, Drone to Infrastructure (D2I) communication is supported, while each drone could use both Disaster Management (DM) and non-Disaster Management (nDM) services. Efficient network selection algorithms are required to satisfy the constraints of the used services, since the presence of DM services affects the importance of nDM services in situations where a natural disaster occurs. This paper proposes a network selection algorithm which is called Dynamic Trapezoidal Fuzzy Topsis with Adaptive Criteria Weights (DTFT-ACW). DTFT-ACW accomplishes the ranking of the candidate networks considering the importance of each service, as well as the weights of the corresponding selection criteria, as they are obtained with respect to the severity level of a natural disaster occurred. Interval-Valued Trapezoidal Fuzzy Numbers (IVTFN) are used for the criteria evaluation. Experimental results show that the suggested method outperforms existing algorithms by satisfying the constraints of DM services when a disaster becomes severe. Furthermore, DTFT-ACW eliminates the computational complexity of the network selection by considering past decisions.
EFFICIENCY ENHANCEMENT BASED ON ALLOCATING BIZARRE PEAKSijwmn
A new work has been proposed in this paper in order to overcome one of the main drawbacks that found in
the Orthogonal Frequency Division Multiplex (OFDM) systems, namely Peak to Average Power Ratio
(PAPR). Furthermore, this work will be compared with a previously published work that uses the neural
network (NN) as a solution to remedy this deficiency.
The proposed work could be considered as a special averaging technique (SAT), which consists of wavelet
transformation in its first stage, a globally statistical adaptive detecting algorithm as a second stage; and
in the third stage it replaces the affected peaks by making use of moving average filter process. In the NN
work, the learning process makes use of a previously published work that is based on three linear coding
techniques.
In order to check the proposed work validity, a MATLAB simulation has been run and has two main
variables to compare with; namely BER and CCDF curves. This is true under the same bandwidth
occupancy and channel characteristics. Two types of tested data have been used; randomly generated data
and a practical data that have been extracted from a funded project entitled by ECEM. From the achieved
simulation results, the work that is based on SAT shows promising results in reducing the PAPR effect
reached up to 80% over the work in the literature and our previously published work. This means that this
work gives an extra reduction up to 15% of our previously published work. However, this achievement will
be under the cost of complexity. This penalty could be optimized by imposing the NN to the SAT work in
order to enhance the wireless systems performance. Orthogonal Frequency Division Multiplexing
EFFICIENCY ENHANCEMENT BASED ON ALLOCATING BIZARRE PEAKSijwmn
A new work has been proposed in this paper in order to overcome one of the main drawbacks that found in
the Orthogonal Frequency Division Multiplex (OFDM) systems, namely Peak to Average Power Ratio
(PAPR). Furthermore, this work will be compared with a previously published work that uses the neural
network (NN) as a solution to remedy this deficiency.
The proposed work could be considered as a special averaging technique (SAT), which consists of wavelet
transformation in its first stage, a globally statistical adaptive detecting algorithm as a second stage; and
in the third stage it replaces the affected peaks by making use of moving average filter process. In the NN
work, the learning process makes use of a previously published work that is based on three linear coding
techniques.
In order to check the proposed work validity, a MATLAB simulation has been run and has two main
variables to compare with; namely BER and CCDF curves. This is true under the same bandwidth
occupancy and channel characteristics. Two types of tested data have been used; randomly generated data
and a practical data that have been extracted from a funded project entitled by ECEM. From the achieved
simulation results, the work that is based on SAT shows promising results in reducing the PAPR effect
reached up to 80% over the work in the literature and our previously published work. This means that this
work gives an extra reduction up to 15% of our previously published work. However, this achievement will
be under the cost of complexity. This penalty could be optimized by imposing the NN to the SAT work in
order to enhance the wireless systems performance.
MODELLING TRAFFIC IN IMS NETWORK NODESijdpsjournal
IMS is well integrated with existing voice and data networks, while adopting many of their key characteristics.
The Call Session Control Functions (CSCFs) servers are the key part of the IMS structure. They are the main components responsible for processing and routing signalling messages.
When CSCFs servers (P-CSCF, I-CSCF, S-CSCF) are running on the same host, the SIP message can be internally passed between SIP servers using a single operating system mechanism like a queue. It increases
the reliability of the network [5], [6]. We have proposed in a last work for each type of service (between ICSCF and S-CSCF (call, data, multimedia.))[23], to use less than two servers well dimensioned and running on the same operating system.
Instead dimensioning servers, in order to increase performance, we try to model traffic on IMS nodes, particularly on entries nodes; it will provide results on separation of incoming flows, and then offer more satisfactory service.
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
In this paper, we investigated a queuing model of fuzzy environment-based a multiple channel queuing model (M/M/C) ( /FCFS) and study its performance under realistic conditions. It applies a nonagonal fuzzy number to analyse the relevant performance of a multiple channel queuing model (M/M/C) ( /FCFS). Based on the sub interval average ranking method for nonagonal fuzzy number, we convert fuzzy number to crisp one. Numerical results reveal that the efficiency of this method. Intuitively, the fuzzy environment adapts well to a multiple channel queuing models (M/M/C) ( /FCFS) are very well.
Peak detection using wavelet transformIJCNCJournal
A new work based-wavelet transform is designed to overcome one of the main drawbacks that found in the
present new technologies. Orthogonal Frequency Division Multiplexing (OFDM)is proposed in the
literature to enhance the multimedia resolution. However, the high peak power (PAPR) values will obstruct
such achievements. Therefore, a new proposition is found in this work, making use of the wavelet
transforms methods, and it is divided into three main stages; de-noising stage, thresholding stage and then
the replacement stage.
In order to check the system stages validity; a mathematical model has been built and its checked after
using a MATLAB simulation. A simulated bit error rate (BER) achievement will be compared with our
previously published work, where an enhancement from 8×10-1 to be 5×10-1 is achieved. Moreover, these
results will be compared to the work found in the literature, where we have accomplished around 27%
PAPR extra reduction.
As a result, the BER performance has been improved for the same bandwidth occupancy. Moreover and
due to the de-noise stage, the verification rate has been improved to reach 81%. This is in addition to the
noise immunity enhancement.
Performance analysis of papr reduction techniques in multicarrier modulation ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
MECC scheduling algorithm in vehicular environment for uplink transmission in...IJECEIAES
Single Carrier Frequency Division Multiple Access (SC-FDMA) is chosen because of the lower peak-to-average power ratio (PAPR) value in uplink transmission. However, the contiguity constraint is one of the major constraint presents in uplink packet scheduling, where all RBs allocated to a single UE must be contiguous in the frequency-domain within each time slot to maintain its single carrier. This paper proposed an uplink-scheduling algorithm namely the Maximum Expansion with Contiguity Constraints (MECC) algorithm, which supports both the RT and NRT services. The MECC algorithm is deployed in two stages. In the first stage, the RBs are allocated fairly among the UEs. The second stage allocates the RBs with the highest metric value and expands the allocation on both sides of the matrix, M with respect to the contiguity constraint. The performance of the MECC algorithm was observed in terms of throughput, fairness, delay, and Packet Loss Ratio (PLR) for VoIP, video and best effort flows. The MECC scheduling algorithm is compared to other algorithms namely the Round Robin (RR), Channel-Dependent First Maximum Expansion (CD-FME), and Proportional Fairness First Maximum Expansion (PF-FME). From here, it can be concluded that the MECC algorithm shows the best results among other algorithms by delivering the highest throughput which is up to 81.29% and 90.04% than CD-FME and RR scheduler for RT and NRT traffic respectively, having low PLR and delay which is up to 93.92% and 56.22% of improvement than CD-FME for the RT traffic flow. The MECC also has a satisfactory level of fairness for the cell-edge users in a vehicular environment of LTE network.
DSR Routing Decisions for Mobile Ad Hoc Networks using Fuzzy Inference Systemcscpconf
Mobile ad-hoc network technology has gained popularity in recent years by researchers on account of its flexibility, low cost and ease of deployment. The objective of this paper is to model the behavior of MANET for DSR protocol by considering some prominent routing metrics.These metrics ( packet delivery fraction, normalized routing load , average end- to- end delayetc.) have been generated by Network Simulator NS 2.34 tools and the node movement has beengenerated using Bonmotion 1.4.The MANET behavior for DSR protocol is hypothesized to be dependent on fuzzy variables like node density, pause time , number of packets transferred , and the number of connection. In this paper the behavior of MANET is modeled using Fuzzy Inference System for DSR (Dynamic Source Routing) protocol , Fuzzy Inference System offers a natural way of representing and reasoning the problems with uncertainty and imprecision. Fuzzy logic is found to be a suitable way in the mobile ad hoc network routing decision. A Fuzzy inference system is implemented on MATLAB 7.0 and the model is found to be satisfactory with the fuzzy input metrics and de fuzzified output metrics .
Performance analysis of papr reduction techniques in multicarrier modulation ...eSAT Journals
Abstract Orthogonal FrequencyDivisionMultiplexing (OFDM) is one of the many multicarrier modulation techniques which provide high spectral efficiency, less vulnerability to echoes,low implementation complexity and resilience to non – linear distortion. It is used in communication systems due to its various advantages. However, while this system is implemented problem of high peak – to – average power ratio(PAPR) is encountered. The reason behind this drawback is the existence of manyindependent subcarriers, due towhichthesignal amplitudecanhavehighpeakvalues as compared to average of whole system. The high PAPR in multicarrier transmission systems causes power degradation and spectrum spreading.Interleaving, Tone Reservation, Peak Reduction Carrier,Block Coding, Active Constellation Extension, Envelope ScalingareamongmanyPAPRreductionschemesthathavebeenproposedas a remedy to thisproblem. In this paper, performances of Amplitude Clipping and Filtering, Selected Level Mapping (SLM), and PartialTransmitSequence (PTS) techniques of PAPR reduction in OFDM systems by parameter variations are analyzed, based on Complementary Cumulative Distribution Function. An attempt has been made to simulate clipping and filtering technique with iterations and the simulation shows that PAPR problem is reduced as number of iterations increases. The attempts have also been made to simulate SLM technique and PTS technique by varying number of phase sequences, number of sub-blocks in SLM, PTS respectively and simulation results shows that by increasing the number of phase sequences, sub-blocks, PAPR can be reduced significantly.The mathematical equations are incorporated here to compute the maximum expected PAPR from an OFDM signal which shows when there is phase alignment of all sub carriers and sub carriers are equally modulated, then signal peak value hits the maximum. Besides these computer simulations, a comparative study of these three techniques is done.
Similar to A Network Selection Scheme with Adaptive Criteria Weights for 5G Vehicular Systems (20)
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...University of Piraeus
Virtual tourism is a novel trend that enhances the experience the users perceive from touristic places, such as archaeological sites. Drones are equipped with 360o video cameras and used for video capturing of the heritage sites. The video material is streamed to the users in real time, enriched with additional 3D, Augmented Reality (AR) or Mixed Reality (MR) material. Furthermore, the selection of the appropriate flying route for each drone should be performed, in order to provide a satisfactory tour experience to the user, considering his preferences about specific monuments. To address this issue, this paper describes a heritage route selection scheme for supporting real-time virtual tours in sites with cultural interest using drones. The proposed scheme applies a Fuzzy Multiple Attribute Decision Making (FMADM) algorithm, the Trapezoidal Fuzzy Topsis for Heritage Route Selection (TFT-HRS), to accomplish the ranking of the candidate heritage routes. The algorithm uses Interval-Valued Trapezoidal Fuzzy Numbers (IVTFN) for the representation of heritage routes evaluation values. Performance evaluation shows that the suggested method produces better results compared to the Fuzzy Topsis (FTOPSIS) by selecting the most appropriate flying route for the drone.
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...University of Piraeus
Virtual tourism is a novel trend that enhances the experience the users perceive from touristic places, such as archaeological sites. Drones are equipped with 360o video cameras and used for video capturing of the heritage sites. The video material is streamed to the users in real time, enriched with additional 3D, Augmented Reality (AR) or Mixed Reality (MR) material. Furthermore, the selection of the appropriate flying route for each drone should be performed, in order to provide a satisfactory tour experience to the user, considering his preferences about specific monuments. To address this issue, this paper describes a heritage route selection scheme for supporting real-time virtual tours in sites with cultural interest using drones. The proposed scheme applies a Fuzzy Multiple Attribute Decision Making (FMADM) algorithm, the Trapezoidal Fuzzy Topsis for Heritage Route Selection (TFT-HRS), to accomplish the ranking of the candidate heritage routes. The algorithm uses Interval-Valued Trapezoidal Fuzzy Numbers (IVTFN) for the representation of heritage routes evaluation values. Performance evaluation shows that the suggested method produces better results compared to the Fuzzy Topsis (FTOPSIS) by selecting the most appropriate flying route for the drone.
A Network Selection Algorithm for supporting Drone Services in 5G Network Arc...University of Piraeus
Flying Ad-hoc Networks (FANETs) use 5G network access technologies to fulfill the requirements of their services. In this environment, Drone to Infrastructure (D2I) communication is supported, while each drone could use both Disaster Management (DM) and non-Disaster Management (nDM) services. Efficient network selection algorithms are required to satisfy the constraints of the used services, since the presence of DM services affects the importance of nDM services in situations where a natural disaster occurs. This paper proposes a network selection algorithm which is called Dynamic Trapezoidal Fuzzy Topsis with Adaptive Criteria Weights (DTFT-ACW). DTFT-ACW accomplishes the ranking of the candidate networks considering the importance of each service, as well as the weights of the corresponding selection criteria, as they are obtained with respect to the severity level of a natural disaster occurred. Interval-Valued Trapezoidal Fuzzy Numbers (IVTFN) are used for the criteria evaluation. Experimental results show that the suggested method outperforms existing algorithms by satisfying the constraints of DM services when a disaster becomes severe. Furthermore, DTFT-ACW eliminates the computational complexity of the network selection by considering past decisions.
A Survey on Medium Access Control Schemes for 5G Vehicular Cloud Computing Sy...University of Piraeus
Fifth generation (5G) vehicular systems support multiple services with strict Quality of Service (QoS) constraints. To fulfill the increased communication needs, 5G Vehicular Cloud Computing (5G-VCC) architectures with dense deployments of the access network infrastructures have been proposed. In such systems, the network resources manipulation is a critical task that could be addressed by the Medium Access Control (MAC) layer. MAC schemes that have been proposed for vehicular networks, can be applied to 5G-VCC systems in order optimal manipulation of communication resources to be accomplished. This paper makes an overview of available MAC schemes, while a comprehensive discussion about their implementation in 5G-VCC systems is performed leading to useful conclusions.
A Survey on Medium Access Control Schemes for 5G Vehicular Cloud Computing Sy...University of Piraeus
Fifth generation (5G) vehicular systems support multiple services with strict Quality of Service (QoS) constraints. To fulfill the increased communication needs, 5G Vehicular Cloud Computing (5G-VCC) architectures with dense deployments of the access network infrastructures have been proposed. In such systems, the network resources manipulation is a critical task that could be addressed by the Medium Access Control (MAC) layer. MAC schemes that have been proposed for vehicular networks, can be applied to 5G-VCC systems in order optimal manipulation of communication resources to be accomplished. This paper makes an overview of available MAC schemes, while a comprehensive discussion about their implementation in 5G-VCC systems is performed leading to useful conclusions.
The enhancement of Underwater Cultural Heritage Assets using Augmented Realit...University of Piraeus
Τhe development in the fields of Underwater Cultural Heritage (UCH) management and Maritime Archaeology, yields an interdisciplinary and creative academic framework, such as the Information and Communication Technologies (ICT) sector that has been proved to build intelligent systems and applications. However, the ways to fully make use of these technologies are still being explored, as their potential have not been exploited yet. Underwater archaeological sites, semi (/or fully) submerged settlements, ancient ports and shipwrecks, unlike land sites, are not accessible to public due to their special (sub) marine environment and depth. In this paper, an innovative research idea of using Augmented Reality (AR) for maintaining the memory and the information of underwater archaeological sites, is presented. Although the “artificial” visual documentation cannot replace the authentic values of the underwater tangible heritage, the AR technology can contribute to the protection of the intangible properties and the conquered knowledge of the past of a place. This research work will focus, among other case studies, on the (semi) submerged fortifications and their contiguous contents of the acropolis of Halai in east Lokris, Greece. Hence, along with the climate change that may lead more antiquities covered by water during the following years, the advances in the communication field and the up-coming 5G and cloud technologies will make the idea fully applicable, contributing to the enhancement of the coastal and the underwater archaeological remains.
Fifth generation (5G) Vehicular Cloud Computing (VCC) systems use heterogeneous network access technologies to
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Performance Analysis and Optimization of Next Generation Wireless NetworksUniversity of Piraeus
The Fifth Generation (5G) networks, including the 5G Vehicular Cloud Computing (5G-VCC) systems, have evolved rapidly offering multiple services to users. The operating principles of vehicular networks, Cloud Computing (CC), Fog Computing (FC), Mobile Edge Computing (MEC) and Software Defined Networks (SDN) are applied to 5G infrastructures. In a 5G-VCC system, the vehicles are equipped with On-Board Units (OBUs) which communicate with each other as well as with Road Side Units (RSUs). Each RSU interacts with a Cloud infrastructure which offers vehicular services with strict Quality of Service (QoS) requirements, including Driver Assistance (DA), Passengers Entertainment and Information (PEnI) and Medical (MED) services. Dense deployments of 5G access networks are also implemented, called Ultra Dense Networks (UDNs), aiming to support high data rates produced by an increased number of vehicular users. In this environment, heterogeneous technologies are used to transfer the network services to vehicles. Optimal manipulation of the communication resources is required, while at the same time vehicular users should always obtain connectivity to the most appropriate network access technology, in order the constraints of the vehicular services to be satisfied. In this thesis, existing schemes for resource allocation as well as for mobility management are studied, while novel solutions are proposed for each topic.
Performance Analysis and Optimization of Next Generation Wireless Networks (P...University of Piraeus
The Fifth Generation (5G) networks, including the 5G Vehicular Cloud Computing (5G-VCC) systems, have evolved rapidly offering multiple services to users. The operating principles of vehicular networks, Cloud Computing (CC), Fog Computing (FC), Mobile Edge Computing (MEC) and Software Defined Networks (SDN) are applied to 5G infrastructures. In a 5G-VCC system, the vehicles are equipped with On-Board Units (OBUs) which communicate with each other as well as with Road Side Units (RSUs). Each RSU interacts with a Cloud infrastructure which offers vehicular services with strict Quality of Service (QoS) requirements, including Driver Assistance (DA), Passengers Entertainment and Information (PEnI) and Medical (MED) services. Dense deployments of 5G access networks are also implemented, called Ultra Dense Networks (UDNs), aiming to support high data rates produced by an increased number of vehicular users. In this environment, heterogeneous technologies are used to transfer the network services to vehicles. Optimal manipulation of the communication resources is required, while at the same time vehicular users should always obtain connectivity to the most appropriate network access technology, in order the constraints of the vehicular services to be satisfied. In this thesis, existing schemes for resource allocation as well as for mobility management are studied, while novel solutions are proposed for each topic.
Personalized Real-Time Virtual Tours in Places with Cultural InterestUniversity of Piraeus
Virtual tours using drones enhance the experience the users perceive from a place with cultural interest. Drones equipped with 360o cameras perform real-time video streaming of the cultural sites. The user preferences about each monument type should be considered in order the appropriate flying route for the drone to be selected. This paper describes a scheme for supporting personalized real-time virtual tours in sites with cultural interest using drones. The user preferences are modeled using the MPEG-21 and the MPEG-7 standards, while Web Ontology Language (OWL) ontologies are used for the description of the metadata structure and semantics. The Metadata-aware Analytic Network Process (MANP) algorithm is proposed in order the weights about the user preferences for each monument type to be estimated. Subsequently, the Trapezoidal Fuzzy Topsis for Heritage Route Selection (TFT-HRS) algorithm accomplishes ranks the candidate heritage routes. Finally, after each virtual tour, the user preferences metadata are updated in order the scheme to continuously learn about the user preferences.
The Convergence of Blockchain, Internet of Things (IoT) and Building Informat...University of Piraeus
The Architecture, Engineering and Construction (AEC) industry has not embraced digital transformation with the same enthusiasm as other industries (e.g. such as manufacture industry). Building Information Modeling (BIM) is a revolutionary technology that is characterized as the opportunity of the AEC industry to move to the digital era and improve the collaboration amongst the partners of this industry by exploiting Information and Communications Technologies (ICT). BIM provides all the necessary tools and automations to achieve end-to-end communication, data exchange and information sharing between project actors. Thus, the virtual 3D models generated in the context of engaging in the BIM process and as-delivered physical assets through Building Management Systems (BMS) could adopt Internet of Things (IoT) architectures and services. However, the orchestration of IoT in a highly modular environment with many moving parts and inter-dependencies between the stakeholders of this environment, lead to many security issues. Therefore, this paper proposes a system architecture that employs the Blockchain technology as a measure to secure and control the BIM technology coupled with IoT. The system architecture under scrutiny is considering the case of a museum building, where efficient security, management and monitoring are of great importance.
The convergence of blockchain, internet of things (io t) and building informa...University of Piraeus
The Architecture, Engineering and Construction (AEC) industry has not embraced digital transformation with the same enthusiasm as other industries (e.g. such as manufacture industry). Building Information Modeling (BIM) is a revolutionary technology that is characterized as the opportunity of the AEC industry to move to the digital era and improve the collaboration amongst the partners of this industry by exploiting Information and Communications Technologies (ICT). BIM provides all the necessary tools and automations to achieve end-to-end communication, data exchange and information sharing between project actors. Thus, the virtual 3D models generated in the context of engaging in the BIM process and as-delivered physical assets through Building Management Systems (BMS) could adopt Internet of Things (IoT) architectures and services. However, the orchestration of IoT in a highly modular environment with many moving parts and inter-dependencies between the stakeholders of this environment, lead to many security issues. Therefore, this paper proposes a system architecture that employs the Blockchain technology as a measure to secure and control the BIM technology coupled with IoT. The system architecture under scrutiny is considering the case of a museum building, where efficient security, management and monitoring are of great importance.
The revival of back-filled monuments through Augmented Reality (AR) (presenta...University of Piraeus
The development of three-dimensional (3D) models and the use of Augmented Reality (AR) in the field of cultural heritage consists an innovative process the recent years that provides the visitors of archaeological sites with additional information. This has been made possible due to achievements in digital technologies, communications, devices and developments in software engineering. Nevertheless, the research to fully make use of these new methods continues, as the potentials of new technologies have not been exploited. In archaeological sites, the production of 3D models for AR is focused on the virtual reconstruction of ruined monuments at their original form, aiming to give visitors the third dimension (height, volume etc.), especially to those who do not have special knowledge of archaeology. This paper describes an innovative approach of using AR for maintaining the memory and the information of monuments, as they have been originally excavated, but that are going to be back -filled due to the particularity of their material or their location. Also, the system architecture of the proposed scheme is described considering two study cases, a Neolithic settlement in the archaeological site of Halai, Lokris and the remains of a Classical Temple on open field of a hill in Thebes, Boeotia. Both mentioned monuments are under the direction of the American School of Classical Studies in Athens (ASCSA).
An analytic network process and trapezoidal interval-valued fuzzy technique f...University of Piraeus
Next generation wireless networks consist of many heterogeneous access technologies that should support various service types with different quality of service (QoS) constraints, as well as user, requirements and provider policies. Therefore, the need for network selection mechanisms that consider multiple factors must be addressed. In this paper, a network selection method is proposed by applying the analytic network process to estimate the weights of the selection criteria, as well as a fuzzy version of technique for order preference by similarity to ideal solution to perform the ranking of network alternatives. The method is applied to a heterogeneous network environment providing different QoS classes and policy characteristics. Each user applies the method to select the most appropriate network, which satisfies his or her requirements in respect of his or her service-level agreement (SLA). Performance evaluation shows that when the user requests only one service, the proposed method performs better compared to the original technique for order preference by similarity to ideal solution, as well as the Fuzzy AHP-ELECTRE method. Moreover, the proposed method can be applied in cases where a user requires multiple services simultaneously on a device. The sensitivity analysis of the proposed method shows that it can be properly adjusted to conform to network environment changes.
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This paper presents a web service which delivers personalized audio information. The personalization process is automated and decentralized. The metadata which support personalization are separated in two categories: the metadata describing user preferences stored at each user and the resource adaptation metadata stored at the web service host. The multimedia models MPEG-21 and MPEG-7 are used to describe metadata information and the Web Ontology Language (OWL) to produce and manipulate ontological descriptions. SPARQL is used for querying the OWL ontologies. The MPEG Query Format (MPQF) is also used, providing a wellknown framework for applying queries to the metadata and to the ontologies.
A Personalized Audio Server using MPEG-7 and MPEG-21 standards (presentation)University of Piraeus
This paper presents a semantic model which delivers personalized audio information. The personalization process is automated and decentralized. The metadata which support personalization are separated in two categories: the metadata describing user preferences stored at each user and the resource adaptation metadata stored at the server. The multimedia models MPEG-21 and MPEG-7 are used to describe metadata information. The Web Ontology Language (OWL) language is used to produce and manipulate the relative ontological descriptions.
A downlink scheduler supporting real time services in LTE cellular networks (...University of Piraeus
The wide spread of real-time services in wireless networks demands scheduling mechanisms supporting strict Quality of Service (QoS) requirements. Nevertheless, the specifications of the LTE standard for mobile connectivity defined by the 3rd Generation Partnership Project (3GPP) does not impose any specific scheduler for the proper allocation of resources to services. Therefore, several LTE schedulers have been proposed in the literature meeting the QoS requirements of modern services. In this paper a QoS aware scheduler for the LTE downlink is proposed namely the FLS-Advanced (FLSA) aiming at prioritizing real-time traffic. The proposed scheduler has been built on three distinct levels assigning the available radio resources to services according to their requirements. Based on simulation results, the FLSA outperforms in terms of packet loss ratio, attainable throughput and fairness the performance of existing schedulers including PF, MLWDF, EXP/PF, FLS, EXP RULE and LOG RULE.
QoS-aware scheduling in LTE-A networks with SDN control (presentation)University of Piraeus
The 3GPP Long Term Evolution Advanced (LTE-A) standard specifies a set of pioneer features such as relay nodes and carrier aggregation. At the same time, the Software Defined Networks (SDN) have become an emerging technology which provides centralized control and programmability to modern networks. In the current communication environment, cloud computing could combine the advantages of both technologies in order to create a novel cloud assisted Software Defined LTEA architecture with relay nodes. Moreover, due to the increased requirements of modern services, the optimal resource allocation is a necessity. In such a context, this paper describes a QoS aware cross carrier scheduler for downlink flows, aiming at the optimization of system resources allocation. The proposed scheduler is evaluated against the PF, MLWDF, EXP/PF, EXP RULE, LOG RULE, FLS and FLSA schedulers in a cloud assisted Software Defined LTE-A topology with relay nodes. Simulation results show that the proposed scheduler improves the real time services performance while at the same time maintains an acceptable performance for best effort flows.
The 3GPP Long Term Evolution Advanced (LTE-A) standard specifies a set of pioneer features such as relay nodes and carrier aggregation. At the same time, the Software Defined Networks (SDN) have become an emerging technology which provides centralized control and programmability to modern networks. In the current communication environment, cloud computing could combine the advantages of both technologies in order to create a novel cloud assisted Software Defined LTEA architecture with relay nodes. Moreover, due to the increased requirements of modern services, the optimal resource allocation is a necessity. In such a context, this paper describes a QoS aware cross carrier scheduler for downlink flows, aiming at the optimization of system resources allocation. The proposed scheduler is evaluated against the PF, MLWDF, EXP/PF, EXP RULE, LOG RULE, FLS and FLSA schedulers in a cloud assisted Software Defined LTE-A topology with relay nodes. Simulation results show that the proposed scheduler improves the real time services performance while at the same time maintains an acceptable performance for best effort flows.
A QoS aware scheduler, the FLS-Advanced (FLSA), a modified version of FLS, for the LTE downlink transmission is proposed.
The main idea is to prioritize the real-time type traffic against the other types.
FLSA has been built on three distinct levels which cooperate each other to allocate the network resources to users.
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A Network Selection Scheme with Adaptive Criteria Weights for 5G Vehicular Systems
1. A Network Selection Scheme with Adaptive
Criteria Weights for 5G Vehicular Systems
Emmanouil Skondras1, Angelos Michalas2, Nikolaos Tsolis1, Dimitrios D. Vergados1
1
Department of Informatics, University of Piraeus, Piraeus, Greece, Email: {skondras, tsolis, vergados}@unipi.gr
2
Department of Informatics Engineering, Technological Educational Institute of Western Macedonia,
Kastoria, Greece, Email: amichalas@kastoria.teiwm.gr
Abstract—Fifth Generation Vehicular Cloud Computing (5G-
VCC) systems use heterogeneous network access technologies to
fulfill the requirements of modern vehicular services. Efficient
network selection algorithms are required to satisfy the con-
straints of Driver Assistance (DA) services, Passengers Enter-
tainment and Information (PEnI) services and Medical (MED)
services that provided to vehicular users. The presence of MED
services affects the importance of other services in situations
where patients with immediate health status exist within the
vehicle. This paper proposes a network selection scheme which
considers the patient health status to adapt the importance of
each service. The scheme consists of two Fuzzy Multi Attribute
Decision Making (FMADM) algorithms: the Trapezoidal Fuzzy
Adaptive Analytic Network Process (TF-AANP) to calculate the
relative importance of each vehicular service and the selection
criteria, as well as the Trapezoidal Fuzzy Topsis with Adaptive
Criteria Weights (TFT-ACW) to accomplish the ranking of
the candidate networks. Both algorithms use Interval-Valued
Trapezoidal Fuzzy Numbers (IVTFN). Performance evaluation
shows that the suggested method outperforms existing algorithms
by satisfying the constraints of MED services when the patient
health status becomes immediate.
I. INTRODUCTION
In a typical 5G-VCC system, vehicles are equipped with
On-Board Units (OBUs) with computational, storage and
communication resources. Vehicles communicate with each
other, as well as with a Cloud infrastructure through the
available Access Networks. The Cloud infrastructure offers
vehicular services, including Driver Assistance (DA) services,
Passengers Entertainment and Information (PEnI) services, as
well as Medical (MED) services with strict Quality of Service
(QoS) requirements. Indicatively, DA services include Naviga-
tion Assistance (NAV) [1] and Parking Assistance (PRK) [2]
services. Accordingly, PEnI services include Conversational
Video (CV) [3], Voice over IP (VoIP) [4], Buffered Streaming
(BS) [5] and Web Browsing (WB) [6] services. Finally, MED
services include Live Healthcare Video (LHVideo) [7], Med-
ical Images (MedImages) [8], Health Monitoring (HMonitor-
ing) [9] and Clinical Data Transmission (CData) [10] services.
The presence of MED services raises questions about the
importance of other services in situations where there are
patients with immediate health status within the vehicle. Thus,
the importance of each service, along with the patient’s health
status must be considered during the network selection.
Several Fuzzy Multiple Attribute Decision Making
(FMADM) methods have been proposed for network
selection. FMADM methods utilize linguistic variables,
triangular fuzzy numbers, trapezoidal fuzzy numbers etc.
to model network attributes and their respective weights.
Such methods include the Fuzzy AHP - TOPSIS (FAT)
[11], the Fuzzy AHP - SAW (FAS) [11], the Fuzzy SAW
(FSAW) [12], the Fuzzy AHP MEW (FAM) [11] and the
Fuzzy AHP - ELECTRE (FAE) [13]. However, the existing
algorithms consider only the selection criteria weights for
each service, while they don’t take into consideration the
relative importance between the services. Thus, in such
cases, the services obtain equal importance with each other,
which occurs to inappropriate network selections where
MED services are provided to passengers with immediate
health status, along with DA or PEnI services. In such cases,
MED services must obtain higher importance than the other
services during the network selection process, in order the
most appropriate network to be selected for satisfying their
strict constraints. In this paper, an improved version of the
Trapezoidal Fuzzy Topsis (TFT) [14] method is proposed.
The scheme consists of two FMADM algorithms, namely the
Trapezoidal Fuzzy Adaptive Analytic Network Process (TF-
AANP) to calculate the relative importance of the vehicular
services and the selection criteria, as well as the Trapezoidal
Fuzzy Topsis with Adaptive Criteria Weights (TFT-ACW) to
accomplish the ranking of the candidate networks.
The remainder of the paper is as follows: Section II de-
scribes the proposed scheme, while Section III presents the
simulation setup and the evaluation results. Finally, section
IV concludes the discussed work.
II. THE PROPOSED NETWORK SELECTION SCHEME
The proposed method consists of two MADM algorithms:
the Trapezoidal Fuzzy Adaptive Analytic Network Process
(TF-AANP) to calculate the relative importance of the services
and of the selection criteria, as well as the Trapezoidal
Fuzzy Topsis with Adaptive Criteria Weights (TFT-ACW) to
978-1-5386-8161-9/18/$31.00 c 2018 IEEE
2. accomplish the ranking of the candidate networks. Interval-
Valued Trapezoidal Fuzzy Numbers (IVTFN) [15] are used for
the representation of both criteria values and their importance
weights.
An Interval-Valued Fuzzy Number (IVFN) introduced by
Sambuc [16] is defined as ˜a = [˜aL
, ˜aU
] consisting of
the lower ˜aL
and the upper ˜aU
fuzzy numbers. IVFNs
replace the crisp membership values by intervals in [0, 1].
They were proposed due to the fact that fuzzy informa-
tion can be better expressed by intervals than by sin-
gle values. In particular, the IVTFN, is the most gen-
eral form of fuzzy number and can be represented as:
˜a = [˜aL
, ˜aU
] = [(aL
1 , aL
2 , aL
3 , aL
4 , vL
), (aU
1 , aU
2 , aU
3 , aU
4 , vU
))]
where: 0 ≤ aL
1 ≤ aL
2 ≤ aL
3 ≤ aL
4 ≤ 1, 0 ≤ aU
1 ≤
aU
2 ≤ aU
3 ≤ aU
4 ≤ 1, 0 ≤ vL
≤ vU
≤ 1 and ˜aL
⊂ ˜aU
.
The operational rules of the interval-valued trapezoidal fuzzy
numbers are defined in [15].
TABLE I: The lingustic terms that used for criteria pairwise comparisons.
Linguistic term Interval-valued trapezoidal fuzzy number
Equally Important (EI) [(0.043, 0.062, 0.137, 0.156, 0.8), (0.025, 0.05, 0.15, 0.175, 1.0)]
More than Equally Important (MEI) [(0.143, 0.162, 0.237, 0.256, 0.8), (0.125, 0.15, 0.25, 0.275, 1.0)]
Moderately More Important (MMI) [(0.243, 0.262, 0.337, 0.356, 0.8), (0.225, 0.25, 0.35, 0.375, 1.0)]
More than Moderately More Important
(MMMI)
[(0.343, 0.362, 0.437, 0.456, 0.8), (0.325, 0.35, 0.45, 0.475, 1.0)]
Strongly More Important (SMI) [(0.443, 0.462, 0.537, 0.556, 0.8), (0.425, 0.45, 0.55, 0.575, 1.0)]
More than Strongly More Important
(MSMI)
[(0.543, 0.562, 0.637, 0.656, 0.8), (0.525, 0.55, 0.65, 0.675, 1.0)]
Very Strongly More Important (VSMI) [(0.643, 0.662, 0.737, 0.756, 0.8), (0.625, 0.65, 0.75, 0.775, 1.0)]
More than Very Strongly More Important
(MVSMI)
[(0.743, 0.762, 0.837, 0.856, 0.8), (0.725, 0.75, 0.85, 0.875, 1.0)]
Extremely More Important (EMI) [(0.843, 0.862, 0.937, 0.956, 0.8), (0.825, 0.85, 0.95, 0.975, 1.0)]
A. Trapezoidal Fuzzy Adaptive Analytic Network Process (TF-
AANP)
A decision problem that is analyzed with the TF-AANP can
be represented as a network of nodes. Each node represents
a component (or cluster) of the system while arcs denote
interactions between them. Interactions and feedbacks within
clusters are called inner dependencies, while interactions and
feedbacks between clusters are called outer dependencies. The
TF-AANP is composed of seven major steps:
a) Estimation of the importance of each service: The
fuzzy pairwise comparison matrix ˜P is derived for the services
using the linguistic terms presented in table I, which corre-
spond to the nine-point importance scale introduced in [17].
The standard form of the ˜P matrix is expressed as follows:
˜P =
1 . . . ˜p1j . . . ˜p1S
.
.
.
.
.
.
.
.
.
1/˜p1s . . . 1 . . . ˜psS
.
.
.
.
.
.
.
.
.
1/˜p1S . . . 1/˜pjS . . . 1
(1)
while S denotes the number of the services. Subsequently, the
geometric mean r ˜Ps
of each service (row) s in ˜P is estimated
according to formula 2, where ⊗ denotes the multiplication
operator of two fuzzy numbers as defined in [18].
r ˜Ps
= (˜ps1 ⊗ ˜ps2 ⊗ ... ⊗ ˜psS )
1
S (2)
Then, the priority vector ˜Ω ˜Ps
of services is constructed as
follows:
˜Ω ˜Ps
= [ ˜ω˜p1 ˜ω˜p2 ... ˜ω˜pS ] (3)
where each ˜ω˜ps = (ωU
˜p1, ωU
˜p2, ωU
˜p3, ωU
˜p4, vU
ps); (ωL
˜p1, ωL
˜p2, ωL
˜p3, ωL
˜p4, vL
ps)
is calculated using formula 4. The ⊕ indicates the addition
operator of two fuzzy numbers as defined in [18].
˜ω˜ps = r ˜Ps
/(r ˜P1
⊕ r ˜P2
⊕ ... ⊕ r ˜Ps
⊕ ... ⊕ r ˜PS
) (4)
b) Model Construction and Problem Structuring for each
service: During this step, for each s ∈ S service the problem
is analyzed and decomposed into a rational system, consisted
of a network of nodes.
c) Pairwise comparison matrices and priority vectors:
In this step, for each s ∈ S service, the fuzzy pairwise
comparison matrix ˜As is derived for each TF-AANP cluster
using the linguistic terms presented in table I. The standard
form of the ˜A matrix is expressed as follows:
˜As =
1 . . . ˜as1j . . . ˜as1n
.
.
.
.
.
.
.
.
.
1/˜as1i . . . 1 . . . ˜asin
.
.
.
.
.
.
.
.
.
1/˜a1sn . . . 1/˜asjn . . . 1
(5)
while n denotes the number of the cluster elements. Sub-
sequently, the geometric mean r ˜Asi
of each row i in ˜As is
estimated according to formula 6.
r ˜Asi
= (˜asi1 ⊗ ˜asi2 ⊗ ... ⊗ ˜asin)
1
n (6)
Then, the priority vector ˜Ωsi of cluster elements is constructed
as follows:
˜Ωsi = [ ˜ωs1 ˜ωs2 ... ˜ωsn ] (7)
where each ˜ωsi = (ωU
s1, ωU
s2, ωU
s3, ωU
s4, vU
si); (ωL
s1, ωL
s2, ωL
s3, ωL
s4, vL
si)
is calculated using formula 8. The ⊕ indicates the addition
operator of two fuzzy numbers as defined in [18].
˜ωsi = r ˜Asi
/(r ˜As1
⊕ r ˜As2
⊕ ... ⊕ r ˜Asi
⊕ ... ⊕ r ˜Asn
) (8)
d) Construction of the Supermatrices: In this step, a
fuzzy supermatrix ˜Ws of the TF-AANP model is constructed
for each service representing the inner and outer dependencies
of the TF-AANP network. It is a partitioned matrix, with
each matrix segment representing the relationship between two
clusters of the network. To construct the supermatrix, the local
priority vectors ˜Ωs are grouped and placed in the appropriate
positions in the supermatrix based on the flow of influence
from one cluster to another, or from a cluster to itself, as in
the loop. For example if we assume a TF-AANP network of
q clusters, Ck with k = [1, 2, , q] and each cluster has nq
3. elements, denoted as ek1, ek2, , eknk
, then the supermatrix is
expressed as:
˜Ws =
C1 ... Ck ... Cq
e11...e1n1
... ek1...eknk
... eq1...eqnq
e11
C1
.
.
. ˜Ws11 ... ˜Ws1j ... ˜Ws1q
e1n1
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
ek1
Ck
.
.
. ˜Wsk1 ... ˜Wskj ... ˜Wskq
eknk
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
eq1
Cq
.
.
. ˜Wsq1 ... ˜Wsqj ... ˜Wsqq
eqnq
(9)
e) Construction of the Weighted Supermatrices: During
this step, the supermatrix of each service is transformed to
a stochastic one,the Weighted Supermatrix ˜Ws using formula
10.
˜Ws,k,j = ˜Ws,k,j /q (10)
f) Calculation of the Limited Supermatrices: In this
step, initially the deffuzified Weighted Supermatrix Ws of
each service is estimated by applying the Weighted Average
method. According to this method formula 11 is used, where
the parameters vs and ds represent the height and the centroid
of each ˜Ws,k,j trapezoid respectively. Subsequently, each Ws
is raised to limiting powers until all the entries converge.
By this way the overall priorities are calculated, and thus
the cumulative influence of each element on every other
interacting element is obtained [19]. At this point, all the
columns of each produced Limit Supermatrix Ls, are the same
and their values show the importance of each element e of the
TF-AANP network for the corresponding service s.
Ws,k,j =
vU
s · dU
s + vL
s · dL
s
dU
s + dL
s
(11)
g) Estimation of the Criteria Weights: In this step, the
weight we for each element e of the TF-AANP network is
calculated using formula 12 where the importance ˜ω ˜P s of each
service s is considered.
we =
S
s=1
˜ω ˜P ,s
∗ Ls,e (12)
B. Trapezoidal Fuzzy Topsis with Adaptive Criteria Weights
(TFT-ACW)
The candidate networks are ranked using the TFT-ACW
algorithm, which improves the TFT [14] by using the adaptive
weights that estimated from the TF-AANP method. Thus, the
imprortance of the opinion of each service (decision maker)
is considered, since the opinions of some decision makers
could have higher importance from the ones of other decision
maker. In general, similar to TFT, the TFT-ACW method is
based on the concept that the best alternative should have the
shortest distance from the positive ideal solution and the longer
distance from the negative ideal solution. Also, it assumes that
the linguistic values of criteria attributes are represented by
interval-valued trapezoidal fuzzy numbers. More specifically,
suppose AL = {AL1, AL2, . . . , ALz} is the set of possible
alternatives, CR = {CR1, CR2, . . . , CRn} is the set of
criteria and w1, w2, . . . , wn are the importance weights of the
respective criteria obtained from the application of the TF-
AANP algorithm. The steps of the method are as follows:
a) Construction of the decision matrix: Each ˜gie element
of the z×n decision matrix ˜D is an IVTFN number expressing
the performance of alternative i for criterion e. Thus
˜D =
CR1 ... CRn
AL1 ˜g11 ... ˜g1n
.
.
.
.
.
.
.
.
.
.
.
.
ALz ˜gz1 ... ˜gzn
(13)
where ˜gie = (gL
ie1, gL
ie2, gL
ie3, gL
ie4, vL
ie), (gU
ie1, gU
ie2, gU
ie3, gU
ie4, vU
ie) .
In the case that there are S services (decision makers)
the decision matrix include the average of the performance
values. Hence, assuming that for the sth
decision maker ˜giex
is the performance of alternative i for criterion (element) e,
the average of the performance values is given by formula 14.
˜gie =
S
s=1
(˜gies · ˜ω˜ps) (14)
b) Normalization of the decision matrix: Consider that
Γb is the set of benefits attributes and Γc is the set of
costs attributes. Then, the elements of the normalized decision
matrix are calculated using either formula 15 or 16, where
be = maxi gU
ie4 for each e ∈ Γb and ce = mini gL
ie4 for each
e ∈ Γc.
˜gie =
gL
ie1
be
,
gL
ie2
be
,
gL
ie3
be
,
gL
ie4
be
, v
L
ie
,
gU
ie1
be
,
gU
ie2
be
,
gU
ie3
be
,
gU
ie4
be
, v
U
ie
(15)
˜gie =
ce
gL
ie4
,
ce
gL
ie3
,
ce
gL
ie2
,
ce
gL
ie1
, v
L
ie
,
ce
gU
ie4
,
ce
gU
ie3
,
ce
gU
ie2
,
ce
gU
ie1
, v
U
ie
(16)
c) Construction of the weighted normalized decision ma-
trix: The weighted normalized decision matrix is constructed
by multiplying each element of the normalized decision matrix
˜gie with the respective weight we according to the formula 17.
˜uie = g
L
ie1 · we, g
L
ie2 · we, g
L
ie3 · we, g
L
ie4 · we, v
L
ie ,
g
U
ie1 · we, g
U
ie2 · we, g
U
ie3 · we, g
U
ie4 · we, v
U
ie
(17)
d) Determination of the positive and negative ideal so-
lution: The positive ideal solution is defined in 18, where
i
≡ maxi in case e ∈ Γb and
i
≡ mini in case e ∈ Γc.
Correspondingly, the negative ideal solution is defined in 19,
where i ≡ mini in case e ∈ Γb and i ≡ maxi in case
e ∈ Γc.
˜G
+
= g
+L
ie1
, g
+L
ie2
, g
+L
ie3
, g
+L
ie4
, v
+L
ie
, g
+U
ie1
, g
+U
ie2
, g
+U
ie3
, g
+U
ie4
, v
+U
ie
=
i
u
L
ie1,
i
u
L
ie2,
i
u
L
ie3,
i
u
L
ie4, v
L
ie ,
i
u
U
ie1,
i
u
U
ie2,
i
u
U
ie3,
i
u
U
ie4, v
U
ie
(18)
˜G
−
= g
−L
ie1
, g
−L
ie2
, g
−L
ie3
, g
−L
ie4
, v
−L
ie
, g
−U
ie1
, g
−U
ie2
, g
−U
ie3
, g
−U
ie4
, v
−U
ie
=
i
u
L
ie1,
i
u
L
ie2,
i
u
L
ie3,
i
u
L
ie4, v
L
ie ,
i
u
U
ie1,
i
u
U
ie2,
i
u
U
ie3,
i
u
U
ie4, v
U
ie
(19)
4. e) Measurement of the distance of each alternative from
the ideal solutions: The distances of each alternative from the
positive ideal solution are evaluated using formulas 20 and 21.
Likewise the distances of each alternative from the negative
ideal solution are estimated using formulas 22 and 23.
p
+
i1
=
n
e=1
1
4
u
L
ie1 − g
+L
ie1
2
+
u
L
ie2 − g
+L
ie2
2
+ u
L
ie3 − g
+L
ie3
2
+ u
L
ie4 − g
+L
ie4
2
1
2
(20)
p
+
i2
=
n
e=1
1
4
u
U
ie1 − g
+U
ie1
2
+
u
U
ie2 − g
+U
ie2
2
+ u
U
ie3 − g
+U
ie3
2
+ u
U
ie4 − g
+U
ie4
2
1
2
(21)
p
−
i1
=
n
e=1
1
4
u
L
ie1 − g
−L
ie1
2
+
u
L
ie2 − g
−L
ie2
2
+ u
L
ie3 − g
−L
ie3
2
+ u
L
ie4 − g
−L
ie4
2
1
2
(22)
p
−
i2
=
n
e=1
1
4
u
U
ie1 − g
−U
ie1
2
+
u
U
ie2 − g
−U
ie2
2
+ u
U
ie3 − g
−U
ie3
2
+ u
U
ie4 − g
−U
ie4
2
1
2
(23)
Consequently, the alternatives distance from the positive and
negative ideal solutions are expressed by intervals such as
[p+
i1, p+
i2] and [p−
i1, p−
i2], instead of single values, while in this
way less information is lost.
f) Calculation of the relative closeness: The relative
closeness of the distances from the ideal solutions are calcu-
lated using formula 24 and 25. Subsequently, the compound
relative closeness is obtained using formula 26.
RCi1 =
p
−
i1
p
+
i1
+ p
−
i1
(24)
RCi2 =
p
−
i2
p
+
i2
+ p
−
i2
(25)
RCi =
RCi1 + RCi2
2
(26)
g) Alternatives ranking: The alternative networks are
ranked according to their RCi values, while the best alternative
is that with the higher RCi value.
III. SIMULATION SETUP AND RESULTS
In our experiments, the 5G-VCC topology presented in
figure 1 is simulated. A mobility trace indicating the map
of the Syntagma square in Athens along with road traffic
data has been created using the Open Street Map (OSM)
software [20]. Then, the mobility trace has been used as input
in the Simulator of Urban Mobility (SUMO) simulator [21]
allowing the production of a realistic mobility pattern for the
simulated vehicles. Furthermore, the network topology is being
built upon the map, using the Network Simulator 3 (NS3)
simulator [22]. It includes a heterogeneous access network
environment and a Cloud infrastructure. The access network
environment includes 1 LTE Macrocell, 4 LTE Femtocells,
1 WiMAX Macrocell and 4 WAVE RSUs. Additionally, the
Cloud infrastructure includes a set of Virtual Machines (VMs)
providing Driver Assistance (DA), Passengers Entertainment
and Information (PeNI) and Medical (MED) services. DA
services include Navigation Assistance (NAV) and Parking
Assistance (PRK) services. Accordingly, PEnI services include
Conversational Video (CV), Voice over IP (VoIP), Buffered
Streaming (BS) and Web Browsing (WB) services. Finally,
MED services include Live Healthcare Video (LHVideo) [7],
Medical Images (MedImages) [8], Health Monitoring (HMon-
itoring) [9] and Clinical Data Transmission (CData) [10]
services. Furthermore, a Software Defined Network (SDN)
controller provides centralized control of the entire system.
TABLE II: Linguistic terms and the corresponding interval-valued
trapezoidal fuzzy numbers used for the criteria attributes.
Linguistic term Interval-valued trapezoidal fuzzy number
Absolutely Poor (AP) [(0.0, 0.0, 0.0, 0.0, 0.9), (0.0, 0.0, 0.0, 0.0, 1.0)]
Very Poor (VP) [(0.01, 0.02, 0.03, 0.07, 0.9), (0.0, 0.01, 0.05, 0.08, 1.0)]
Poor (P) [(0.04, 0.1, 0.18, 0.23, 0.9), (0.02, 0.08, 0.2, 0.25, 1.0)]
Medium Poor (MP) [(0.17, 0.22, 0.36, 0.42, 0.9), (0.14, 0.18, 0.38, 0.45, 1.0)]
Medium (M) [(0.32, 0.41, 0.58, 0.65, 0.9), (0.28, 0.38, 0.6, 0.7, 1.0)]
Medium Good (MG) [(0.58, 0.63, 0.8, 0.86, 0.9), (0.5, 0.6, 0.9, 0.92, 1.0)]
Good (G) [(0.72, 0.78, 0.92, 0.97, 0.9), (0.7, 0.75, 0.95, 0.98, 1.0)]
Very Good (VG) [(0.93, 0.98, 1.0, 1.0, 0.9), (0.9, 0.95, 1.0, 1.0, 1.0)]
Absolutely Good (AG) [(1.0, 1.0, 1.0, 1.0, 0.9), (1.0, 1.0, 1.0, 1.0, 1.0)]
Vehicle 8Vehicle 8
Vehicle 7Vehicle 7
Vehicle 6Vehicle 6
Vehicle 5Vehicle 5
Vehicle 4Vehicle 4
Vehicle 3Vehicle 3
Vehicle 1Vehicle 1
Vehicle 10Vehicle 10
Vehicle 9Vehicle 9
LTE MacroLTE Macro
WAVE RSU2
WAVE RSU3
WAVE RSU4
WAVE RSU1
LTE
Femto1
LTE
Femto3
LTE
Femto2
LTE
Femto2
LTE
Femto4
WiMAX
Macro
WiMAX
Macro
Cloud
VM
Services
VM
Services VM
Services
VM
ServicesVM
Services
VM
Services
...
...
...
SDN
controller
SDN
controller
Vehicle 2Vehicle 2
Heterogeneous Access Network Environment
Fig. 1: The simulated topology.
Three Service Level Agreements (SLAs) are defined. Each
SLA determines the available networks for each service type.
SLA1 supports all the available networks while SLA3 supports
the fewer networks.
Table II presents the lingustic terms and the corresponding
interval-valued trapezoidal fuzzy numbers used for the criteria
attributes of the available networks, while table III presents
the corresponding specifications per service and SLA of each
network, in terms of throughput, delay, jitter, packet loss
ratio, price, security and service reliability. Service reliability
5. TABLE III: The available networks.
Service
SLA
1
SLA
2
SLA
3
Network
Through
-put
Delay Jitter
Packet
Loss
Service
Reliability
Security Price
NavigationAssistance
(NAV)
LTE Macro G MG VG AG VG AG VG
LTE Femto 1 VG AG VG VG AG MG P
LTE Femto 2 AG G AG G VG G G
LTE Femto 3 G MG G MG G AG P
LTE Femto 4 AG AG MG AG G G AP
WiMAX Macro G AG G VG AG VG VP
WAVE 1 VG MG VG AG VG AG G
WAVE 2 MG MG VG VG G G AP
WAVE 3 MG MG G VG MG MG M
WAVE 4 M M MG VG MG MG MP
ParkingAssistance
(PRK)
LTE Macro MG M G VG VG AG MP
LTE Femto 1 AG AG AG AG AG VG G
LTE Femto 2 VG AG M VG AG G AG
LTE Femto 3 G VG MG AG VG AG MG
LTE Femto 4 MG G M G VG G G
WiMAX Macro G M M AG MG M MP
WAVE 1 M MP MG VG G G VG
WAVE 2 MG M M AG M M M
WAVE 3 AG G G AG MG MG P
WAVE 4 G M AG AG MG G G
ConversationVideo
(CV)
LTE Macro AG AG AG VG VG AG G
LTE Femto 1 MP MG VG AG AG VG AP
LTE Femto 2 G G MG VG AG MG M
LTE Femto 3 AG VG AG G VG G P
LTE Femto 4 G VG VG AG MG AG MG
WiMAX Macro MP M MG G G G MP
WAVE 1 G G VG VG G G M
WAVE 2 MG MG AG VG G MG AG
WAVE 3 MG MG G AG MG VG MP
WAVE 4 MP MP MG AG MG G P
VoiceoverIP
(VoIP)
LTE Macro VG VG AG AG VG AG AP
LTE Femto 1 M G VG VG AG VG G
LTE Femto 2 G VG MG AG VG G MG
LTE Femto 3 MG G G VG G MG MP
LTE Femto 4 VG AG VG AG VG VG P
WiMAX Macro M G MG MG G G M
WAVE 1 M MG AG AG G G VG
WAVE 2 MG M VG AG MG M M
WAVE 3 VG AG VG AG MG VG G
WAVE 4 G VG G AG MG G AG
BufferedStreaming
(BS)
LTE Macro G MG VG AG VG AG VG
LTE Femto 1 VG AG AG VG AG VG P
LTE Femto 2 AG VG VG MG MG AG G
LTE Femto 3 G MG VG G VG G M
LTE Femto 4 AG AG AG VG G G P
WiMAX Macro G AG G VG AG VG VP
WAVE 1 VG MG VG AG VG AG G
WAVE 2 MG MG VG VG G G AP
WAVE 3 MG MG G VG MG MG M
WAVE 4 M M MG VG MG MG MP
WebBrowsing
(WB)
LTE Macro MG M G VG VG AG MP
LTE Femto 1 AG AG AG AG AG VG G
LTE Femto 2 G G M G G VG G
LTE Femto 3 AG AG MG AG VG MG M
LTE Femto 4 VG G G VG MG G MG
WiMAX Macro G VG MG G M VG M
WAVE 1 M MP MG VG G G VG
WAVE 2 MG M M AG M M M
WAVE 3 AG G G AG MG MG AP
WAVE 4 G M AG AG MG G G
LiveHealthcareVideo
(LHVideo)
LTE Macro MG MG G VG MG VG MP
LTE Femto 1 MP MG VG AG AG VG AP
LTE Femto 2 G VG AG AG VG G G
LTE Femto 3 VG AG G AG G MG M
LTE Femto 4 MG G VG G AG AG G
WiMAX Macro MP M MG G G G MP
WAVE 1 G G VG VG G G M
WAVE 2 MG MG AG VG G MG AG
WAVE 3 AG AG AG AG VG AG G
WAVE 4 MP MP MG AG MG G P
MedicalImages
(MedImages)
LTE Macro M MG AG AG G AG VG
LTE Femto 1 M G VG VG AG VG G
LTE Femto 2 AG AG VG AG VG AG P
LTE Femto 3 VG MG G MG G MG MP
LTE Femto 4 G G VG G AG G MP
WiMAX Macro M G MG VG G G M
WAVE 1 VG VG AG AG VG AG AP
WAVE 2 MG M VG AG MG M M
WAVE 3 VG AG VG AG MG VG G
WAVE 4 G VG G AG MG G MP
HealthMonitoring
(HMonitoring)
LTE Macro G MG VG AG VG AG VG
LTE Femto 1 VG AG AG VG AG VG P
LTE Femto 2 AG G G G MG G VG
LTE Femto 3 VG AG MG AG MG VG G
LTE Femto 4 G VG VG G G G VG
WiMAX Macro G AG G VG AG VG VP
WAVE 1 VG MG VG AG VG AG G
WAVE 2 MG MG VG VG G G AP
WAVE 3 MG MG G VG MG MG M
WAVE 4 M M MG VG MG MG MP
ClinicalDataTransmission
(CData)
LTE Macro MG M G VG VG AG MP
LTE Femto 1 AG AG AG AG AG VG P
LTE Femto 2 AG VG MG VG VG G M
LTE Femto 3 G AG M G G MG M
LTE Femto 4 VG G G AG VG AG G
WiMAX Macro G MG VG G VG MG AG
WAVE 1 M MP MG VG G G AG
WAVE 2 MG M M AG M M M
WAVE 3 AG G G AG MG MG P
WAVE 4 G M AG AG MG G G
TABLE IV: The simulated vehicles.
Vehicle SLA Vehicular Services Patient Health Status
1 1 PRK, CV, BS, WB, LHVideo Immediate
2 1 WB, MedImages, HMonitoring Non-Urgent
3 1 NAV, VoIP, HMonitoring Standard
4 1 NAV, WB, CData Urgent
5 2 CV, LHVideo, MedImages Non-Urgent
6 2 CV, WB, MedImages Immediate
7 2 WB, HMonitoring Very urgent
8 3 WB, MedImages, CData Standard
9 3 NAV, HMonitoring, CData Urgent
10 3 WB, MedImages, HMonitoring Immediate
determines the ability for service constraints satisfaction and
optimization of performance when a network is congested.
We consider the case where 10 vehicles with patients are
moving inside the network environment and need to be con-
nected to a network which satisfies the requirements of their
services and at the same time comply with their patient health
status, as well as with their respective SLA agreements. The
health status of each patient is evaluated using the Manchester
Triage System (MTS) [23] healthcare classification system,
which defines 5 health statuses, called Non-Urgent, Standard,
Urgent, Very-Urgent and Immediate. The Non-Urgent status
has the lower risk about patient’s life, while the Immediate
status has the higher one.
During the network selection process initially the relative
importance ˜ω˜ps of each service is considered with respect to
the patient health status. Figure 2 presents the importance of
each service per patient health status, as it is obtained using
the TF-AANP method. As can be observed, the importance
of MED services depends on the patient health status. In-
dicatively, when the patient health status becomes immediate,
the MED services obtain higher importance than the DA and
the PEnI services. Accordingly, when the patient health status
becomes Non-Urgent, the relative importance of the services
is quite similar. Subsequently, the TF-AANP estimates the
decision weights we per service type and patient health status,
considering the ANP network model proposed in [14]. The cri-
teria weights per SLA for DA and PEnI services are presented
in figures 3 and 4, respectively. Also, for each possible health
status, the criteria weights per healthcare service for the MED
services are presented in figure 5. As illustrated the weights
are proportional to the constraints of each service as well as
to the health status of each patient. In particular, the weight of
the price criterion is low for Immediate health status, resulting
in a weight value which is very close to 0. Accordingly, when
the health status is evaluated as Non-Urgent, the medical risk
for the patient is very low and the price criterion becomes
more important.
Considering the relative importance ˜ω˜ps of each service
and the criteria weights we for DA, PEnI and MED services,
the final criteria weights are estimated for each vehicle with
respect to the health status of onboard patients, as well as to
the SLA of each vehicle (figure 6).
Ranking of the networks alternatives is performed from
the TFT-ACW algorithm using the afforementioned criteria
weights for each vehicle.
Subsequently, the experimental results of the TFT-ACW
method are compared with the ones obtained from the TFT
6. TABLE V: Networks’ classification in respect of TFT-ACW, TFT and FSAW results.
Vehicle 1 Vehicle 2 Vehicle 3 Vehicle 4 Vehicle 5 Vehicle 6 Vehicle 7 Vehicle 8 Vehicle 9 Vehicle 10
``````Networks
Method
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
TFT-ACW
TFT
FSAW
LTE Macro 4 3 3 2 2 2 1 1 1 2 2 1 2 2 1 2 1 1 1 2 2 1 1 2 2 3 4 3 2 3
LTE Femto 1 3 2 1 1 1 1 - - - - - - - - - - - - - - - - - - 3 1 1 2 1 1
LTE Femto 2 2 1 2 3 4 3 - - - - - - - - - - - - - - - - - - - - - - - -
LTE Femto 3 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
LTE Femto 4 - - - - - - - - - 1 4 5 - - - - - - - - - - - - - - - - - -
WiMAX Macro 7 7 8 6 7 7 3 3 2 4 5 3 4 4 4 4 4 4 3 3 3 3 3 3 4 2 3 4 5 5
WAVE 1 5 4 4 4 3 4 2 2 3 3 1 2 3 3 3 1 3 3 2 1 1 2 2 1 1 4 2 1 3 2
WAVE 2 6 6 7 8 8 8 5 5 5 6 7 7 - - - - - - - - - - - - - - - - - -
WAVE 3 1 5 5 5 5 6 4 4 4 7 6 6 1 1 2 3 2 2 4 4 4 4 4 4 5 5 5 5 4 4
WAVE 4 8 8 6 7 6 5 6 6 6 5 3 4 - - - - - - - - - - - - - - - - - -
Fig. 2: The importance of each service per patient health status.
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
SLA 1 SLA 2 SLA 3 SLA 1 SLA 2 SLA 3
Navigation Assistance Parking Assistance
TF-AANPweight
Criteria Weights for Driver Assistance services per SLA
Throughput Delay Jitter Packet loss Service Reliability Security Price
Fig. 3: The TF-AANP criteria weights for DA services per SLA.
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
SLA 1 SLA 1 SLA 2 SLA 1 SLA 2 SLA 1 SLA 2 SLA 3
VoIP Conversational Video Buffered Streaming Web
TF-AANPweight
Criteria Weights for Passengers Entertainment and Information services per SLA
Throughput Delay Jitter Packet loss Service Reliability Security Price
Fig. 4: The TF-AANP criteria weights for PeNI services per SLA.
[14] and the FSAW [12] algorithms (Table V). When the
patient health status is Non-Urgent (vehicles 2 and 5) or
Standard (vehicles 3 and 8) the results of the TFT-ACW and
the TFT are similar, due to the similar relative importance
considered from the TFT-ACW for each service. However,
when the patient health status gets worse, the TFT-ACW
assigns higher importance to MED services and selects the
most appropriate network to satisfy their strict constraints.
Indicatively, in the case of vehicle 1, the TFT-ACW selects the
WAVE 3 network, which provides VG for service reliability,
as well as AG for throughput, delay, jitter, packet loss and
security, for the LHVideo medical service. On the contrary, the
results of both TFT and FSAW are negatively affected from
the existence of non medical services in the vehicle 1 ignoring
Fig. 5: The TF-AANP criteria weights for MED services per SLA and
patient health status.
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
Vehicle 1 Vehicle 2 Vehicle 3 Vehicle 4 Vehicle 5 Vehicle 6 Vehicle 7 Vehicle 8 Vehicle 9 Vehicle 10
TF-AANPweight
The TF-AANP weights for each vehicle
Throughput Delay Jitter Packet loss Service Reliability Security Price
Fig. 6: The TF-AANP weights for each vehicle.
the immediate health status of the patient. Specifically, the
TFT selects the LTE Femto 2 network, which provides worse
specifications for the LHVideo service (e.g. G for throughput
and VG for delay), while the FSAW selects the LTE Femto
1 network, which also provides worse specifications for the
aforementioned medical service (e.g. MP for throughput and
MG for delay).
7. IV. CONCLUSION
This paper proposes a network selection scheme for sup-
porting modern vehicular services in 5G-VCC systems. The
discussed scheme consists of two FMADM algorithms, namely
the TF-AANP to calculate the relative importance of each
service, as well as the weights of the selection criteria and
the TFT-ACW to accomplish the ranking of the candidate
networks. The health status of onboard patients and the SLA
of each vehicle are considered, while the criteria used for
network evaluation include throughput, delay, jitter, packet
loss, service reliability, security and price. Performance eval-
uation showed that the proposed scheme outperforms existing
network selection methods by satisfying the strict constraints
of medical services, when the patient’s health status becomes
immediate and multiple types of non medical services coexist
with medical services to the vehicle.
ACKNOWLEDGEMENTS
The publication of this paper has been partly supported by
the University of Piraeus Research Center (UPRC).
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