The document proposes a vertical handover management scheme for vehicular cloud computing systems that considers vehicle velocity and current network connection. It involves a two-step process: 1) a vertical handover initiation process evaluates the need for handover; and 2) if needed, a network selection process selects the best alternative network based on service requirements and operator policies. Performance evaluation shows the scheme ensures the best connection for vehicles while outperforming other handover management methods.
Newton-raphson method to solve systems of non-linear equations in VANET perfo...journalBEEI
Nowadays, Vehicular Ad-Hoc Network (VANET) has got more attention from the researchers. The researchers have studied numerous topics of VANET, such as the routing protocols of VANET and the MAC protocols of VANET. The aim of their works is to improve the network performance of VANET, either in terms of energy consumption or packet delivery ratio (PDR) and delay. For this research paper, the main goal is to find the coefficient of a, b and c of three non-linear equations by using a Newton- Raphson method. Those three non-linear equations are derived from a different value of Medium Access Control (MAC) protocol's parameters. After that, those three coefficient is then will be used in optimization of the VANET in terms of energy, PDR, and delay.
Channel Aware Mac Protocol for Maximizing Throughput and FairnessIJORCS
The proper channel utilization and the queue length aware routing protocol is a challenging task in MANET. To overcome this drawback we are extending the previous work by improving the MAC protocol to maximize the Throughput and Fairness. In this work we are estimating the channel condition and Contention for a channel aware packet scheduling and the queue length is also calculated for the routing protocol which is aware of the queue length. The channel is scheduled based on the channel condition and the routing is carried out by considering the queue length. This queue length will provide a measurement of traffic load at the mobile node itself. Depending upon this load the node with the lesser load will be selected for the routing; this will effectively balance the load and improve the throughput of the ad hoc network.
PERFORMANCE OF OLSR MANET ADOPTING CROSS-LAYER APPROACH UNDER CBR AND VBR TRA...IJCNCJournal
The routing protocols play an important role in Mobile Ad-Hoc Network (MANET) because of the dynamically change of its topology. Optimized Link State Routing (OLSR), unawareness of Quality of Service (QoS) and power-consumed protocol, is an example of a widely-used routing protocol in MANET.
The Multi-Point Relays (MPR) selection algorithm is very crucial in OLSR. Therefore, firstly, we propose a heuristic method to select the best path based on two parameters; Bit Error Rate (BER) derived from the physical layer and Weighted Connectivity Index (CI) adopted from the network layer. This can be done via the cross-layer design scheme. This is anticipated to enhance the performance of OLSR, provide QoS
guarantee and improve the power consumption. The performances of the proposed scheme are investigated
by simulation of two types of traffics: CBR and VBR (MPEG-4), evaluated by metrics namely Throughput, Packet Delivery Ratio (PDR), Average End-to-End Delay, Control Overhead and Average Total Power Consumption.We compare our results with the typical OLSR and OLSR using only Weighted CI. It is
obvious that our proposed scheme provides superior performances to the typical OLSR and OLSR using only Weighted CI, especially, at high traffic load.
Performance evaluation of high mobility OFDM channel estimation techniques IJECEIAES
In wireless communication, Orthogonal Frequency Division Multiplexing (OFDM) has been adopted due to its robustness to multipath fading and high data rate transmissions. At the other hand, the performance of OFDM systems severely degraded due to multi-path fading and Doppler frequency shifts in mobile systems, which causes inter-carrier-interference (ICI). Thus, Estimation of channel parameters is required at the receiver using a pre designed estimator where pilot tones are inserted in each OFDM symbol. In this paper, a random pilot data are generated and inserted in each OFDM symbol at equally spaced locations. The performance test of Least Square (LS) and Linear Minimum Mean Square (LMMSE) estimation methods are proposed with Discrete Fourier Transform (DFT) based on both LS and LMMSE, where different ITU channel models are considered in order to compare their performance for data transmission in high mobile systems with different Doppler frequencies exceeds 200 Hz and minimal number of pilots.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel Multi-
Radios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
Newton-raphson method to solve systems of non-linear equations in VANET perfo...journalBEEI
Nowadays, Vehicular Ad-Hoc Network (VANET) has got more attention from the researchers. The researchers have studied numerous topics of VANET, such as the routing protocols of VANET and the MAC protocols of VANET. The aim of their works is to improve the network performance of VANET, either in terms of energy consumption or packet delivery ratio (PDR) and delay. For this research paper, the main goal is to find the coefficient of a, b and c of three non-linear equations by using a Newton- Raphson method. Those three non-linear equations are derived from a different value of Medium Access Control (MAC) protocol's parameters. After that, those three coefficient is then will be used in optimization of the VANET in terms of energy, PDR, and delay.
Channel Aware Mac Protocol for Maximizing Throughput and FairnessIJORCS
The proper channel utilization and the queue length aware routing protocol is a challenging task in MANET. To overcome this drawback we are extending the previous work by improving the MAC protocol to maximize the Throughput and Fairness. In this work we are estimating the channel condition and Contention for a channel aware packet scheduling and the queue length is also calculated for the routing protocol which is aware of the queue length. The channel is scheduled based on the channel condition and the routing is carried out by considering the queue length. This queue length will provide a measurement of traffic load at the mobile node itself. Depending upon this load the node with the lesser load will be selected for the routing; this will effectively balance the load and improve the throughput of the ad hoc network.
PERFORMANCE OF OLSR MANET ADOPTING CROSS-LAYER APPROACH UNDER CBR AND VBR TRA...IJCNCJournal
The routing protocols play an important role in Mobile Ad-Hoc Network (MANET) because of the dynamically change of its topology. Optimized Link State Routing (OLSR), unawareness of Quality of Service (QoS) and power-consumed protocol, is an example of a widely-used routing protocol in MANET.
The Multi-Point Relays (MPR) selection algorithm is very crucial in OLSR. Therefore, firstly, we propose a heuristic method to select the best path based on two parameters; Bit Error Rate (BER) derived from the physical layer and Weighted Connectivity Index (CI) adopted from the network layer. This can be done via the cross-layer design scheme. This is anticipated to enhance the performance of OLSR, provide QoS
guarantee and improve the power consumption. The performances of the proposed scheme are investigated
by simulation of two types of traffics: CBR and VBR (MPEG-4), evaluated by metrics namely Throughput, Packet Delivery Ratio (PDR), Average End-to-End Delay, Control Overhead and Average Total Power Consumption.We compare our results with the typical OLSR and OLSR using only Weighted CI. It is
obvious that our proposed scheme provides superior performances to the typical OLSR and OLSR using only Weighted CI, especially, at high traffic load.
Performance evaluation of high mobility OFDM channel estimation techniques IJECEIAES
In wireless communication, Orthogonal Frequency Division Multiplexing (OFDM) has been adopted due to its robustness to multipath fading and high data rate transmissions. At the other hand, the performance of OFDM systems severely degraded due to multi-path fading and Doppler frequency shifts in mobile systems, which causes inter-carrier-interference (ICI). Thus, Estimation of channel parameters is required at the receiver using a pre designed estimator where pilot tones are inserted in each OFDM symbol. In this paper, a random pilot data are generated and inserted in each OFDM symbol at equally spaced locations. The performance test of Least Square (LS) and Linear Minimum Mean Square (LMMSE) estimation methods are proposed with Discrete Fourier Transform (DFT) based on both LS and LMMSE, where different ITU channel models are considered in order to compare their performance for data transmission in high mobile systems with different Doppler frequencies exceeds 200 Hz and minimal number of pilots.
ON DEMAND CHANNEL ASSIGNMENT METHOD FOR CHANNEL DIVERSITY (ODCAM)ijwmn
The IEEE 802.11s Wireless Mesh Networks (WMN) is a new multi-hop technology increasing the coverage
of IEEE 802.11 Wireless Network and providing Internet access. In order to increase the mesh network
capacity, the WMN has evolved from single-radio single-channel architecture to Multi-Channel Multi-
Radios (MC-MR) architecture. In MC-MR the main challenge of the WMN is the channel assignment. In
this article, we propose a new channel assignment method based on channel diversity. This new method
named ODCAM (On Demand channel Assignment Method for channel diversity ) defines a channel
diversity mechanism used to select a new channel along the path between the source and the destination.
The best path between the source and the destination is provided by the HWMP (Hybrid Wireless Mesh
Protocol) protocol using MWCETT (Modified Weighted Cumulative Expected Transmission Time) an
extension of the WCETT metric. The simulation results show the ODCAM performance compared with an
hybrid approach.
LTE QOS DYNAMIC RESOURCE BLOCK ALLOCATION WITH POWER SOURCE LIMITATION AND QU...IJCNCJournal
3GPP has defined the long term evolution (LTE) for 3G radio access in order to maintain the future
competitiveness for 3G technology, the system provides the capability of supporting a mixture of services
with different quality of service (QoS) requirements. This paper proposes a new cross-layer scheduling
algorithm to satisfy better QoS parameters for real time applications. The proposed algorithm takes care of
allocating resource blocks (RBs) with different modulation and coding schemes (MCS) according to target
bit error rate (BER), user equipment supportable MCS, queue stability constraints and available transmit
power constraints. The proposed algorithm has been valued, compared with an earlier allocation algorithm
in terms of service rate and packet delay and showed better performance regards the real time
applications.
Routing in All-Optical Networks Using Recursive State Space Techniquesipij
In this papr, we have minimized the effects of failures on network performace, by using suitable Routing
and Wavelenghth Assignment(RWA) method without disturbing other performance criteria such as blocking
probability(BP) and network management(NM). The computation complexity is reduced by using Kalaman
Filter(KF) techniques. The minimum reconfiguration probability routing (MRPR) algorithm must be
able to select most reliable routes and assign wavelengths to connections in a manner that utilizes the light
path(LP) established efficiently considering all possible requests.
Daly Analysis for WiMax under balanced and unbalanced traffic conditions in f...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
PERFORMANCE OF MIMO MC-CDMA SYSTEM WITH CHANNEL ESTIMATION AND MMSE EQUALIZATIONTamilarasan N
The quality of a wireless link can be described by three basic parameters, namely transmission rate, transmission range
and transmission reliability. With the advent of multiple-input multiple-output (MIMO) assisted Multicarrier code
division multiple access (MC-CDMA) systems, the above-mentioned three parameters may be simultaneously
improved. The MC-CDMA combined with the MIMO technique, has become a core technology for future mobile radio
communication system. However, possible potential gain in spectral efficiency is challenged by the receiver’s ability to
accurately detect the symbol due to inter symbol interference (ISI). Multipath propagation, mobility of transmitter,
receiver and local scattering cause the signal to be spread in frequency, different arrival time and angle, which results in
ISI in the received signal. This will affect overall system performance. The use of MC-CDMA mitigates the problem of
time dispersion. However, still it is necessary to remove the amplitude and phase shift caused by channel. To solve this
problem, a multiple antenna array can be used at the receiver, not only for spectral efficiency or gain enhancement, but
also for interference suppression. This can be done by the, efficient channel estimation with strong equalization. This
paper proposes MIMO MC-CDMA system, Minimum mean square error (MMSE) equalization with pilot based
channel estimation. The simulation result shows improved Bit error rate (BER) performance when the sub carrier (SC)
and antenna configuration were increased
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.
An Efficient and Stable Routing Algorithm in Mobile Ad Hoc NetworkIJCNCJournal
Mobile Ad hoc Network (MANET) is mainly designed to set up communication among devices in infrastructure-less wireless communication network. Routing in this kind of communication network is highly affected by its restricted characteristics such as frequent topological changes and limited battery power. Several research works have been carried out to improve routing performance in MANET. However, the overall performance enhancement in terms of packet delivery, delay and control message overhead is still not come into the wrapping up. In order to overcome the addressed issues, an Efficient and Stable-AODV (EFST-AODV) routing scheme has been proposed which is an improvement over AODV to establish a better quality route between source and destination. In this method, we have modified the route request and route reply phase. During the route request phase, cost metric of a route is calculated on the basis of parameters such as residual energy, delay and distance. In a route reply phase, average residual energy and average delay of overall path is calculated and the data forwarding decision is taken at the source node accordingly. Simulation outcomes reveal that the proposed approach gives better results in terms of packet delivery ratio, delay, throughput, normalized routing load and control message overhead as compared to AODV.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
3GPP has introduced LTE Femtocells to manipulate the traffic for indoor users and to minimize
the charge on the Macro cells. A key mechanism in the LTE traffic handling is the packet
scheduler which is in charge of allocating resources to active flows in both the frequency and
time dimension. So several scheduling algorithms need to be analyzed for femtocells networks.
In this paper we introduce a performance analysis of three distinct scheduling algorithms of
mixed type of traffic flows in LTE femtocells networks. The particularly study is evaluated in
terms of throughput, packet loss ratio, fairness index and spectral efficiency.
Capacity improvement of mimo ofdma system using adaptive resource allocation ...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.
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.
Fifth generation (5G) Vehicular Cloud Computing (VCC) systems use heterogeneous network access technologies to
fulfill the requirements of modern services. Multiple services with dierent Quality of Service (QoS) constraints could be available in each vehicle, while at the same time, user requirements and provider policies must be addressed. Therefore, the design of ecient Vertical Handover (VHO) management schemes for 5G-VCC infrastructures is needed. In this paper, a novel VHO management scheme for 5G-VCC systems is proposed. Whenever the user satisfaction grade becomes less than a predefined threshold, VHO is initiated and network selection is performed, considering the velocity of the vehicle, network characteristic criteria such as throughput, delay, jitter and packet loss, as well as provider policy criteria such as service reliability, security and price. The proposed scheme uses linguistic values for VHO criteria attributes represented by Interval Valued Pentagonal Fuzzy Numbers (IVPFNs) to express the information using membership intervals. The VHO scheme is applied to a 5G-VCC system which includes 3GPP Long Term Evolution (LTE) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX) Macrocells and Femtocells, as well as IEEE 802.11p Wireless Access for Vehicular Environment (WAVE) Road Side Units (RSUs). Performance evaluation shows that the suggested method ensures the Always Best Connection (ABC) principle, while at the same time outperforms existing VHO management schemes.
Congestion control based on sliding mode control and scheduling with prioriti...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.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
LTE QOS DYNAMIC RESOURCE BLOCK ALLOCATION WITH POWER SOURCE LIMITATION AND QU...IJCNCJournal
3GPP has defined the long term evolution (LTE) for 3G radio access in order to maintain the future
competitiveness for 3G technology, the system provides the capability of supporting a mixture of services
with different quality of service (QoS) requirements. This paper proposes a new cross-layer scheduling
algorithm to satisfy better QoS parameters for real time applications. The proposed algorithm takes care of
allocating resource blocks (RBs) with different modulation and coding schemes (MCS) according to target
bit error rate (BER), user equipment supportable MCS, queue stability constraints and available transmit
power constraints. The proposed algorithm has been valued, compared with an earlier allocation algorithm
in terms of service rate and packet delay and showed better performance regards the real time
applications.
Routing in All-Optical Networks Using Recursive State Space Techniquesipij
In this papr, we have minimized the effects of failures on network performace, by using suitable Routing
and Wavelenghth Assignment(RWA) method without disturbing other performance criteria such as blocking
probability(BP) and network management(NM). The computation complexity is reduced by using Kalaman
Filter(KF) techniques. The minimum reconfiguration probability routing (MRPR) algorithm must be
able to select most reliable routes and assign wavelengths to connections in a manner that utilizes the light
path(LP) established efficiently considering all possible requests.
Daly Analysis for WiMax under balanced and unbalanced traffic conditions in f...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
PERFORMANCE OF MIMO MC-CDMA SYSTEM WITH CHANNEL ESTIMATION AND MMSE EQUALIZATIONTamilarasan N
The quality of a wireless link can be described by three basic parameters, namely transmission rate, transmission range
and transmission reliability. With the advent of multiple-input multiple-output (MIMO) assisted Multicarrier code
division multiple access (MC-CDMA) systems, the above-mentioned three parameters may be simultaneously
improved. The MC-CDMA combined with the MIMO technique, has become a core technology for future mobile radio
communication system. However, possible potential gain in spectral efficiency is challenged by the receiver’s ability to
accurately detect the symbol due to inter symbol interference (ISI). Multipath propagation, mobility of transmitter,
receiver and local scattering cause the signal to be spread in frequency, different arrival time and angle, which results in
ISI in the received signal. This will affect overall system performance. The use of MC-CDMA mitigates the problem of
time dispersion. However, still it is necessary to remove the amplitude and phase shift caused by channel. To solve this
problem, a multiple antenna array can be used at the receiver, not only for spectral efficiency or gain enhancement, but
also for interference suppression. This can be done by the, efficient channel estimation with strong equalization. This
paper proposes MIMO MC-CDMA system, Minimum mean square error (MMSE) equalization with pilot based
channel estimation. The simulation result shows improved Bit error rate (BER) performance when the sub carrier (SC)
and antenna configuration were increased
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.
An Efficient and Stable Routing Algorithm in Mobile Ad Hoc NetworkIJCNCJournal
Mobile Ad hoc Network (MANET) is mainly designed to set up communication among devices in infrastructure-less wireless communication network. Routing in this kind of communication network is highly affected by its restricted characteristics such as frequent topological changes and limited battery power. Several research works have been carried out to improve routing performance in MANET. However, the overall performance enhancement in terms of packet delivery, delay and control message overhead is still not come into the wrapping up. In order to overcome the addressed issues, an Efficient and Stable-AODV (EFST-AODV) routing scheme has been proposed which is an improvement over AODV to establish a better quality route between source and destination. In this method, we have modified the route request and route reply phase. During the route request phase, cost metric of a route is calculated on the basis of parameters such as residual energy, delay and distance. In a route reply phase, average residual energy and average delay of overall path is calculated and the data forwarding decision is taken at the source node accordingly. Simulation outcomes reveal that the proposed approach gives better results in terms of packet delivery ratio, delay, throughput, normalized routing load and control message overhead as compared to AODV.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
3GPP has introduced LTE Femtocells to manipulate the traffic for indoor users and to minimize
the charge on the Macro cells. A key mechanism in the LTE traffic handling is the packet
scheduler which is in charge of allocating resources to active flows in both the frequency and
time dimension. So several scheduling algorithms need to be analyzed for femtocells networks.
In this paper we introduce a performance analysis of three distinct scheduling algorithms of
mixed type of traffic flows in LTE femtocells networks. The particularly study is evaluated in
terms of throughput, packet loss ratio, fairness index and spectral efficiency.
Capacity improvement of mimo ofdma system using adaptive resource allocation ...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.
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.
Fifth generation (5G) Vehicular Cloud Computing (VCC) systems use heterogeneous network access technologies to
fulfill the requirements of modern services. Multiple services with dierent Quality of Service (QoS) constraints could be available in each vehicle, while at the same time, user requirements and provider policies must be addressed. Therefore, the design of ecient Vertical Handover (VHO) management schemes for 5G-VCC infrastructures is needed. In this paper, a novel VHO management scheme for 5G-VCC systems is proposed. Whenever the user satisfaction grade becomes less than a predefined threshold, VHO is initiated and network selection is performed, considering the velocity of the vehicle, network characteristic criteria such as throughput, delay, jitter and packet loss, as well as provider policy criteria such as service reliability, security and price. The proposed scheme uses linguistic values for VHO criteria attributes represented by Interval Valued Pentagonal Fuzzy Numbers (IVPFNs) to express the information using membership intervals. The VHO scheme is applied to a 5G-VCC system which includes 3GPP Long Term Evolution (LTE) and IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX) Macrocells and Femtocells, as well as IEEE 802.11p Wireless Access for Vehicular Environment (WAVE) Road Side Units (RSUs). Performance evaluation shows that the suggested method ensures the Always Best Connection (ABC) principle, while at the same time outperforms existing VHO management schemes.
Congestion control based on sliding mode control and scheduling with prioriti...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.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
QOS ROUTING AND PERFORMANCE EVALUATION FOR MOBILE AD HOC NETWORKS USING OLSR ...ijasuc
Mobile Ad-Hoc network is a collection of mobile nodes in communication without using infrastructure.
As the real-time applications used in today’s wireless network grow, we need some schemes to provide
more suitable service for them. We know that most of actual schemes do not perform well on traffic which
is not strictly CBR. Therefore, in this paper we have studied the impact, respectively, of mobility models
and the density of nodes on the performances (End-to-End Delay, Throughput and Packet Delivery ratio)
of routing protocol (Optimized Link State Routing) OLSR by using in the first a real-time VBR (MPEG-4)
and secondly the Constant Bit Rate (CBR) traffic. Finally we compare the performance on both cases.
Experimentally, we considered the three mobility models as follows Random Waypoint, Random
Direction and Mobgen Steady State. The experimental results illustrate that the behavior of OLSR change
according to the model and the used traffics.
A New Model of Genetic Zone Routing Protocol (GZRP): The Process of Load Bala...TELKOMNIKA JOURNAL
The stages of the process of Genetic Algorithm (GA), are: Encoding Genotype and Chromosome;
Set Initialization Population; Evaluation Fitness Function; and Selection Process as well as in the later
stages Cross Over Process and Mutation. Outputs from the tests performed in this study can be obtained
by comparing the Genes of the Child (condition data traffic on the UMTS Hybrid - 802.11g network after
the GA) against Gen Holding (traffic data before the GA process).
The research was conducted by calculating the environmental factors, namely: The scheme Two
- Ray Model Propagation and Overlapping Channel Interference Factor, the Doppler Effect be ignored
because the User Equipment (UE) is considered not to shift significant arenas on the IEEE 802.11g
networks. The results of the research is as follows: In the process of cross over, there is a significant
change in the bandwidth, data traffic capacity and Power parameter changes by 9 MHz, 36 MB, and 40
dBm. In the process of mutation, there is a significant change in the bandwidth, data traffic capacity, and
Power parameter by 17 MHz, 32 MB, and 20 dBm.
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.
An Approach using Local Information to Build QoS Routing Algorithminventionjournals
The requirement for quality of service (QoS) is more and more sophisticated, such as the required bandwidth, the value of delay time or packet loss. To assure the network performance, localized QoS routing algorithms have recently been proposed as a promising alternative to the currently deployed global QoS routing schemes. Different from the traditional QoS routing algorithms which use global state information, the localized routing algorithms use local information collected from source node to make routing decisions. These localized routing algorithms can be solutions to users’ demand in the near future. In this paper, we propose a new localized QoS routing algorithm which can help to assure quality of service, and show our simulations which are better in results against other routing algorithms.
Mobile environment pretense a number of novel
theoretical and optimization issues such as position, operation
and following in that a lot of requests rely on them for
desirable information. The precedent works are sprinkled
across the entire network layer: from the medium of physical
to link layer to routing and then application layer. In this
invention, we present outline solutions in Medium Access
Control (MAC), data distribution, coverage resolve issues
under mobile ad-hoc network environment based on
congestion control technique using Transmission Control
Protocol (TCP). In mobile ad-hoc network issues can arise
such as link disconnections, channel contention and recurrent
path loss. To resolve this issue, we propose a Cross Layer
based Hybrid fuzzy ad-hoc rate based Congestion Control
(CLHCC) approach to maximize network performance. Based
on the destination report it regulates the speed of data flow to
control data loss by monitoring the present network status
and transmits this report to the source as advice. The source
adjusts the sending flow rate as per the advice. This is
monitored by channel usage, ultimate delay, short term
throughput.
A Machine Learning based Network Sharing System Design with MPTCPIJMREMJournal
The information and communication technologies (ICT) integrate different types of wireless communication to
provide IT-enabled services and applications. The great majority end devices are equipped with multiple network
interfaces such as Wi-Fi and 4G. Our goal is to integrate the available network interfaces and technologies to
enhance seamless communication efficiency and increase resources utilization. We proposed a heterogeneous
network management algorithm based on machine learning methods which includes roaming and sharing
functions. The roaming function provides the multiple network resources in physical and media access control
layers. The sharing function supports multiple network resources allocation and the service handover process
based on the Multi-Path TCP protocol. The simulation result also shows that the proposed scheme can increase
the network bandwidth utilization effectively. The sharing system could be used in home, mobile and vehicular
environments to realize ubiquitous social sharing networks.
A Machine Learning based Network Sharing System Design with MPTCPIJMREMJournal
The information and communication technologies (ICT) integrate different types of wireless communication to provide IT-enabled services and applications. The great majority end devices are equipped with multiple network interfaces such as Wi-Fi and 4G. Our goal is to integrate the available network interfaces and technologies to enhance seamless communication efficiency and increase resources utilization. We proposed a heterogeneous network management algorithm based on machine learning methods which includes roaming and sharing functions. The roaming function provides the multiple network resources in physical and media access control layers. The sharing function supports multiple network resources allocation and the service handover process based on the Multi-Path TCP protocol. The simulation result also shows that the proposed scheme can increase the network bandwidth utilization effectively. The sharing system could be used in home, mobile and vehicular environments to realize ubiquitous social sharing networks.
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 Scheme with Adaptive Criteria Weights for 5G Vehicular Sy...University of Piraeus
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.
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 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.
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.
A Personalized Audio Web Service using MPEG-7 and MPEG-21 standards (presenta...University of Piraeus
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.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
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2. selection is executed, while no femtocells are considered
as alternatives.
• The vehicle velocity is greater than 30 km
h and it is
not already connected to a femtocell: Accordingly, the
VHO initiation will be executed, while no femtocells are
considered as alternatives.
• The vehicle velocity is less than 30 km
h : Then, the
VHO initiation will be executed, while all the available
networks will be considered as alternatives.
A. VHO initiation
During the VHO initiation process the Su,i parameter is
defined, determining the satisfaction grade of user u from
his current network i. If the satisfaction grade is less than
a predefined Sth threshold value, then the network selection
process will be executed. More specifically, Su,i is calculated
using a Mamdani FIS which considers two parameters, the
RSSu,i and the Qu,i. The RSSu,i represents the Received
Signal Strength, while the Qu,i represents the quality of the
user’s services offered from the current network. Qu,i is
calculated using formula 1, where thu,i,k, du,i,k, ju,i,k and
plu,i,k represent the throughput, the delay, the jitter and the
packet loss ratio respectively, obtained by user u for the service
k. Additionally, the wth,k, wd,k ,wj,k and wp,kl represent the
weights of the aforementioned parameters, while N represents
the number of the parameters considered and K the number
of the available services.
Qu,i =
K
k=1
(wth,k · thu,i,k + wd,k ·
1
du,i,k
+
wj,k ·
1
ju,i,k
+ wpl,k ·
1
plu,i,k
)/N /K
(1)
Both RSSu,i and Qu,i are normalized in order to have
values within the range [0, 1]. Also, the MFRSS, MFQ,
MFS membership functions (MF) are defined, indicating the
linguistic terms and the corresponding Interval Valued Trape-
zoidal Fuzzy Numbers (IVTFN) for the fuzzy representation
of the RSSu,i, Qu,i and Su,i respectively. Thus, for each
crisp value, two membership degrees are determined in the
corresponding MF, one for the upper trapezoid and one for the
lower trapezoid. The Mamdani FIS implements the following
methods:
a) Fuzzy rule (or knowledge) base: A set R of fuzzy
rules is defined, where each rule r ∈ R is a simple if-then
statement with a condition and a conclusion. The rule’s con-
dition consists of MFRSS and MFQ membership functions,
while its conclusion indicates an MFS membership function.
b) Fuzzification: The RSSu,i and Qu,i crisp values are
converted to degrees of membership indicated as RSSu,i and
Qu,i by a lookup in MFRSS and MFQ membership functions
respectively.
c) Combining the fuzzified inputs (Fuzzy Operations):
A Zu,i,r degree is calculated considering the rule’s condition,
indicating the strength of the rule. Furthermore, in case that a
rule’s condition has multiple parts, the fuzzy operators ‘AND’
and ‘OR’ may be used to combine more than one conditions.
The ‘Algebraic product’ and the ‘Algebraic sum’ are applied
for the ‘AND’ and the ‘OR’ operators respectively. In our case,
the ‘Algebraic product’ is calculated using formula 2, while
the ‘Algebraic sum’ is calculated using formula 3.
Zu,i,r = RSSu,i,rˆ·Qu,i,r = RSSu,i,r · Qu,i,r (2)
Zu,i,r = (RSSu,i,r + Qu,i,r) − (RSSu,i,r · Qu,i,r) (3)
d) Implication method: The implication method esti-
mates the consequence MFSc
r
of the rule conclusion, con-
sidering both the rule conclusion MFSr and the rule strength
Zu,i,r. More specifically, the MFSr
height is trimmed with
respect to the Zu,i,r degree, using formula 4, which applies
the Min method.
MFSc
rHeight
= min{MFSrHeight
, Zu,i,r} (4)
e) Aggregation method: The aggregation method com-
bines the R rules’ consequences to calculate the SA
u,i fuzzy
set, using formula 5, which applies the Max method.
SA
u,i = MFSc
r
(r = 1)∪MFSc
r
(r = 2)∪...∪MFSc
r
(r = R)
(5)
f) Defuzzification: During the defuzzification, the SA
u,i
fuzzy set is transformed to the crisp value Su,i. Formula 6
that applies the Weighted Average method is used, where µr
is the height and hr is the centroid of each rule obtained from
the SA
u,i. Also, symbols U and L represent the upper and the
lower trapezoid of each rule respectively .
Su,i =
R
r=1
(µU
r · hU
r + µL
r · hL
r )
R
r=1
(hU
r + hL
r )
(6)
B. Network selection
The network selection is performed using the Trapezoidal
Fuzzy Topsis (TFT) [8] algorithm. TFT is based on the
concept that the best alternative should have the shortest
distance from the positive ideal solution and the longer dis-
tance 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, . . . , ALn} is the set of possible
alternatives, CR = {CR1, CR2, . . . , CRn} is the set of
criteria and w1, w2, . . . , wm are the weights of each criterion.
The steps of the method are as follows:
a) Construction of the decision matrix: Each gij element
of the n × m decision matrix DM is an interval-valued
trapezoidal fuzzy number which expresses the performance
of alternative i for criterion j. Thus
DM =
CR1 . . . CRm
AL1 g11 . . . g1m
...
...
...
...
ALn gn1 . . . gnm
(7)
where gij = (gL
ij1, gL
ij2, gL
ij3, gL
ij4, vL
ij), (gU
ij1, gU
ij2, gU
ij3, gU
ij4, vU
ij) .
2017 IEEE Symposium on Computers and Communications (ISCC)
3. In the case that there are D decision makers the decision
matrix and the criteria weights include the average of the
performance values and weights respectively, of the decision
makers. Hence, assuming that for the kth
decision maker xijk
is the performance of alternative i for criterion j, and wjk
is the importance weight for criterion j, the average of the
performance values and weights are given by formula 8 and
9, respectively.
gij =
1
D
D
d=1
gijd
(8)
wj =
1
D
·
D
d=1
wjd (9)
b) Normalization of the decision matrix: Consider that
Ωb is the set of benefits attributes and Ωc is the set of
costs attributes. Then, the elements of the normalized decision
matrix are calculated using either formula 10 or 11, where
bj = maxi gU
ij4 for each j ∈ Ωb and cj = mini gL
ij4 for each
j ∈ Ωc.
gij =
gL
ij1
bj
,
gL
ij2
bj
,
gL
ij3
bj
,
gL
ij4
bj
, vL
ij ,
gU
ij1
bj
,
gU
ij2
bj
,
gU
ij3
bj
,
gU
ij4
bj
, vU
ij
(10)
gij =
cj
gL
ij4
,
cj
gL
ij3
,
cj
gL
ij2
,
cj
gL
ij1
, vL
ij ,
cj
gU
ij4
,
cj
gU
ij3
,
cj
gU
ij2
,
cj
gU
ij1
, vU
ij
(11)
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
gij with the respective weight wj according to the formula 12.
uij = g L
ij1 · wj, g L
ij2 · wj, g L
ij3 · wj, g L
ij4 · wj, v L
ij ,
g U
ij1 · wj, g U
ij2 · wj, g U
ij3 · wj, g U
ij4 · wj, vU
ij
(12)
d) Determination of the positive and negative ideal so-
lution: The positive ideal solution is defined in 13, where
i
≡ maxi in case j ∈ Ωb and
i
≡ mini in case j ∈ Ωc.
Correspondingly, the negative ideal solution is defined in 14,
where i ≡ mini in case j ∈ Ωb and i ≡ maxi in case
j ∈ Ωc.
G+
= g+L
ij1 , g+L
ij2 , g+L
ij3 , g+L
ij4 , v+L
ij , g+U
ij1 , g+U
ij2 , g+U
ij3 , g+U
ij4 , v+U
ij
(13)
G−
= g−L
ij1 , g−L
ij2 , g−L
ij3 , g−L
ij4 , v−L
ij , g−U
ij1 , g−U
ij2 , g−U
ij3 , g−U
ij4 , v−U
ij
(14)
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 15 and 16.
Likewise the distances of each alternative from the negative
ideal solution are estimated using formulas 17 and 18.
p+
i1 =
m
j=1
1
4
uL
ij1 − g+L
ij1
2
+
uL
ij2 − g+L
ij2
2
+ uL
ij3 − g+L
ij3
2
+ uL
ij4 − g+L
ij4
2
1
2
(15)
p+
i2 =
m
j=1
1
4
uU
ij1 − g+U
ij1
2
+
uU
ij2 − g+U
ij2
2
+ uU
ij3 − g+U
ij3
2
+ uU
ij4 − g+U
ij4
2
1
2
(16)
p−
i1 =
m
j=1
1
4
uL
ij1 − g−L
ij1
2
+
uL
ij2 − g−L
ij2
2
+ uL
ij3 − g−L
ij3
2
+ uL
ij4 − g−L
ij4
2
1
2
(17)
p−
i2 =
m
j=1
1
4
uU
ij1 − g−U
ij1
2
+
uU
ij2 − g−U
ij2
2
+ uU
ij3 − g−U
ij3
2
+ uU
ij4 − g−U
ij4
2
1
2
(18)
Consequently, similar to [9] 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 19. Subsequently, the compound relative
closeness is obtained using formula 20.
RCij =
p−
ij
p+
ij + p−
ij
j = 1, 2 (19)
RCi =
RCi1 + RCi2
2
(20)
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 we consider the Software Defined
VANET Cloud topology presented in figure 1, which includes
a heterogeneous network environment and a cloud infrastruc-
ture. The network environment consists of one LTE Macrocell,
two LTE Femtocells and two 802.11p RSUs, with radius
equal to 250m, 120m and 15m respectively. Accordingly, the
Cloud infrastructure includes a set of Virtual Machines (VMs)
providing services such as Navigation Assistance (NAV),
Voice over IP (VoIP), Conversational Video (CV), Buffered
Streaming (BS) and Web Browsing (WB). Furthermore, a Soft-
ware Defined Network (SDN) controller provides centralized
control of the entire system.
Each access network supports at least one of the afforemen-
tioned Cloud services, while three Service Level Agreements
(SLAs) are defined. Each SLA determines the provided speci-
fication per network for each service type, in terms of through-
put, delay, jitter, packet loss ratio, price, security and service
reliability. Service reliability determines the ability for service
constraints satisfaction and optimization of performance when
a network is congested. SLA1 has the higher service priority,
while SLA3 has the lower one. Additionally, SLA1 supports
2017 IEEE Symposium on Computers and Communications (ISCC)
4. Cloud
SDN
controller
VM
Services
VM
Services
VM
Services
VM
Services
VM
Services
VM
Services
VM
Services
VM
Services
...
...
...
... ...
...
...
...
LTE Macro
802.11p RSU1802.11p RSU1 802.11p RSU2802.11p RSU2
LTE
Femto2
LTE
Femto2
LTE
Femto1
LTE
Femto1
Fig. 1: The simulated topology.
all service types and provides the best values for QoS and
policy decision criteria. SLA2 supports less service types and
slightly worse decision criteria values. Finally, SLA3 supports
only the WB service and provides acceptable decision criteria
values. The linguistic terms for the criteria attributes are
represented by interval-valued trapezoidal fuzzy numbers as
shown in table I.
TABLE I: Lingustic 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, 0.8), (0.0, 0.0, 0.0, 0.0, 1)]
Very Poor (VP) [(0.01, 0.02, 0.03, 0.07, 0.8), (0.0, 0.01, 0.05, 0.08, 1)]
Poor (P) [(0.04, 0.1, 0.18, 0.23, 0.8), (0.02, 0.08, 0.2, 0.25, 1)]
Medium Poor (MP) [(0.17, 0.22, 0.36, 0.42, 0.8), (0.14, 0.18, 0.38, 0.45, 1)]
Medium (M) [(0.32, 0.41, 0.58, 0.65, 0.8), (0.28, 0.38, 0.6, 0.7, 1)]
Medium Good (MG) [(0.58, 0.63, 0.8, 0.86, 0.8), (0.5, 0.6, 0.9, 0.92, 1)]
Good (G) [(0.72, 0.78, 0.92, 0.97, 0.8), (0.7, 0.75, 0.95, 0.98, 1)]
Very Good (VG) [(0.93, 0.98, 1, 1, 0.8), (0.9, 0.95, 1, 1, 1)]
Absolutely Good (AG) [(1, 1, 1, 1, 0.8), (1, 1, 1, 1, 1)]
We consider the case where 10 vehicles are moving inside
the heterogeneous 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 respective
SLA agreements. For each vehicle, table III presents its SLA
and the services used. Also, the current access network, the
candidate networks as well as the next process (VHO initiation
or network selection) that must be executed, according to the
proposed algorithm, are shown.
A. VHO initiation
During the VHO initiation process, the Analytic Hierarchy
Process (AHP) [10] method is applied in order to estimate the
services weights. The criteria used include throughput, delay,
TABLE II: The available networks of each SLA.
SLA Service Network Throughput Delay Jitter
Packet
Loss
Price
Service
Reliability
Security
SLA1
NAV
LTE
Macro
VG
(300 Kbps)
AG
(25 ms)
AG
(15 ms)
VG
(10−3)
VP AG VG
LTE
Femto1
G
(290 Kbps)
MG
(40 ms)
VG
(25 ms)
AG
(10−4)
VP VG AG
LTE
Femto2
AG
(305 Kbps)
AG
(25 ms)
VG
(22 ms)
VG
(10−3)
AP G G
802.11p
RSU1
MG
(280 Kbps)
MG
(40 ms)
G
(30 ms)
VG
(10−3)
MP MG MG
802.11p
RSU2
M
(270 Kbps)
M
(45 ms)
MG
(35 ms)
VG
(10−3)
MP MG MG
VoIP
LTE
Macro
MG
(210 Kbps)
MG
(90 ms)
VG
(22 ms)
VG
(10−4)
VP AG VG
LTE
Femto1
AG
(250 Kbps)
AG
(40 ms)
AG
(15 ms)
MG
(10−2)
VP VG AG
LTE
Femto2
AG
(240 Kbps)
VG
(50 ms)
G
(28 ms)
G
(10−3)
MP AG VG
802.11p
RSU1
MG
(210 Kbps)
MG
(90 ms)
MG
(30 ms)
AG
(10−5)
P MG G
802.11p
RSU2
G
(220 Kbps)
G
(80 ms)
VG
(20 ms)
AG
(10−5)
MP MG G
CV
LTE
Macro
MP
(8 Mbps)
MG
(60 ms)
VG
(35 ms)
AG
(10−5)
AP AG VG
LTE
Femto1
AG
(9.5 Mbps)
AG
(45 ms)
AG
(25 ms)
VG
(10−4)
AP VG AG
LTE
Femto2
G
(9 Mbps)
VG
(50 ms)
AG
(25 ms)
AG
(10−5)
MP VG G
802.11p
RSU1
MG
(8.5 Mbps)
MG
(60 ms)
G
(40 ms)
AG
(10−5)
MP MG VG
802.11p
RSU2
MP
(8 Mbps)
MP
(70 ms)
MG
(45 ms)
AG
(10−5)
MP MG G
BS
LTE
Macro
M
(8 Mbps)
G
(60 ms)
VG
(40 ms)
VG
(10−6)
AP AG VG
LTE
Femto1
VG
(9 Mbps)
VG
(55 ms)
AG
(35 ms)
AG
(10−7)
AP VG AG
LTE
Femto2
G
(8.5 Mbps)
G
(60 ms)
VG
(40 ms)
AG
(10−7)
MP VG G
802.11p
RSU1
VG
(9 Mbps)
AG
(50 ms)
VG
(40 ms)
AG
(10−7)
MP MG VG
802.11p
RSU2
G
(8.7 Mbps)
VG
(55 ms)
G
(45 ms)
AG
(10−7)
MP MG G
WB
LTE
Macro
AG
(3.2 Mbps)
AG
(150ms)
AG
(80 ms)
AG
(10−5)
VP AG VG
LTE
Femto1
MG
(2.5 Mbps)
M
(190ms)
G
(90 ms)
VG
(10−4)
MP VG AG
LTE
Femto2
VG
(3 Mbps)
G
(170ms)
M
(100ms)
AG
(10−5)
MP VG G
802.11p
RSU1
AG
(3.2 Mbps)
G
(170ms)
G
(90 ms)
AG
(10−5)
P MG MG
802.11p
RSU2
G
(2.8 Mbps)
M
(190ms)
AG
(80 ms)
AG
(10−5)
MP MG G
SLA2
CV
LTE
Macro
MP
(8 Mbps)
M
(65 ms)
MG
(45 ms)
G
(10−3)
MP G G
LTE
Femto1
G
(9 Mbps)
G
(55 ms)
VG
(35 ms)
VG
(10−4)
M G G
LTE
Femto2
MG
(8.5 Mbps)
MG
(60 ms)
AG
(30 ms)
VG
(10−4)
MP G MG
802.11p
RSU1
MP
(8 Mbps)
MP
(70 ms)
M
(50 ms)
VG
(10−4)
M G MG
802.11p
RSU2
MP
(8 Mbps)
P
(75 ms)
P
(60 ms)
VG
(10−4)
M P M
BS
LTE
Macro
M
(8 Mbps)
G
(60 ms)
MG
(50 ms)
VG
(10−6)
MP G G
LTE
Femto1
M
(8 Mbps)
MG
(65 ms)
AG
(35 ms)
AG
(10−7)
MP G G
LTE
Femto2
MG
(8.2 Mbps)
M
(70 ms)
VG
(40 ms)
AG
(10−7)
M MG M
802.11p
RSU1
G
(8.5 Mbps)
VG
(55 ms)
G
(45 ms)
AG
(10−7)
M MP G
802.11p
RSU2
P
(6.7 Mbps)
MP
(80 ms)
M
(60 ms)
VG
(10−6)
MP P M
WB
LTE
Macro
G
(2.8 Mbps)
M
(190ms)
M
(100ms)
AG
(10−5)
MP MG M
LTE
Femto1
M
(2.3 Mbps)
MP
(200ms)
MG
(95 ms)
VG
(10−4)
M G G
LTE
Femto2
MG
(2.5 Mbps)
M
(190ms)
M
(100ms)
AG
(10−5)
M M M
802.11p
RSU1
G
(2.8 Mbps)
M
(190ms)
M
(100ms)
AG
(10−5)
MP MG MP
802.11p
RSU2
MG
(2.5 Mbps)
MP
(200ms)
MG
(95 ms)
AG
(10−5)
M M MG
SLA3 WB
LTE
Macro
MP
(2 Mbps)
P
(210ms)
M
(100ms)
G
(10−3)
VG P P
LTE
Femto1
M
(2.3 Mbps)
M
(190ms)
G
(90 ms)
VG
(10−4)
VG P MP
LTE
Femto2
VP
(1.8 Mbps)
P
(220ms)
P
(120ms)
AG
(10−5)
VG VP VP
802.11p
RSU1
AP
(1.1 Mbps)
VP
(260ms)
P
(120ms)
VG
(10−4)
AG VP AP
802.11p
RSU2
AP
(1.0 Mbps)
AP
(300ms)
VP
(140ms)
G
(10−3)
AG AP AP
jitter and packet loss. Figure 2 depicts the estimated VHO
initiation weights for each service.
The linguistic terms for the RSSu,i, Qu,i and Su,i are
represented by interval-valued trapezoidal fuzzy numbers as
shown in table IV. The RSSu,i and Qu,i values are combined
using a Mamdani Fuzzy Inference System (FIS) [6], which
2017 IEEE Symposium on Computers and Communications (ISCC)
5. TABLE III: The simulated vehicles.
Vehicle SLA Velocity Services Current Network (RSS)
Candidate
Networks
Next process
1 1 10 kmh VoIP, CV LTE Femto2 (-85dBm) All VHO initiation
2 1 50 kmh
NAV,
VoIP
80211p RSU1 (-68 dBm)
All except
femtocells
VHO initiation
3 1 80 kmh CV LTE Femto1 (-88 dBm)
All except
femtocells
Network selection
4 1 10 kmh NAV, WB LTE Femto2 (-105 dBm) All VHO initiation
5 2 40 kmh BS 80211p RSU2 (-70 dBm)
All except
femtocells
VHO initiation
6 2 20 kmh CV, WB LTE Macro (-107 dBm) All VHO initiation
7 2 10 kmh CV 80211p RSU2 (-77 dBm) All VHO initiation
8 2 5 kmh BS, WB 80211p RSU1 (-60 dBm) All VHO initiation
9 3 70 kmh WB 80211p RSU1 (-85 dBm)
All except
femtocells
VHO initiation
10 3 30 km WB 80211p RSU2 (-75 dBm) All VHO initiation
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
Navigation Assistance VoIP Conversational Video Buffered Streaming Web
Weight
VHO initiation weights
Throughput Delay Jitter Packet loss
Fig. 2: Criteria weights per service for the VHO initiation.
calculates the SA
u,i fuzzy set using the rules presented in table
V. Afterwards, the SA
u,i is defuzzified in order to extract
TABLE IV: Linguistic terms and the corresponding interval-valued
trapezoidal fuzzy numbers used for RSSu,i, Qu,i and Su,i.
RSSu,i membership functions.
Linguistic term Interval-valued trapezoidal fuzzy number
Too Bad (TB) [(0.0, 0.0, 0.0, 0.0, 0.8), (0.0, 0.0, 0.0, 0.0, 1)]
Bad (B) [(0.1, 0.2, 0.3, 0.4, 0.8), (0.01, 0.15, 0.38, 0.5, 1)]
Enough (EN) [(0.47, 0.59, 0.69, 0.75, 0.8), (0.4, 0.52, 0.74, 0.82, 1)]
More than Enough (ME) [(0.72, 0.78, 0.92, 0.97, 0.8), (0.7, 0.75, 0.95, 0.98, 1)]
Excellent (EX) [(1, 1, 1, 1, 0.8), (1, 1, 1, 1, 1)]
Qu,i membership functions.
Linguistic term Interval-valued trapezoidal fuzzy number
Absolutely Poor (AP) [(0.0, 0.0, 0.0, 0.0, 0.8), (0.0, 0.0, 0.0, 0.0, 1)]
Very Poor (VP) [(0.01, 0.02, 0.03, 0.07, 0.8), (0.0, 0.01, 0.05, 0.08, 1)]
Poor (P) [(0.04, 0.1, 0.18, 0.23, 0.8), (0.02, 0.08, 0.2, 0.25, 1)]
Medium Poor (MP) [(0.17, 0.22, 0.36, 0.42, 0.8), (0.14, 0.18, 0.38, 0.45, 1)]
Medium (M) [(0.32, 0.41, 0.58, 0.65, 0.8), (0.28, 0.38, 0.6, 0.7, 1)]
Medium Good (MG) [(0.58, 0.63, 0.8, 0.86, 0.8), (0.5, 0.6, 0.9, 0.92, 1)]
Good (G) [(0.72, 0.78, 0.92, 0.97, 0.8), (0.7, 0.75, 0.95, 0.98, 1)]
Very Good (VG) [(0.93, 0.98, 1, 1, 0.8), (0.9, 0.95, 1, 1, 1)]
Absolutely Good (AG) [(1, 1, 1, 1, 0.8), (1, 1, 1, 1, 1)]
Su,i membership functions.
Linguistic term Interval-valued trapezoidal fuzzy number
Absolute Unsatisfactory (AU) [(0.0, 0.0, 0.0, 0.0, 0.8), (0.0, 0.0, 0.0, 0.0, 1)]
Very Unsatisfactory (VU) [(0.01, 0.02, 0.03, 0.07, 0.8), (0.0, 0.01, 0.05, 0.08, 1)]
Unsatisfactory (U) [(0.04, 0.1, 0.18, 0.23, 0.8), (0.02, 0.08, 0.2, 0.25, 1)]
Slightly Unsatisfactory (SU) [(0.08, 0.14, 0.26, 0.3, 0.8), (0.04, 0.12, 0.32, 0.38, 1)]
Less than Acceptable (LA) [(0.17, 0.22, 0.36, 0.42, 0.8), (0.14, 0.18, 0.38, 0.45, 1)]
Slightly Acceptable (SA) [(0.32, 0.41, 0.58, 0.65, 0.8), (0.28, 0.38, 0.6, 0.7, 1)]
Acceptable (A) [(0.44, 0.52, 0.61, 0.75, 0.8), (0.37, 0.45, 0.68, 0.83, 1)]
More than Acceptable (MA) [(0.58, 0.63, 0.8, 0.86, 0.8), (0.5, 0.6, 0.9, 0.92, 1)]
Slightly Satisfactory (SS) [(0.72, 0.78, 0.92, 0.97, 0.8), (0.7, 0.75, 0.95, 0.98, 1)]
Satisfactory (S) [(0.83, 0.87, 0.95, 0.98, 0.8), (0.74, 0.77, 0.98, 0.99, 1)]
Very Satisfactory (VS) [(0.93, 0.98, 1, 1, 0.8), (0.9, 0.95, 1, 1, 1)]
Absolute Satisfactory (AS) [(1, 1, 1, 1, 0.8), (1, 1, 1, 1, 1)]
the crisp value Su,i expressing the satisfaction of user u for
his current network i. Figure 3 illustrates the complete set of
possible Su,i values as a function of the initial RSSu,i and
Qu,i values. Indicatively, when the RSSu,i and Qu,i values
are too low, the produced Su,i value is too low as well. On
the contrary, when the RSSu,i and Qu,i values are close to 1,
the produced Su,i value is also high, indicating that the user is
fully satisfied. Furthermore, when only one of the RSSu,i or
the Qu,i values is close to 0, the user satisfaction is in quite
low levels.
Table VI presents the minimum acceptable values for
RSSSLA and QSLA per SLA as well as the evaluated Sth,SLA
TABLE V: The FIS rules for SA
u,i calculation.
Rule MFRSS Operator MFQ MFS
1 TB or AP AU
2 B and VP AU
3 EN and VP VU
4 ME and VP VU
5 EX and VP U
6 B and P AU
7 EN and P VU
8 ME and P U
9 EX and P SU
10 B and MP AU
11 EN and MP SU
12 ME and MP LA
13 EX and MP SA
14 B and M VU
15 EN and M LA
16 ME and M SA
17 EX and M A
18 B and MG VU
19 EN and MG SA
20 ME and MG A
21 EX and MG SS
22 B and G U
23 EN and G A
24 ME and G SS
25 EX and G S
26 B and VG U
27 EN and VG MA
28 ME and VG S
29 EX and VG VS
30 B and AG SU
31 EN and AG S
32 ME and AG VS
33 EX and AG AS
Fig. 3: The S values range as obtained using the FIS.
thresholds, which are obtained from the Mamdani FIS. Finally,
table VII presents the VHO initiation results for each vehicle.
As it can be observed, the VHO initiation process is ignored
for the vehicle 3, due to the fact that it moves with high
velocity while at the same time it is connected to a femtocell.
TABLE VI: The RSSSLA, QSLA and Sth,SLA thresholds per SLA.
SLA RSSSLA QSLA Sth,SLA
1 0.8 0.9 0.67287
2 0.7 0.7 0.49000
3 0.6 0.35 0.24076
TABLE VII: VHO initiation results.
Vehicle RSSu,i Qu,i Su,i Sth,SLA VHO required
1 1.000000 0.704539 0.84523 0.67287 No
2 0.733333 0.538458 0.41351 0.67287 Yes
3 - - - -
Yes
(according to velocity)
4 0.428571 0.773342 0.32516 0.67287 Yes
5 0.666667 0.697471 0.48699 0.49000 Yes
6 0.371429 0.844627 0.11667 0.49000 Yes
7 0.433333 0.661852 0.36116 0.49000 Yes
8 1.000000 0.986799 0.96375 0.49000 No
9 0.166667 0.408965 0.032391 0.24076 Yes
10 0.500000 0.345476 0.23878 0.24076 Yes
2017 IEEE Symposium on Computers and Communications (ISCC)
6. 0
0,1
0,2
0,3
0,4
0,5
Navigation
Assistance
(SLA1)
VoIP
(SLA1)
Conversational
Video
(SLA1)
Buffered
Streaming
(SLA1)
Web
(SLA1)
Conversational
Video
(SLA2)
Buffered
Streaming
(SLA2)
Web
(SLA2)
Web
(SLA3)
Weight
Network Selection weights for each SLA
Throughput Delay Jitter Packet loss Price Service Reliability Security
Fig. 4: Criteria weights per service and SLA for the Network Selection.
LTEFemto2
802.11pRSU1
LTEFemto1
LTEFemto2
802.11pRSU2
LTEMacro
802.11pRSU2
802.11pRSU1
802.11pRSU1
802.11pRSU2
LTEFemto2
LTEMacro
LTEMacro
LTEMacro
LTEMacro
LTEFemto1
LTEFemto1
802.11pRSU1
LTEMacro
LTEFemto1
LTEFemto2
802.11pRSU1
LTEFemto1
LTEMacro
802.11pRSU2
LTEFemto1
LTEFemto1
802.11pRSU1
LTEFemto1
802.11pRSU2
LTEFemto1
LTEMacro
LTEFemto1
LTEFemto2
LTEMacro
LTEMacro
802.11pRSU2
LTEMacro
802.11pRSU2
LTEMacro
0
0,02
0,04
0,06
0,08
0,1
0,12
0,14
Vehicle 1
v=10kmh
Vehicle 2
v=50kmh
Vehicle 3
v=80kmh
Vehicle 4
v=10kmh
Vehicle 5
v=40kmh
Vehicle 6
v=20kmh
Vehicle 7
v=10kmh
Vehicle 8
v=5kmh
Vehicle 9
v=70kmh
Vehicle 10
v=30kmh
TFTrank
TFT ranking of each VHO scheme
Current RSU Proposed Scheme UCCA Two-step
Fig. 5: Proposed VHO management scheme’s results.
B. Network selection
During the network selection process initially the Analytic
Network Process (ANP) [11] method is applied in order to
estimate the decision weights per service type and SLA,
considering the ANP network model proposed in [8]. The
criteria used include throughput, delay, jitter, packet loss,
price, service reliability and security. The decision weights
per service and SLA are obtained as presented in figure 4.
Subsequently, the TFT algorithm selects the best network
for each vehicle considering the vehicle service requirements
(Table III).
Figure 5 compares the results of the proposed scheme with
the ones obtained using the UCCA [3] and the Two-step [4]
VHO management schemes. In this figure, for each vehicle
the current network as well as the target network connection
estimated by each of the three schemes are presented. Ad-
ditionally, the TFT ranking of each network is given. From
the obtained results it is clear that the suggested algorithm
outperforms the existing schemes since it selects as target
networks for vehicles the ones with the best TFT ranks. Also,
in special cases where the velocity of vehicles is high (eg. for
vehicles 2, 3, 5 and 9) the proposed scheme considers only
the wide coverage candidate networks as alternatives avoiding
the handovers to femtocell networks.
IV. CONCLUSION
This paper proposes a VHO management scheme for VCC
systems. The vehicle velocity and its current network con-
nection type are considered. Subsequently, the VHO initiation
process estimates whether a VHO must be performed, while
the network selection algorithm selects the most appropriate
network, with respect to both vehicle’s services and operator’s
policies. Simulation results showed that the ABC principle is
fully ensured, while at the same time the proposed scheme
outperforms existing VHO management algorithms.
ACKNOWLEDGEMENTS
The publication of this paper has been partly supported by
the University of Piraeus Research Center (UPRC).
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