Context aware qo e modelling, measurement, and prediction in mobile computing systems
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IEEE PROJECTS 2015-2016
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JAVA 2013 IEEE DATAMINING PROJECT Distributed web systems performance forecas...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
The convergence of wireless networks and multimedia communicatio.docxcherry686017
The convergence of wireless networks and multimedia communications, linked to the swift development of services and the increasing competition, has caused user expectations of network quality to rise. Network quality has become one of the main targets for the network optimization and maintenance departments.
Traditionally, network measurements such as accessibility, maintainability, and quality were enough to evaluate the user experience of voice services [1]. However, for data services, the correlation between network measurements and user benefits is not as straightforward. Firstly, the data system, due to the use of packet switching, is affected by the performance of individual nodes and protocols through which information travels, and, secondly, radio resources are now shared among different applications. Under these conditions, the performance evaluation of data services is usually carried out by monitoring terminals on the real network.
The end-to-end quality experienced by an end user results from a combination of elements throughout the protocol stack and system components. Thus, the performance evaluation of the service requires a detailed performance analysis of the entire network (from the user equipment up to the application server or remote user equipment).
Quality of experience (QoE) is a subjective measurement of the quality experienced by a user when he uses a telecommunication service. The aim pursued when assessing the quality of service (QoS) may be the desire to optimize the operation of the network from a perspective purely based on objective parameters, or the more recent need of determining the quality that the user is actually achieving, as well as its satisfaction level. However, the QoE goes further and takes into account the satisfaction a user receives in terms of both content and use of applications. In this sense, the introduction of smartphones has been a quantitative leap in user QoE expectations.
Traditionally, QoE has been evaluated through subjective tests carried out on the users in order to assess their satisfaction degree with a mean opinion score (MOS) value. This type of approach is obviously quite expensive, as well as annoying to the user. Additionally, this method cannot be used for making decisions to improve the QoE on the move. That is why in recent years new methods have been proposed to estimate the QoE based on certain performance indicators associated with services. A possible solution to evaluate instantaneously the QoE is to integrate QoE analysers in the mobile terminal itself [2]. If mobile terminals are able to report the measurements to a central server, the
QoE assessment process is simplified significantly. Other solutions are focused on including new network elements (e.g., network analysers, deep packet inspectors, etc.) that are responsible for capturing the traffic from a certain service and analysing its performance [3]. For instance, the work presented in [4] investigates the ...
CHARACTERIZATION OF USER-PERCEIVED QUALITY OF SERVICE (QOS) IN MOBILE DEVICES...ijwmn
This paper presents a user-centric and application-specific QoS assessment methodology for cellular
communication networks. Specifically, it uses the Analytic Hierarchy Process (AHP) to evaluate QoS as a
multi-criteria decision problem that represents how well cellular networks’ data services are perceived
given particular sets of application classes and relative to other networks servicing in the same area. As
part of the methodology, drive testing is performed to collect objective measurements associated with
identified QoS criteria for data services. Once drive testing is performed and data collected, multiple
networks are compared to determine the network that provides higher QoS based on users’ perception of
quality. The selection of the best performing network is based on the output provided by the AHP
approach, which is used as unified measurement of the perceived QoS by users on different networks. In
order to determine application-specific priorities, the approach presented uses three different application
classes, including Emergency, Business, and Personal. For each class, the relative importance of each
quality evaluation criteria is adjusted in the AHP procedure to reflect the priorities of the services
expected. Through several case studies, the approach is proven successful in providing a way for
analyzing user-centric QoS for application-specific scenarios.
Correlating objective factors with videoIJCNCJournal
To succeed in providing services, the quality of services should meet users’ satisfaction. This is a motivation to study the relationship between the service quality and the real perceived quality of users, which is commonly referred to as the quality of experience (QoE). However, most of existing QoE studies that focus on video-on-demand or IPTV services analyze only the influence of network behaviors to video quality. This paper focuses on P2P video streaming services, which are becoming a significant portion of Internet traffic, and pays attention to the change of users’ perception with the adjustment of objective
factors as well as network behaviors. We propose to use mean opinion score and peak signal to noise ratio
methods as QoE evaluations to consider the effect of the chunk loss ratio, the group-of-picture size, and the
chunk size. The experimental results provide a convincing reference to build the complete relationship
between objective factors and QoE. We believe that this assessment will contribute to study a new service
quality evaluation mechanism based on users’ satisfaction in the future.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
JAVA 2013 IEEE DATAMINING PROJECT Distributed web systems performance forecas...IEEEGLOBALSOFTTECHNOLOGIES
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
The convergence of wireless networks and multimedia communicatio.docxcherry686017
The convergence of wireless networks and multimedia communications, linked to the swift development of services and the increasing competition, has caused user expectations of network quality to rise. Network quality has become one of the main targets for the network optimization and maintenance departments.
Traditionally, network measurements such as accessibility, maintainability, and quality were enough to evaluate the user experience of voice services [1]. However, for data services, the correlation between network measurements and user benefits is not as straightforward. Firstly, the data system, due to the use of packet switching, is affected by the performance of individual nodes and protocols through which information travels, and, secondly, radio resources are now shared among different applications. Under these conditions, the performance evaluation of data services is usually carried out by monitoring terminals on the real network.
The end-to-end quality experienced by an end user results from a combination of elements throughout the protocol stack and system components. Thus, the performance evaluation of the service requires a detailed performance analysis of the entire network (from the user equipment up to the application server or remote user equipment).
Quality of experience (QoE) is a subjective measurement of the quality experienced by a user when he uses a telecommunication service. The aim pursued when assessing the quality of service (QoS) may be the desire to optimize the operation of the network from a perspective purely based on objective parameters, or the more recent need of determining the quality that the user is actually achieving, as well as its satisfaction level. However, the QoE goes further and takes into account the satisfaction a user receives in terms of both content and use of applications. In this sense, the introduction of smartphones has been a quantitative leap in user QoE expectations.
Traditionally, QoE has been evaluated through subjective tests carried out on the users in order to assess their satisfaction degree with a mean opinion score (MOS) value. This type of approach is obviously quite expensive, as well as annoying to the user. Additionally, this method cannot be used for making decisions to improve the QoE on the move. That is why in recent years new methods have been proposed to estimate the QoE based on certain performance indicators associated with services. A possible solution to evaluate instantaneously the QoE is to integrate QoE analysers in the mobile terminal itself [2]. If mobile terminals are able to report the measurements to a central server, the
QoE assessment process is simplified significantly. Other solutions are focused on including new network elements (e.g., network analysers, deep packet inspectors, etc.) that are responsible for capturing the traffic from a certain service and analysing its performance [3]. For instance, the work presented in [4] investigates the ...
CHARACTERIZATION OF USER-PERCEIVED QUALITY OF SERVICE (QOS) IN MOBILE DEVICES...ijwmn
This paper presents a user-centric and application-specific QoS assessment methodology for cellular
communication networks. Specifically, it uses the Analytic Hierarchy Process (AHP) to evaluate QoS as a
multi-criteria decision problem that represents how well cellular networks’ data services are perceived
given particular sets of application classes and relative to other networks servicing in the same area. As
part of the methodology, drive testing is performed to collect objective measurements associated with
identified QoS criteria for data services. Once drive testing is performed and data collected, multiple
networks are compared to determine the network that provides higher QoS based on users’ perception of
quality. The selection of the best performing network is based on the output provided by the AHP
approach, which is used as unified measurement of the perceived QoS by users on different networks. In
order to determine application-specific priorities, the approach presented uses three different application
classes, including Emergency, Business, and Personal. For each class, the relative importance of each
quality evaluation criteria is adjusted in the AHP procedure to reflect the priorities of the services
expected. Through several case studies, the approach is proven successful in providing a way for
analyzing user-centric QoS for application-specific scenarios.
Correlating objective factors with videoIJCNCJournal
To succeed in providing services, the quality of services should meet users’ satisfaction. This is a motivation to study the relationship between the service quality and the real perceived quality of users, which is commonly referred to as the quality of experience (QoE). However, most of existing QoE studies that focus on video-on-demand or IPTV services analyze only the influence of network behaviors to video quality. This paper focuses on P2P video streaming services, which are becoming a significant portion of Internet traffic, and pays attention to the change of users’ perception with the adjustment of objective
factors as well as network behaviors. We propose to use mean opinion score and peak signal to noise ratio
methods as QoE evaluations to consider the effect of the chunk loss ratio, the group-of-picture size, and the
chunk size. The experimental results provide a convincing reference to build the complete relationship
between objective factors and QoE. We believe that this assessment will contribute to study a new service
quality evaluation mechanism based on users’ satisfaction in the future.
Recently with the increasing development of distributed computer systems (DCSs) in networked
industrial and manufacturing applications on the World Wide Web (WWW) platform, including service-oriented
architecture and Web of Things QoS-aware systems, it has become important to predict the Web performance.
In this paper, we present Web performance prediction in time by making a forecast of a Web resource
downloading using the Efficient Turning Bands (TB) geostatistical simulation method. Real-life data for the
research were obtained from our own website named "Distributed forecasting system". Generation of log file
form website and performing monitoring of a group of Web clients from connected LAN. For better web
prediction we used spatio temporal prediction method with time utility for downloading particular file from
website and calculate forecasting result using Turning bands method but improving more forecasting
accuracy use the efficient turning band method basically efficient turning band use Naive bays algorithm and
calculate efficient result and that result is compared with Turning band and efficient turning band method.
The efficient turning band method result show good forecasting quality of Web performance prediction and
forecasting.
SURVEY ON QOE\QOS CORRELATION MODELS FORMULTIMEDIA SERVICESijdpsjournal
This paper presents a brief review of some existing correlation models which attempt to map Quality of
Service (QoS) to Quality of Experience (QoE) for multimedia services. The term QoS refers to deterministic
network behaviour, so that data can be transported with a minimum of packet loss, delay and maximum
bandwidth. QoE is a subjective measure that involves human dimensions; it ties together user perception,
expectations, and experience of the application and network performance. The Holy Grail of subjective
measurement is to predict it from the objective measurements; in other words predict QoE from a given set
of QoS parameters or vice versa. Whilst there are many quality models for multimedia, most of them are
only partial solutions to predicting QoE from a given QoS. This contribution analyses a number of previous
attempts and optimisation techniquesthat can reliably compute the weighting coefficients for the QoS/QoE
mapping.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Digital supply chain quality managementMartin Geddes
We've figured out how to send physical goods around the world: aggregate them into containers. We're still struggling how to do digital good, which we disaggregate into packets. Here's the answer.
Collaborative Filtering Approach For QoS PredictionEditor IJMTER
Many researchers propose that, not only functional but also non-functional properties, also
known as quality of service (QoS), should be taken into consideration when consumers select
services. Consumers need to make prediction on quality of unused web services before selecting.
Usually, this prediction is based on other consumers’ experiences. Being aware of different QoS
experiences of consumers, this paper proposes a collaborative filtering based approach to making
similarity mining and prediction from consumers’ experiences. Experimental results demonstrate that
this approach can make significant improvement on the effectiveness of QoS prediction for web
services.
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy ...redpel dot com
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy Neural Networks for Cloud Services
for more ieee paper / full abstract / implementation , just visit www.redpel.com
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their
functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services. In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
In this paper, an application-based QoS evaluation approach for heterogeneous networks is proposed.It is possible to expand the network capacity and coverage in a dynamic fashion by applying heterogeneous wireless network architecture. However, the Quality of Service (QoS) evaluation of this type of network architecture is very challenging due to the presence of different communication technologies. Different communication technologies have different characteristics and the applications that utilize them have unique QoS requirements. Although, the communication technologies have different performance measurement parameters, the applications using these radio access networks have the same QoS requirements. As a result, it would be easier to evaluate the QoS of the access networks and the overall network configuration based on the performance of applications running on them. Using such applicationbased QoS evaluation approach, the heterogeneous nature of the underlying networks and the diversity of their traffic can be adequately taken into account. Through simulation studies, we show that the application performance based assessment approach facilitates better QoS management and monitoring of heterogeneous network configurations.
ANALYTIC HIERARCHY PROCESS FOR QOS EVALUATION OF MOBILE DATA NETWORKSIJCNCJournal
The widespread demand for data applications over mobile networks requires that service providers guarantee a well-defined quality of service (QoS) for subscribers. Evaluating the QoS provided by service providers within a geographical area to determine which network provides the best QoS is a challenging task. The complex nature of mobile networks with multi-criteria and conflicting factors makes good decision making difficult. This paper presents a measurement-based method called Analytic Hierarchy Process (AHP) for evaluating QoS in application-specific and user-centric data on 3G mobile networks. The evaluation problem is formulated as a multi-criteria decision problem. Latency, jitter, data loss, and throughput are the parameters collected as criteria in drive testing over the mobile network. Decision matrix is applied to solve the problem by reaching a final ranking of the network based on the collected measured values of the problem parameters. A case study of 3G mobile networks in Uyo metropolis is used to show how this approach can be effective in ranking the QoS in data applications to determine which network provides the best QoS based on users’ perception of quality. The implemented results in Java indicate that Etisalat network is the alternative that offers the best QoS for web browsing application based on measured criteria. This is followed by Airtel and then MTN, while Glo is ranked least. The result provides useful information to decision makers for performance improvement on service quality.
Recently with the increasing development of distributed computer systems (DCSs) in networked
industrial and manufacturing applications on the World Wide Web (WWW) platform, including service-oriented
architecture and Web of Things QoS-aware systems, it has become important to predict the Web performance.
In this paper, we present Web performance prediction in time by making a forecast of a Web resource
downloading using the Efficient Turning Bands (TB) geostatistical simulation method. Real-life data for the
research were obtained from our own website named "Distributed forecasting system". Generation of log file
form website and performing monitoring of a group of Web clients from connected LAN. For better web
prediction we used spatio temporal prediction method with time utility for downloading particular file from
website and calculate forecasting result using Turning bands method but improving more forecasting
accuracy use the efficient turning band method basically efficient turning band use Naive bays algorithm and
calculate efficient result and that result is compared with Turning band and efficient turning band method.
The efficient turning band method result show good forecasting quality of Web performance prediction and
forecasting.
SURVEY ON QOE\QOS CORRELATION MODELS FORMULTIMEDIA SERVICESijdpsjournal
This paper presents a brief review of some existing correlation models which attempt to map Quality of
Service (QoS) to Quality of Experience (QoE) for multimedia services. The term QoS refers to deterministic
network behaviour, so that data can be transported with a minimum of packet loss, delay and maximum
bandwidth. QoE is a subjective measure that involves human dimensions; it ties together user perception,
expectations, and experience of the application and network performance. The Holy Grail of subjective
measurement is to predict it from the objective measurements; in other words predict QoE from a given set
of QoS parameters or vice versa. Whilst there are many quality models for multimedia, most of them are
only partial solutions to predicting QoE from a given QoS. This contribution analyses a number of previous
attempts and optimisation techniquesthat can reliably compute the weighting coefficients for the QoS/QoE
mapping.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Digital supply chain quality managementMartin Geddes
We've figured out how to send physical goods around the world: aggregate them into containers. We're still struggling how to do digital good, which we disaggregate into packets. Here's the answer.
Collaborative Filtering Approach For QoS PredictionEditor IJMTER
Many researchers propose that, not only functional but also non-functional properties, also
known as quality of service (QoS), should be taken into consideration when consumers select
services. Consumers need to make prediction on quality of unused web services before selecting.
Usually, this prediction is based on other consumers’ experiences. Being aware of different QoS
experiences of consumers, this paper proposes a collaborative filtering based approach to making
similarity mining and prediction from consumers’ experiences. Experimental results demonstrate that
this approach can make significant improvement on the effectiveness of QoS prediction for web
services.
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy ...redpel dot com
Web Service QoS Prediction Based on Adaptive Dynamic Programming Using Fuzzy Neural Networks for Cloud Services
for more ieee paper / full abstract / implementation , just visit www.redpel.com
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their
functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services.
In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
WEB SERVICE SELECTION BASED ON RANKING OF QOS USING ASSOCIATIVE CLASSIFICATIONijwscjournal
With the explosive growth of the number of services published over the Internet, it is difficult to select satisfactory web services among the candidate web services which provide similar functionalities. Quality of Service (QoS) is considered as the most important non-functional criterion for service selection. But this criterion is no longer considered as the only criterion to rank web services, satisfying user’s preferences. The similarity measure (outputs–inputs similarity) between concepts based on ontology in an interconnected network of semantic Web services involved in a composition can be used as a distinguishing criterion to estimate the semantic quality of selected services for the composite service. Coupling the
semantic similarity as the functional aspect and quality of services allows us to further constrain and select services for the valid composite services. In this paper, we present an overall service selection and ranking framework which firstly classify candidate web services to different QoS levels respect to user’s QoS requirements and preferences with an Associative Classification algorithm and then rank the most qualified candidate services based on their functional quality through semantic matching. The experimental results show that proposed framework can satisfy service requesters’ non-functional requirements.
In this paper, an application-based QoS evaluation approach for heterogeneous networks is proposed.It is possible to expand the network capacity and coverage in a dynamic fashion by applying heterogeneous wireless network architecture. However, the Quality of Service (QoS) evaluation of this type of network architecture is very challenging due to the presence of different communication technologies. Different communication technologies have different characteristics and the applications that utilize them have unique QoS requirements. Although, the communication technologies have different performance measurement parameters, the applications using these radio access networks have the same QoS requirements. As a result, it would be easier to evaluate the QoS of the access networks and the overall network configuration based on the performance of applications running on them. Using such applicationbased QoS evaluation approach, the heterogeneous nature of the underlying networks and the diversity of their traffic can be adequately taken into account. Through simulation studies, we show that the application performance based assessment approach facilitates better QoS management and monitoring of heterogeneous network configurations.
ANALYTIC HIERARCHY PROCESS FOR QOS EVALUATION OF MOBILE DATA NETWORKSIJCNCJournal
The widespread demand for data applications over mobile networks requires that service providers guarantee a well-defined quality of service (QoS) for subscribers. Evaluating the QoS provided by service providers within a geographical area to determine which network provides the best QoS is a challenging task. The complex nature of mobile networks with multi-criteria and conflicting factors makes good decision making difficult. This paper presents a measurement-based method called Analytic Hierarchy Process (AHP) for evaluating QoS in application-specific and user-centric data on 3G mobile networks. The evaluation problem is formulated as a multi-criteria decision problem. Latency, jitter, data loss, and throughput are the parameters collected as criteria in drive testing over the mobile network. Decision matrix is applied to solve the problem by reaching a final ranking of the network based on the collected measured values of the problem parameters. A case study of 3G mobile networks in Uyo metropolis is used to show how this approach can be effective in ranking the QoS in data applications to determine which network provides the best QoS based on users’ perception of quality. The implemented results in Java indicate that Etisalat network is the alternative that offers the best QoS for web browsing application based on measured criteria. This is followed by Airtel and then MTN, while Glo is ranked least. The result provides useful information to decision makers for performance improvement on service quality.
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Ensuring predictable contact opportunity for scalable vehicular internet acce...ieeeprojectschennai
Ensuring predictable contact opportunity for scalable vehicular internet access on the go
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www.projectsieee.com, www.ieee-projects-chennai.com
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Utilize signal traces from others a crowdsourcing perspective of energy savin...ieeeprojectschennai
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Swimming seamless and efficient wi fi based internet access from moving vehiclesieeeprojectschennai
Swimming seamless and efficient wi fi based internet access from moving vehicles
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IEEE PROJECTS 2015-2016
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Impact of location popularity on throughput and delay in mobile ad hoc networksieeeprojectschennai
Impact of location popularity on throughput and delay in mobile ad hoc networks
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IEEE PROJECTS 2015-2016
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How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
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Context aware qo e modelling, measurement, and prediction in mobile computing systems
1. Context-Aware QoE Modelling, Measurement and Prediction in Mobile
Computing Systems
Abstract:
Quality of Experience (QoE) as an aggregate of Quality of Service (QoS)
and human user-related metrics will be the key success factor for current
and future mobile computing systems. QoE measurement and prediction
are complex tasks as they may involve a large parameter space such as
location, delay, jitter, packet loss and user satisfaction just to name a few.
These tasks necessitate the development of practical context-aware QoE
models that efficiently determine relationships between user context and
QoE parameters. In this paper, we propose, develop and validate a novel
decision-theoretic approach called CaQoEM for QoE modelling,
measurement and prediction. We address the challenge of QoE
measurement and prediction where each QoE parameter can be measured
on a different scale and may involve different units of measurement.
CaQoEM is context-aware and uses Bayesian networks and utility theory to
measure and predict users’ QoE under uncertainty. We validate CaQoEM
using extensive experimentation, user studies and simulations. The results
soundly demonstrate that CaQoEM correctly measures range-defined QoE
using a bipolar scale. For QoE prediction, an overall accuracy of 98.93%
was achieved using 10-fold cross validation in multiple diverse network
2. conditions such as vertical handoffs, wireless signal fading and wireless
network congestion.
Existing System:
We argue that QoE is a broader construct which encompasses QoS
parameters along with user related factors such as their behavioural,
cognitive and psychological states along with the context in which these
products and services are provided to them.
These factors determine their overall QoE related to a particular application
or service. In mobile computing environments, users’ behaviour is dynamic
as they use applications or services in different scenarios. Thus, for QoE
measurement and prediction, it is important to consider parameters related
to users, their device(s) and environment along with network QoS.
Proposed System:
We propose, develop and validate a context-aware method for QoE
modeling based on context spaces model (CSM) and Bayesian networks.
Our method considers several context attributes and QoE parameters. It
provides a simple and efficient way to determine relationships between
these attributes as well as parameters to measure and predict users’ QoE.
We propose, develop and validate a context-aware, decision-theoretic
method for QoE measurement and prediction under uncertainty on a
3. single scale. We validate CaQoEM using a number of case studies. We
developed a prototype and performed a number of subjective tests.
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• RAM : 256 Mb.
Software Requirements:
• Operating system : - Windows XP.
• Front End : - JSP
• Back End : - SQL Server
Software Requirements:
• Operating system : - Windows XP.
• Front End : - .Net
• Back End : - SQL Server
