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.
IoT traffic management and integration in the QoS supported networkBASIM AL-SHAMMARI
This paper proposes: 1) a traffic flow management
policy, which allocates and organizes machine type communication
(MTC) traffic flows network resources sharing within evolved
packet system (EPS); 2) an access element as a wireless sensor
network gateway for providing an overlaying access channel
between the machine type devices and EPS; and 3) it addresses
the effect and interaction in the heterogeneity of applications,
services and terminal devices, and the related quality of service
(QoS) issues among them. This paper overcomes the problems
of network resource starvation by preventing deterioration of
network performance. The scheme is validated through simulation,
which indicates the proposed traffic flow management policy
outperforms the current traffic management policy. Specifically,
simulation results show that the proposed model achieves an
enhancement in QoS performance for the MTC traffic flows,
including a decrease of 99.45% in packet loss rate (PLR), a
decrease of 99.89% in packet end to end (E2E) delay, a decrease
of 99.21% in packet delay variation (PDV). Furthermore, it
retains the perceived quality of experience of the real time application
users within high satisfaction levels, such as the voice
over long term evolution service possessing a mean opinion
score (MOS) of 4.349 and enhancing the QoS of a video conference
service within the standardized values of a 3GPP body,
with a decrease of 85.28% in PLR, a decrease of 85% in packet
E2E delay and a decrease of 88.5% in PDV.
Index Terms—Application quality of service (AQoS), end to
end (E2E) delay, gateway, human type communication (HTC),
Internet of Things (IoT), jitter, machine type communication
(MTC), network QoS (NQoS), quality of experience (QoE), QoS
class identifier (QCI), traffic policy.
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5Gijwmn
Machine to Machine communication or M2M, refers to a model of communication where devices communicate directly with each other using the available wired or wireless channels. M2M is a new concept proposed under 3GPP(3rd Generation Partnership Project); several research are working on providing solutions for M2M communication for the 5G networks. Challenges associated with M2M communication are the lack of standards, security, poor infrastructure, interoperability and diverse architecture. In this paper, we propose a new mechanism called TM2M5G (The Machine to Machine for 5G) based on SOFTNET platform which results in support of 5G heterogeneous network. In this paper, we
propose the architecture for M2M communication based on SOFTNET and provide new features support like security algorithms for data transmission among devices and scheduling algorithm for seamless transmission of data packets over the network. Finallysimulation results ofthis algorithm based on a system level simulator, considering two different approaches for analyzing the parameters such as delay, throughput and bandwidth are presented.
Efficient P2P data dissemination in integrated optical and wireless networks ...TELKOMNIKA JOURNAL
The Quality of Service (QoS) resource consumption is always the tricky problem and also
the on-going issue in the access network of mobile wireless part because of its dynamic nature of network
wireless transmissions. It is very critical for the infrastructure-less wireless mobile ad hoc network that is
distributed while interconnects in a peer-to-peer manner. Toward resolve the problem, Taguchi method
optimization of mobile ad hoc routing (AODVUU) is applied in integrated optical and wireless networks
called the adLMMHOWAN. Practically, this technique was carry out using OMNeT++ software by building
a simulation based optimization through design of experiment. Its QoS network performance is examined
based on packet delivery ratio (PDR) metric and packet loss probabilities (PLP) metric that consider
the scenario of variation number of nodes. During the performing stage with random mobile connectivity
based on improvement in optimized front-end wireless domain of AODVUU routing, the result is performing
better when compared with previous study called the oRia scheme with the improvement of 14.1% PDR
and 43.3% PLP in this convergence of heterogeneous optical wireless network.
Application-Based QoS Evaluation of Heterogeneous Networks csandit
Heterogeneous wireless networks expand the network capacity and coverage by leveraging the
network architecture and resources in a dynamic fashion. However, the presence of different
communication technologies makes the Quality of Service (QoS) evaluation, management, and
monitoring of these networks very challenging. Each communication technology has its own
characteristics while the applications that utilize them have their specific QoS requirements.
Although, the communication technologies have different performance assessment 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 depending on the performance of applications running on them. Using such
application-based QoS evaluation approach, the heterogeneous nature of the underlying
networks and the diversity of their traffic can be adequately taken into account. In this paper,
we propose an application-based QoS evaluation approach for heterogeneous networks.
Through simulation studies, we show that this assessment approach facilitates better QoS
management and monitoring of heterogeneous network configurations.
IoT traffic management and integration in the QoS supported networkBASIM AL-SHAMMARI
This paper proposes: 1) a traffic flow management
policy, which allocates and organizes machine type communication
(MTC) traffic flows network resources sharing within evolved
packet system (EPS); 2) an access element as a wireless sensor
network gateway for providing an overlaying access channel
between the machine type devices and EPS; and 3) it addresses
the effect and interaction in the heterogeneity of applications,
services and terminal devices, and the related quality of service
(QoS) issues among them. This paper overcomes the problems
of network resource starvation by preventing deterioration of
network performance. The scheme is validated through simulation,
which indicates the proposed traffic flow management policy
outperforms the current traffic management policy. Specifically,
simulation results show that the proposed model achieves an
enhancement in QoS performance for the MTC traffic flows,
including a decrease of 99.45% in packet loss rate (PLR), a
decrease of 99.89% in packet end to end (E2E) delay, a decrease
of 99.21% in packet delay variation (PDV). Furthermore, it
retains the perceived quality of experience of the real time application
users within high satisfaction levels, such as the voice
over long term evolution service possessing a mean opinion
score (MOS) of 4.349 and enhancing the QoS of a video conference
service within the standardized values of a 3GPP body,
with a decrease of 85.28% in PLR, a decrease of 85% in packet
E2E delay and a decrease of 88.5% in PDV.
Index Terms—Application quality of service (AQoS), end to
end (E2E) delay, gateway, human type communication (HTC),
Internet of Things (IoT), jitter, machine type communication
(MTC), network QoS (NQoS), quality of experience (QoE), QoS
class identifier (QCI), traffic policy.
NEW TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION IN SOFTNET TOWARDS 5Gijwmn
Machine to Machine communication or M2M, refers to a model of communication where devices communicate directly with each other using the available wired or wireless channels. M2M is a new concept proposed under 3GPP(3rd Generation Partnership Project); several research are working on providing solutions for M2M communication for the 5G networks. Challenges associated with M2M communication are the lack of standards, security, poor infrastructure, interoperability and diverse architecture. In this paper, we propose a new mechanism called TM2M5G (The Machine to Machine for 5G) based on SOFTNET platform which results in support of 5G heterogeneous network. In this paper, we
propose the architecture for M2M communication based on SOFTNET and provide new features support like security algorithms for data transmission among devices and scheduling algorithm for seamless transmission of data packets over the network. Finallysimulation results ofthis algorithm based on a system level simulator, considering two different approaches for analyzing the parameters such as delay, throughput and bandwidth are presented.
Efficient P2P data dissemination in integrated optical and wireless networks ...TELKOMNIKA JOURNAL
The Quality of Service (QoS) resource consumption is always the tricky problem and also
the on-going issue in the access network of mobile wireless part because of its dynamic nature of network
wireless transmissions. It is very critical for the infrastructure-less wireless mobile ad hoc network that is
distributed while interconnects in a peer-to-peer manner. Toward resolve the problem, Taguchi method
optimization of mobile ad hoc routing (AODVUU) is applied in integrated optical and wireless networks
called the adLMMHOWAN. Practically, this technique was carry out using OMNeT++ software by building
a simulation based optimization through design of experiment. Its QoS network performance is examined
based on packet delivery ratio (PDR) metric and packet loss probabilities (PLP) metric that consider
the scenario of variation number of nodes. During the performing stage with random mobile connectivity
based on improvement in optimized front-end wireless domain of AODVUU routing, the result is performing
better when compared with previous study called the oRia scheme with the improvement of 14.1% PDR
and 43.3% PLP in this convergence of heterogeneous optical wireless network.
Application-Based QoS Evaluation of Heterogeneous Networks csandit
Heterogeneous wireless networks expand the network capacity and coverage by leveraging the
network architecture and resources in a dynamic fashion. However, the presence of different
communication technologies makes the Quality of Service (QoS) evaluation, management, and
monitoring of these networks very challenging. Each communication technology has its own
characteristics while the applications that utilize them have their specific QoS requirements.
Although, the communication technologies have different performance assessment 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 depending on the performance of applications running on them. Using such
application-based QoS evaluation approach, the heterogeneous nature of the underlying
networks and the diversity of their traffic can be adequately taken into account. In this paper,
we propose an application-based QoS evaluation approach for heterogeneous networks.
Through simulation studies, we show that this assessment approach facilitates better QoS
management and monitoring of heterogeneous network configurations.
A Review on Traffic Classification Methods in WSNIJARIIT
In a wireless network it is very important to provide the network security and quality of service. To achieve these parameters there must be proper traffic classification in the wireless network. There are many algorithms used such as port number, deep packet inspection as the earlier methods and now days KISS, nearest cluster based classifier (NCC), SVM method and used to classify the traffic and improve the network security and quality of service of a network.
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.
33 9140 it immensely discriminate routing in wireless (edit lafi)IAESIJEECS
Wireless networks are predictable to grant essential Internet access multimedia traffic service
also increasingly such networks have been emerged in real life. However, the application scenarios is
indeterminate as well as largely scalable routing is very difficult. Thus require efficient routing schemes in
wireless network. In this paper, we propose Immensely Discriminate Routing protocol is used for multihop
routing in wireless network. Here, node distance, node link, node trust and node quality of service is
evaluated the next hop. This parameters are determined an efficient path in the wireless network.
Performance Prediction of 5G : The Next Generation of Mobile Communication ijngnjournal
The 5G standard is a mobile communication of the 5th generation, which presupposes an increase of the
information exchange speed up to 10 Gbit/s. It is 30 times quicker than the speed of 4G network. It is a new
stage in the development of technologies connecting society. This standard will provide an unlimited access
to the network for individual users and devices. When developing the 5G standard, the advanced
opportunities of LTE and HSPA, as well as other technologies of a radio access focused on the solution of
specific objectives are considered. The main advantage of the mass introduction of the 5G communication
development represents the so-called Internet of Things (IoT). There the devices and not people will be the
main consumers of traffic. The functional requirements of5G networks, their speed, and its traffic
parameters for HD video services and massifs of M2M-devices are analyzed in the paper. They will have
been the most demandedones by 2020.
A survey on Stack Path Identification and Encryption Adopted as Spoofing Defe...IOSR Journals
Abstract: Spoofing attacks are a constant nag in the information world, so many methodologies have been
invented to reduce on its effects but still there is a lot left to be desired. The kind of impact that this attacks have
on Electronic Payment Systems is so detrimental to the economic world given that this systems are viewed as
performance enhancers on payments. This study elaborates two methodologies a combination of StackPi and
Encryption as spoofing defense methodologies. Billions of shillings are lost in this rollercoaster thus giving rise
to a situation that deserves undivided attention and should be researched on. A profound argument on the
methodologies that have been used in this mission to eradicate spoofing attacks, the limitations that they posses
and other methodologies that have been brought in play to succeed them elicits an interesting he strategy of
integrating or combining methodologies and the benefits that this strategy contributes to curbing spoofing
attacks. With that knowledge underhand, it can be justified why the combination of Stack Pi and Encryption is a
recommended solution against spoofing attacks.
Keywords: Electronic Payment Systems, Encryption, Security, Spoofing attacks, Stack Pi
Dynamic resource allocation for opportunistic software-defined IoT networks: s...IJECEIAES
Several wireless technologies have recently emerged to enable efficient and scalable Internet-of-Things (IoT) networking. Cognitive radio (CR) technology, enabled by software-defined radios, is considered one of the main IoT-enabling technologies that can provide opportunistic wireless access to a large number of connected IoT devices. An important challenge in this domain is how to dynamically enable IoT transmissions while achieving efficient spectrum usage with a minimum total power consumption under interference and traffic demand uncertainty. Toward this end, we propose a dynamic bandwidth/channel/power allocation algorithm that aims at maximizing the overall network’s throughput while selecting the set of power resulting in the minimum total transmission power. This problem can be formulated as a two-stage binary linear stochastic programming. Because the interference over different channels is a continuous random variable and noting that the interference statistics are highly correlated, a suboptimal sampling solution is proposed. Our proposed algorithm is an adaptive algorithm that is to be periodically conducted over time to consider the changes of the channel and interference conditions. Numerical results indicate that our proposed algorithm significantly increases the number of simultaneous IoT transmissions compared to a typical algorithm, and hence, the achieved throughput is improved.
A Trust-Based Predictive Model for Mobile Ad Hoc Networkspijans
The Internet of things (IoT) is a heterogeneous network of different types of wireless networks such as wireless sensor networks (WSNs), ZigBee, Wi-Fi, mobile ad hoc networks (MANETs), and RFID. To make IoT a reality for smart environment, more attractive to end users, and economically successful, it must be compatible with WSNs and MANETs. In light of this, the present paper discusses a novel quantitative trust model for an IoT-MANET. The proposed trust model combines both direct and indirect trust opinion in order to calculate the final trust value for a node. Further, a routing protocol has been designed to ensure the secure and reliable end-to-end delivery of packets by only considering trustworthy nodes in the path. Simulation results show that our proposed trust model outperforms similar existing trust models.
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Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network iosrjce
Network congestion is one of the major problems of GSM service providers as the number of
subscribers increase and new services are introduced. All the proposed techniques in literatures for controlling
congestion are centered on two principles which are either to reject excessive traffic to prevent over-utilization
of network resources or diverting excess load if overload occurs. These techniques do not specify how network
resource can be provided to absorb rejected or diverted traffic so that revenue will not be lost during congestion
and hence, they do not really address congestion during busy hour. Real-time traffic analysis is required to
understand user traffic demand pattern on network resources for proper prediction of network congestion so
that resources can be provided to take care of rejected or diverted traffic. However, available literature survey
on mobile network congestion modeling showed that none of the existing literature: address congestion at the
three basic elements of GSM network to characterize end-to-end connection; use busy hour traffic data to
adequately dimension GSM network elements so that the network can cope with load B. Therefore, effective
congestion control mechanism that can take these research gaps into consideration for proper forecasting and
efficient dimension of the network resources to address busy hour congestion must be developed. This paper is a
preliminary report on development of such accurate congestion prediction model through an ongoing research
work using real live network data from one of the Service provider’s networks in Abuja, Nigeria as a case study
APPLICATION-BASED QOS EVALUATION OF HETEROGENEOUS NETWORKS cscpconf
Heterogeneous wireless networks expand the network capacity and coverage by leveraging the network architecture and resources in a dynamic fashion. However, the presence of different communication technologies makes the Quality of Service (QoS) evaluation, management, and monitoring of these networks very challenging. Each communication technology has its own characteristics while the applications that utilize them have their specific QoS requirements. Although, the communication technologies have different performance assessment 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 depending on the performance of applications running on them. Using such application-based QoS evaluation approach, the heterogeneous nature of the underlying networks and the diversity of their traffic can be adequately taken into account. In this paper, we propose an application-based QoS evaluation approach for heterogeneous networks. Through simulation studies, we show that this 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.
Enhancing qo s and qoe in ims enabled next generation networksgraphhoc
Managing network complexity, accommodating greater numbers of subscribers, improving coverage to support data services (e.g. email, video, and music downloads), keeping up to speed with fast-changing technology, and driving maximum value from existing networks – all while reducing CapEX and OpEX and ensuring Quality of Service (QoS) for the network and Quality of Experience (QoE) for the user. These are just some of the pressing business issues faced by mobileservice providers, summarized by the demand to “achieve more, for less.” The ultimate goal of optimization techniques at the network and application layer is to ensure End-user perceived QoS. The next generation networks (NGN), a composite environment of proven telecommunications and Internet-oriented mechanisms have become generally recognized as the telecommunications environment of the future. However, the nature of the NGN environment presents several complex issues regarding quality assurance that have not existed in the legacy environments (e.g., multi-network, multi-vendor, and multi-operator IP-based telecommunications environment, distributed intelligence, third-party provisioning, fixed-wireless and mobile access, etc.). In this Research Paper, a service aware policy-based approach to NGN quality assurance is presented, taking into account both perceptual quality of experience and technologydependant quality of service issues. The respective procedures, entities, mechanisms, and profiles are discussed. The purpose of the presented approach is in research, development, and discussion of pursuing the end-to-end controllability of the quality of the multimedia NGN-based communications in an environment that is best effort in its nature and promotes end user’s access agnosticism, service agility, and global mobility
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 ...
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.
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.
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.
A Review on Traffic Classification Methods in WSNIJARIIT
In a wireless network it is very important to provide the network security and quality of service. To achieve these parameters there must be proper traffic classification in the wireless network. There are many algorithms used such as port number, deep packet inspection as the earlier methods and now days KISS, nearest cluster based classifier (NCC), SVM method and used to classify the traffic and improve the network security and quality of service of a network.
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.
33 9140 it immensely discriminate routing in wireless (edit lafi)IAESIJEECS
Wireless networks are predictable to grant essential Internet access multimedia traffic service
also increasingly such networks have been emerged in real life. However, the application scenarios is
indeterminate as well as largely scalable routing is very difficult. Thus require efficient routing schemes in
wireless network. In this paper, we propose Immensely Discriminate Routing protocol is used for multihop
routing in wireless network. Here, node distance, node link, node trust and node quality of service is
evaluated the next hop. This parameters are determined an efficient path in the wireless network.
Performance Prediction of 5G : The Next Generation of Mobile Communication ijngnjournal
The 5G standard is a mobile communication of the 5th generation, which presupposes an increase of the
information exchange speed up to 10 Gbit/s. It is 30 times quicker than the speed of 4G network. It is a new
stage in the development of technologies connecting society. This standard will provide an unlimited access
to the network for individual users and devices. When developing the 5G standard, the advanced
opportunities of LTE and HSPA, as well as other technologies of a radio access focused on the solution of
specific objectives are considered. The main advantage of the mass introduction of the 5G communication
development represents the so-called Internet of Things (IoT). There the devices and not people will be the
main consumers of traffic. The functional requirements of5G networks, their speed, and its traffic
parameters for HD video services and massifs of M2M-devices are analyzed in the paper. They will have
been the most demandedones by 2020.
A survey on Stack Path Identification and Encryption Adopted as Spoofing Defe...IOSR Journals
Abstract: Spoofing attacks are a constant nag in the information world, so many methodologies have been
invented to reduce on its effects but still there is a lot left to be desired. The kind of impact that this attacks have
on Electronic Payment Systems is so detrimental to the economic world given that this systems are viewed as
performance enhancers on payments. This study elaborates two methodologies a combination of StackPi and
Encryption as spoofing defense methodologies. Billions of shillings are lost in this rollercoaster thus giving rise
to a situation that deserves undivided attention and should be researched on. A profound argument on the
methodologies that have been used in this mission to eradicate spoofing attacks, the limitations that they posses
and other methodologies that have been brought in play to succeed them elicits an interesting he strategy of
integrating or combining methodologies and the benefits that this strategy contributes to curbing spoofing
attacks. With that knowledge underhand, it can be justified why the combination of Stack Pi and Encryption is a
recommended solution against spoofing attacks.
Keywords: Electronic Payment Systems, Encryption, Security, Spoofing attacks, Stack Pi
Dynamic resource allocation for opportunistic software-defined IoT networks: s...IJECEIAES
Several wireless technologies have recently emerged to enable efficient and scalable Internet-of-Things (IoT) networking. Cognitive radio (CR) technology, enabled by software-defined radios, is considered one of the main IoT-enabling technologies that can provide opportunistic wireless access to a large number of connected IoT devices. An important challenge in this domain is how to dynamically enable IoT transmissions while achieving efficient spectrum usage with a minimum total power consumption under interference and traffic demand uncertainty. Toward this end, we propose a dynamic bandwidth/channel/power allocation algorithm that aims at maximizing the overall network’s throughput while selecting the set of power resulting in the minimum total transmission power. This problem can be formulated as a two-stage binary linear stochastic programming. Because the interference over different channels is a continuous random variable and noting that the interference statistics are highly correlated, a suboptimal sampling solution is proposed. Our proposed algorithm is an adaptive algorithm that is to be periodically conducted over time to consider the changes of the channel and interference conditions. Numerical results indicate that our proposed algorithm significantly increases the number of simultaneous IoT transmissions compared to a typical algorithm, and hence, the achieved throughput is improved.
A Trust-Based Predictive Model for Mobile Ad Hoc Networkspijans
The Internet of things (IoT) is a heterogeneous network of different types of wireless networks such as wireless sensor networks (WSNs), ZigBee, Wi-Fi, mobile ad hoc networks (MANETs), and RFID. To make IoT a reality for smart environment, more attractive to end users, and economically successful, it must be compatible with WSNs and MANETs. In light of this, the present paper discusses a novel quantitative trust model for an IoT-MANET. The proposed trust model combines both direct and indirect trust opinion in order to calculate the final trust value for a node. Further, a routing protocol has been designed to ensure the secure and reliable end-to-end delivery of packets by only considering trustworthy nodes in the path. Simulation results show that our proposed trust model outperforms similar existing trust models.
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Litrature Survey of Traffic Analysis and Congestion Modeling In Mobile Network iosrjce
Network congestion is one of the major problems of GSM service providers as the number of
subscribers increase and new services are introduced. All the proposed techniques in literatures for controlling
congestion are centered on two principles which are either to reject excessive traffic to prevent over-utilization
of network resources or diverting excess load if overload occurs. These techniques do not specify how network
resource can be provided to absorb rejected or diverted traffic so that revenue will not be lost during congestion
and hence, they do not really address congestion during busy hour. Real-time traffic analysis is required to
understand user traffic demand pattern on network resources for proper prediction of network congestion so
that resources can be provided to take care of rejected or diverted traffic. However, available literature survey
on mobile network congestion modeling showed that none of the existing literature: address congestion at the
three basic elements of GSM network to characterize end-to-end connection; use busy hour traffic data to
adequately dimension GSM network elements so that the network can cope with load B. Therefore, effective
congestion control mechanism that can take these research gaps into consideration for proper forecasting and
efficient dimension of the network resources to address busy hour congestion must be developed. This paper is a
preliminary report on development of such accurate congestion prediction model through an ongoing research
work using real live network data from one of the Service provider’s networks in Abuja, Nigeria as a case study
APPLICATION-BASED QOS EVALUATION OF HETEROGENEOUS NETWORKS cscpconf
Heterogeneous wireless networks expand the network capacity and coverage by leveraging the network architecture and resources in a dynamic fashion. However, the presence of different communication technologies makes the Quality of Service (QoS) evaluation, management, and monitoring of these networks very challenging. Each communication technology has its own characteristics while the applications that utilize them have their specific QoS requirements. Although, the communication technologies have different performance assessment 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 depending on the performance of applications running on them. Using such application-based QoS evaluation approach, the heterogeneous nature of the underlying networks and the diversity of their traffic can be adequately taken into account. In this paper, we propose an application-based QoS evaluation approach for heterogeneous networks. Through simulation studies, we show that this 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.
Enhancing qo s and qoe in ims enabled next generation networksgraphhoc
Managing network complexity, accommodating greater numbers of subscribers, improving coverage to support data services (e.g. email, video, and music downloads), keeping up to speed with fast-changing technology, and driving maximum value from existing networks – all while reducing CapEX and OpEX and ensuring Quality of Service (QoS) for the network and Quality of Experience (QoE) for the user. These are just some of the pressing business issues faced by mobileservice providers, summarized by the demand to “achieve more, for less.” The ultimate goal of optimization techniques at the network and application layer is to ensure End-user perceived QoS. The next generation networks (NGN), a composite environment of proven telecommunications and Internet-oriented mechanisms have become generally recognized as the telecommunications environment of the future. However, the nature of the NGN environment presents several complex issues regarding quality assurance that have not existed in the legacy environments (e.g., multi-network, multi-vendor, and multi-operator IP-based telecommunications environment, distributed intelligence, third-party provisioning, fixed-wireless and mobile access, etc.). In this Research Paper, a service aware policy-based approach to NGN quality assurance is presented, taking into account both perceptual quality of experience and technologydependant quality of service issues. The respective procedures, entities, mechanisms, and profiles are discussed. The purpose of the presented approach is in research, development, and discussion of pursuing the end-to-end controllability of the quality of the multimedia NGN-based communications in an environment that is best effort in its nature and promotes end user’s access agnosticism, service agility, and global mobility
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 ...
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.
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.
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.
Quality of experience aware network selection model for service provisioning...IJECEIAES
Heterogeneous wireless networks (HWNs) are capable of integrating the different radio access technologies that make it possible to connect mobile users based on the performance parameters. Further quality of service (QoS) is one of the major topics for HWNs, moreover existing radio access technology (RAT) methodology are designed to provide network QoS criteria. However, limited work has been carried out for the RAT selection mechanism considering user QoS preference and existing models are developed based on the multi-mode terminal under a given minimal density network. For overcoming research issues this paper present quality of experience (QoE) RAT (QOE-RAT) selection methodology, incorporating both network performance criteria and user preference considering multiple call and multi-mode HWNs environment. First, this paper presents fuzzy preference aware weight (FPAW) and multi-mode terminal preference aware TOPSIS (MMTPA-TOPSIS) for choosing the best RAT for gaining multiservices. Experiment outcomes show the QOE-RAT selection method achieves much superior packet transmission outcomes when compared with state-of-art Rat selection methodologies.
Wireless Networks Performance Monitoring Based on Passive-active Quality of S...IJCNCJournal
Monitoring of the performance of wireless network is of vital importance for both users and the service provider which should be accurate, simple and fast enough to reflect the network performance in a timely manner. The aim of this paper is to develop an approach which can infer the performance of wireless ad hoc networks based on Quality of service (QoS) parameters assessment. The developed method considers the QoS requirements of multimedia applications transmitted over these kind of networks. This approach is based on the ideas of combination of both active and passive measurement methods. This approach uses an in-service measurement method in which the QoS parameters of the actual application (user) are estimated by means of dedicated monitoring packets (probes). Afterwards, these parameters are combined to produce and assess the application’s overall QoS using the fuzzy logic assessment and based on the measured QoS parameters estimated using the probe traffic. The active scheme is used to generate monitoring probe packets which are inserted between blocks of target application packets at regular intervals. While the passive monitoring is utilized to act as a traffic meter which performs as a counter of user packets (and bytes) that belong to the application (user) traffic flow that is subjected to monitoring. After simulating the developed technique, it offered a good estimation for the delay, throughput, packet losses and the overall QoS when using different probe rates.
Vehicular ad hoc networks (VANETs) have seen tremendous growth in the last decade, providing a vast
range of applications in both military and civilian activities. The temporary connectivity in the vehicles can also
increase the driver’s capability on the road. However, such applications require heavy data packets to be shared on
the same spectrum without the requirement of excessive radios. Thus, e-client approaches are required which can
provide improved data dissemination along with the better quality of services to allow heavy traffic to be easily
shared between the vehicles. In this paper, an e-client data dissemination approach is proposed which not only
improves the vehicle to vehicle connectivity but also improves the QoS between the source and the destination. The
proposed approach is analyzed and compared with the existing state-of-the-art approaches. The effectiveness of the
proposed approach is demonstrated in terms of the significant gains attained in the parameters namely, end to end
delay, packet delivery ratio, route acquisition time, throughput, and message dissemination rate in comparison with
the existing approaches.
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CHARACTERIZATION OF USER-PERCEIVED QUALITY OF SERVICE (QOS) IN MOBILE DEVICES USING NETWORK PAIRWISE COMPARISONS
1. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
DOI : 10.5121/ijwmn.2010.2310 141
CHARACTERIZATION OF USER-PERCEIVED
QUALITY OF SERVICE (QOS) IN MOBILE DEVICES
USING NETWORK PAIRWISE COMPARISONS
Carlos E. Otero1
, Ivica Kostanic2
, Luis D. Otero3
, and Scott L. Meredith2
1
Department of Mathematics & Computer Science, University of Virginia’s College at
Wise, Wise, VA, USA
cotero@virginia.edu
2
Department of Electrical & Computer Engineering, Florida Institute of Technology,
Melbourne, FL, USA
kostanic@fit.edu; smeredit@my.fit.edu
3
Department of Engineering Systems, Florida Institute of Technology,
Melbourne, FL, USA
lotero@fit.edu
ABSTRACT
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.
KEYWORDS
Quality of Service, Wireless Networks, Cellular Networks, Analytic Hierarchy Process, Performance
Evaluation in Cellular Networks
1. INTRODUCTION
By 2014, cell phones and other mobile devices will send and receive more data each month than
they did in all of 2008 [1]. This fast and constant increase in the cellular market is expected to
leave a huge imprint in all facets of human (day to day) life, such as social networking,
transportation, healthcare, education, and national security. Unfortunately for network
providers, loyalty is a rare (and perhaps non-existent) trait among customers when it comes to
choosing/keeping a particular mobile cellular system provider. This means that no matter how
much effort, engineering, and money invested by companies into their respective
communication technologies, users will ultimately make their decisions based on their
perceived quality of service (QoS). Therefore, to remain competitive, network providers will be
required to understand and characterize customers’ perception of the QoS provided by their
respective technologies.
2. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
142
In today's cellular markets one encounters multiple cellular networks servicing the same
geographical area. For example, in mature US markets, there may be as many as eight cellular
licenses servicing the area (2 in the 850MHz band and 6 in the 1900MHz band). Each license
may host a different service provider. Furthermore, with recent auctions of 700MHz spectrum
and the rollout of broadband services in 2.5GHz and 3.65GHz bands, the number of wireless
cellular networks is bound to increase even more. Due to various competitive and historical
reasons, deployed networks may be quite different. For example, the networks may have been
deployed with different objectives in mind, they may utilize different access technologies or
they may be at a different evolutional stage of a given access technology. Furthermore, most of
the networks support both circuit switched (CS) and packet switched (PS) communication
services. While CS services are dominated by voice, PS services support a plurality of data
centric applications. As a result, a comparison between QoS levels offered by different
networks becomes a non trivial task. As cellular technology continues to ingrain itself in all
aspects of society, network providers must emphasize on delivering high QoS to its end users.
Therefore, the assessment of QoS based on user experiences becomes essential.
This paper proposes a quantitative approach for evaluating the perceived QoS of data services in
wireless cellular networks. Specifically, the approach uses the Analytic Hierarchy Process
(AHP) to evaluate data collected from drive-testing to characterize the perceived QoS of data
services from three different networks. This characterization can be used by network providers
to evaluate how well their services are being perceived so that they can make corrections or
improvements as needed. The development of this methodology provides a unique approach to
characterize QoS based on application-specific quality criteria and relative to other networks
operating in the same geographical area. The remainder of the paper is organized as follows.
Section 2 provides a brief summary of user-centric QoS evaluation methods. Section 3 provides
a brief summary of the solution approach, which includes drive-testing and the AHP. Sections 4
and 5 provide detailed explanations of the drive-testing experimental environment and AHP
technique. Section 6 presents the results of various case studies. Finally, Section 7 provides
summarized conclusions and highlights of the proposed approach.
2. BACKGROUND WORK
In [2], the authors present a QoS assessment methodology for cellular communication networks
based on the data collected through drive-testing. The work focuses on the end user perception
of service quality by providing independent QoS measurement for voice and data services. In
their work, the authors discuss QoS assessment for both the circuit switched and packet
switched side of the network; however, they fail to provide QoS measurements as function of
both voice and data services simultaneously. In [3], the authors stress the importance of
network operators evaluating user-perceived QoS of data services in cellular networks. In their
work, the authors specify user experience as a key factor in determining the network operator's
success; and present a methodology for evaluating quality of the FTP data service in cellular
UMTS networks. Their methodology is based on data collected through drive testing and can be
easily extended to other cellular data services. However, the proposed methodology
concentrates on evaluating end-user experience based only on data services on a single network.
Similarly, in [4], the authors present results of evaluation of (user-centric) QoS of background
services in an individual UMTS network. In their work, the authors present results for user-
perceived QoS for email and SMS. However, their approach is bounded to a single UMTS
network. In [5], a multi-network methodology for evaluating QoS for both voice and data
services is presented. The authors use drive-testing to measure individual QoS criteria for both
voice and data services. The criteria used for evaluating QoS in voice services are
Accessibility, Retainability, Call Quality, and Voice Quality. For data services, the identified
QoS criteria include Connection, FTP Downlink, and FTP Uplink. Once drive testing is
performed and the data collected, their approach uses desirability functions to fuse all
3. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
143
measurements into one unified value that is representative of QoS for a particular application
class. In their work, the authors define the following application classes: Emergency, Business,
and Personal. For each class, the desirability function parameters are adjusted to reflect the
priorities of the (voice and data) services expected. This results in a holistic QoS measurement
that considers prioritized voice and data services. The approach provides an improvement to
previous work by fusing both voice and data services, and providing a way to customize the
evaluation process to specific classes of applications. However, their approach fails to provide
evaluation of QoS relative to other networks in the same geographical area. In [6], the authors
present a process for comparing Quality of Experience (QoE) in packet-switched networks
using the AHP and Grey Relational Analysis. However, by their own admission, their
approach, like many other QoE approaches, “rely mostly on user survey and scores from the
user, which are too subjective and need much processing time and cost.”[6].
From the reviewed literature, it is evident that there is room for the development of a holistic,
user-centric, and application-specific evaluation methodology that provides objective
measurements of QoS relative to all other networks available in the same region. This will
allow network providers to better assess how well their services are being perceived relative to
their competitors.
3. SOLUTION APPROACH
To properly evaluate QoS of data services in cellular networks, analysts must follow a
methodology that considers user-experiences in specific application scenarios. Furthermore, the
evaluation methodology must allow users to compare how well networks perform (relative to
competitors) in the same geographical region based on predefined evaluation criteria. The
evaluation methodology must also allow users to assign priorities to evaluation criteria to
customize the results based on particular classes of applications. The creation of such
methodology is achieved as follows. First, drive-testing is performed to collect objective
measurements associated with identified QoS criteria for data services. Once drive-testing is
completed and the data collected, the AHP technique is used to compare multiple networks and
determine the network that provides higher QoS based on users’ perception of quality. The
output provided by the AHP approach can be used as unified measurement of the perceived QoS
by users on different networks. In order to determine application-specific priorities, the
approach presented here uses the application classes identified in [5], that is: 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.
4. DRIVE TESTING
Drive-testing is performed by placing calls, either voice or data, to a cellular network and
recording the data from these calls. The calls are automated by test equipment and the data are
geographically referenced by using a GPS unit. A typical setup for the drive testing equipment
for PS data measurements is presented in Figure 1. As seen, the setup consists of the in-vehicle
equipment and appropriate PS data server. The in-vehicle equipment controls data cards (or
other data communicating devices), associated with the cellular networks under test. The PS
data server is connected to the cellular networks through the Internet cloud. The connectivity
between the PS data server and the Internet is accomplished through high bandwidth dedicated
lines. This way the performance of the data service is primarily determined by the performance
of the cellular side of the network. The in-vehicle equipment controls data devices and it is
programmed to execute a sequence of actions. Depending on what needs to be tested, the
sequence may include one or multiple data services.
4. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
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Figure 1. Drive Testing Setup Overview
Each device in the vehicle loops through the same sequence of tasks and relevant measurements
are collected, time stamped and geographically referenced. The types of tasks that are included
in the test depend on what particular data service needs to be tested. In practice, one would at
least test ping, FTP upload, FTP download and HTTP based web browsing [7, 8]. The PS data
server needs to be configured properly so that it is able to act as a termination point for all data
calls.
5. ANALYTIC HIERARCHY PROCESS
The AHP is a multi-attribute decision-making method used to facilitate decisions that involve
multiple competing goals [9, 10, 11]. It provides a powerful tool that can be used to evaluate
different network providers based on multiple QoS Evaluation Criteria (QEC). It starts by
transforming the QoS evaluation problem into a structured hierarchy where each QEC is
quantified and related to overall goals for evaluating alternative solutions. Typical QEC for
data services could include network accessibility, success rates of FTP download, or success
rate of FTP uploads. Typical goals for evaluating alternative solutions could include
maximizing (or minimizing) all QEC identified. Evaluation goals are customized based on
specific application requirements. For example, in the Emergency class of applications (EMTs,
police officers, etc.), users will come to rely heavily on location-based services, where
connection and downlink data services are of most importance. Other examples include the
business and personal class of applications. In all cases, AHP can be used to quantify goals,
prioritize them, and include them in the evaluation methodology. A generic AHP hierarchy for
the QoS evaluation process is presented in Figure 2.
The second and third levels of the AHP hierarchy vary according to the networks available and
the QECs selected for evaluating the networks. As seen, the second level can be extended to
include other QECs, such as increased security, maintenance, voice services, etc. The third
level consists of the networks servicing the geographical region being evaluated. To describe
the methodology, this paper considers the following three networks: CDMA, GSM and UMTS.
5. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
145
Figure 2. AHP Hierarchy for QoS Evaluation
In other scenarios, there could be n networks, each providing different measurements for each
QEC identified. Once the hierarchy is built, and relevant QEC measurements taken for each
network, a common scale is created to rank each network. That is, for each comparison made
during the AHP, a common pair-wise comparison scale is used to determine how preferred one
option is from another. This allows standardization in all comparisons made during the AHP
process. Table 1 presents the pairwise comparison scale created for the QoS evaluation
problem.
Table 1. Pairwise Comparison Scale.
Scale (w) Description
1 Equally Preferred
2 Equally to Moderately Preferred
3 Moderately Preferred
4 Moderately to Strongly Preferred
5 Strongly Preferred
QoS evaluators establish preferences between different networks using the pairwise comparison
scale and pairwise comparison matrices [11]. There are two types of pairwise comparison
matrices in AHP: the Network vs. Network matrices, and the QEC vs. QEC matrix. The
Network vs. Network pairwise comparison matrices are matrices where each element aij
represents how much more desirable the network at row i is than the network at column i, in
terms of a pre-defined QEC (e.g., connectivity, downlink, uplink). Using the results from drive-
testing, QoS evaluators are equipped with the knowledge necessary to make these assignments.
The format of the Network vs. Network matrices is presented in (1), where Az is the pairwise
comparison matrix for QEC z (i.e., z ∈ {connectivity, downlink efficiency, uplink efficiency})
and Nx represents network x.
6. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
146
=
n
n
n
n
n
n
n
n
z
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
N
N
N
N
N
N
A
L
M
O
M
M
L
L
M
L
2
1
2
2
2
1
2
1
2
1
1
1
2
1
2
1
(1)
From each Az matrix, a weight vector W is computed to determine the relative importance of
each network in the pairwise comparison matrix. That is, assuming weight
vector [ ]
n
w
w
w
W L
2
1
= , the value of wi represents the relative importance of network i of the
associated pairwise comparison matrix based on QEC z. The weight vectors are used to make
the final decision. To compute the weight vectors, the pairwise comparison matrix Az is
normalized using (2),
=
∑
∑
∑
∑
=
=
=
=
n
i
in
nn
n
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L
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(2)
where aij represents the ath
element at row i and column j of the respective Network vs. Network
comparison matrix. Once in normalized form, the weight vector associated with Anorm is
computed with (3).
=
=
=
=
∑
∑
∑ =
=
=
n
a
w
n
a
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W
n
j
nj
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n
j
j
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1 L (3)
The QEC vs. QEC pairwise comparison matrix is a n x n matrix where each location aij
represents how much more important the QEC (e.g., connectivity, downlink, uplink, etc.) at row
i is than the QEC at column j. The importance of each QEC is configured depending on the
class of application (e.g., Emergency, Business, or Personal) used in the evaluation process.
The format of the QEC vs. QEC matrix is presented in (4), where wi is the weight given to QEC
i.
(4)
Once the QEC vs. QEC matrix is created, it is normalized and the weight vector is computed
using the same procedure as in the Network vs. Network matrices. Once all weight vectors in
the QoS evaluation problem have been computed, they are used to determine the network that
=
n
n
n
n
n
n
n
n
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
w
Q
Q
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A
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1
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1
2
1
7. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
147
provides the best QoS. For example, assuming a QoS evaluation problem with x number of
QEC and y number of networks, the AHP provides y+1 weight vectors; one (WA) associated
with the QEC vs. QEC pair-wise comparison matrix, and the rest Wi associated with each
Network vs. Network matrix i, as illustrated in Figure 3.
Figure 3. AHP Weight Vectors
To compute the relative preference for network i, we let W = Wi, WA = WA, and define Si as the
overall score for network i, then,
Si = ( )
k
n
k
k WA
W
∑
=1
(5)
where k represents the kth
element of vectors W and WA. Once overall scores are computed for
all networks, the highest score is identified as the network providing the best QoS, followed by
the second highest score, and so on. This prioritized list helps determine the best perceived QoS
for a particular class of applications among different network providers.
4. CASE STUDY
This section presents results of a QoS evaluation case study using the proposed approach. The
case study evaluates QoS of data services for the following three cellular networks: CDMA,
GSM, and UMTS. The types of QEC depend on the particular data services being evaluated.
For this case study, the identified QEC for data services include Connection (CO), FTP
Downlink (DL), and FTP Uplink (UL). CO is a measure of the network accessibility; that is, the
ratio between the number of successfully established connections and the number of attempted
connections. DL and UL are measurements of the probability that a started FTP download or
upload terminates properly with its completion. The file sizes used for evaluating DL and UL
were 3MB and 100KB respectively. For details of the drive-testing environment and setup,
readers can refer to [2]. The success rates for CO, DL, and UL are presented in Table 2.
Table 2. QoS Criteria Assessment Matrix for Case Study 1
Network
Data Services Success Rate (%)
Connectivity Downlink Uplink
CDMA 89.00 70.00 65.00
GSM 74.00 55.00 75.00
UMTS 83.00 88.00 94.00
To evaluate the data services QoS provided by the networks, pairwise comparison of each
network in terms of each individual QEC is performed. Each network is compared using the
comparison scale specified in Table 1. Results are presented below.
n
T
w
w
w
w
M
2
1
1
n
T
w
w
w
w
M
2
1
2
n
T
w
w
w
w
M
L
2
1
−
n
T
y
w
w
w
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2
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2
1
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Using the pairwise comparison matrices of all networks based on each QEC, the AHP approach
can now be used to compute a measurement of QoS for all three classes of applications
identified in [5]; that is, Emergency, Business, and Personal. The following sections show the
effects that each of these applications have on overall QoS evaluation. Comparisons of QEC
vs. QEC are made to properly reflect the relative importance of each QEC in the three types of
applications.
4.1 Emergency Class
To show the effects that particular classes of applications have on overall QoS evaluation, the
QEC vs. QEC comparisons are made to properly reflect the relative importance of each QEC in
emergency applications (EMTs, police officers, etc). In this class of applications, users will
come to rely heavily on location-based services, where connection and downlink data services
are of most importance. The QEC vs. QEC comparison matrix, normalized matrix, and weight
vector are presented in Table 6.
Table 6. QEC vs. QEC Matrix, Normalized Matrix, and Weight Vector for Emergency Class
QEC vs. QEC Connectivity Downlink Uplink
Connectivity 1 4 5
Downlink 0.25 1 4
Uplink 0.2 0.25 1
Total 1.45 5.25 10
QEC vs. QEC Connectivity Downlink Uplink
Connectivity 0.69 0.76 0.50
Downlink 0.17 0.19 0.40
Uplink 0.14 0.05 0.10
Connectivity Downlink Uplink
Weight 0.65 0.25 0.10
Finally, using (5), the results of Tables 3 – 6 are combined to provide the final QoS
measurement for data services based on the Emergency class of applications. The final
perceived QoS measurement is presented in Table 7.
Table 7. Network QoS for Data Services in the Emergency Class
Network QoS
CDMA 47.00%
GSM 12.42%
UMTS 40.57%
4.2 Business Class
For Business applications, the ability to connect and uplink a file may be of higher importance
than the downlink capability. Therefore, for this case application, the QEC vs. QEC
comparison matrix is configured to reflect this assumption, as seen in Table 8. The QEC vs.
QEC comparison matrix, normalized matrix and weight vector are presented in Table 8 and the
results presented in Table 9.
10. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
150
Table 8. QEC vs. QEC Comparison Matrix, Normalized Matrix, and Weight Vector for
Business Class
QEC vs. QEC Connectivity Downlink Uplink
Connectivity 1.00 3.00 0.50
Downlink 0.33 1.00 0.20
Uplink 2.00 5.00 1.00
Total 3.33 9.00 1.70
QEC vs. QEC Connectivity Downlink Uplink
Connectivity 0.30 0.33 0.29
Downlink 0.10 0.11 0.12
Uplink 0.60 0.56 0.59
Connectivity Downlink Uplink
Weight 0.31 0.11 0.58
Table 9. Network QoS for Data Services in the Business Class
Network QoS
CDMA 27.62%
GSM 18.18%
UMTS 54.20%
As seen, when uplink is equally to moderately preferred to connectivity; connectivity
moderately preferred to downlink; and uplink strongly preferred to downlink, the results of the
perceived QoS change to identify the UMTS network as the best performer, followed by
CDMA, and GSM. In similar fashion, the QEC vs. QEC parameters can be adjusted for
applications in the personal class of mobile applications to appropriately evaluate QoS.
4.3 Personal Class
For Personal applications, the ability to download information, such as web pages, music, and
pictures are commonly expected among users of the Personal class of applications. Users in this
class tend to accept the fact that minimal network flaws related to establishing connections is an
inherently and unavoidable part of network services. Therefore, users of the Personal class of
applications may put up with not being able to connect to the network at times; however, when
a connection is made, they may mandate the ability to download data contents using the
network. This can be reflected by configuring the QEC vs QEC matrix to reflect Downlink
having the higher priority, followed by Connectivity and Uplink. The QEC vs. QEC
comparison matrix, normalized matrix and weight vector are presented in Table 10 and the
results presented in Table 11.
Table 10. QEC vs. QEC Comparison Matrix, Normalized Matrix, and Weight Vector for
Personal Class
Factor vs.
Factor
Connectivity Downlink Uplink
Connectivity 1.00 0.50 4.00
Downlink 2.00 1.00 5.00
Uplink 0.25 0.20 1.00
Total 3.25 1.70 10.00
11. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
151
Factor vs.
Factor
Connectivity Downlink Uplink
Connectivity 0.31 0.29 0.40
Downlink 0.62 0.59 0.50
Uplink 0.08 0.12 0.10
Connectivity Downlink Uplink
Weight 0.33 0.57 0.10
Table 11. Network QoS for Data Services in the Personal Class
Network QoS
CDMA 35.76%
GSM 11.68%
UMTS 52.56%
5. CONCLUSION
The research presented in this paper develops an approach for evaluating application-specific
and user-perceived QoS in cellular networks based on data services. Specifically, it presents a
technology-agnostic methodology that uses AHP to create a unified measurement that
represents how well cellular networks operate for a particular set of application classes and
relative to other networks servicing the same area. Through several case studies, the approach
is proven successful in providing a way for analyzing user-centric QoS for application-specific
usage.
There are several important contributions from this research. First, the approach is simple and
readily available for implementation using a simple spreadsheet. This can promote usage in
practical scenarios, where highly complex methodologies for QoS evaluation are impractical.
Second, the approach fuses unlimited QoS quality evaluation criteria to provide a holistic view
of the experienced QoS. This allows the approach to be easily extended to include additional
data (or voice) quality criteria not considered in this research. Third, by using data from drive-
testing, the approach provides objective measures of QoS, which improves previous approaches
using subjective data from surveys. Finally, the approach provides a mechanism to evaluate
QoS based on application-specific scenarios. By modifying the parameters of the QEC vs. QEC
comparison matrix, QoS can be evaluated by taking consideration of prioritized services that are
necessary for different classes of applications. Overall, the approach presented in this research
proved to be a feasible technique for efficiently evaluating the perceived QoS in wireless
cellular networks.
ACKNOWLEDGEMENT
The authors would like to express a sincere appreciation to QualiTest Technologies, Inc. for
support of the research presented in this paper. Also, the authors would like to thank the
reviewers whose constructive critique greatly improved the quality of the paper.
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Authors
Dr. Carlos E. Otero was born in 1977 in Bayamon, Puerto Rico. He received his B.S.
in computer science, M.S. in software engineering, M.S. in systems engineering, and
Ph.D. in computer engineering from Florida Institute of Technology, in Melbourne, FL.
His primary research interests include performance evaluation and optimization of
systems and processes in a wide variety of domains (including wireless systems,
software engineering, and systems engineering).
He is currently Assistant Professor in the department of Mathematics and Computer
Science at the University of Virginia’s College at Wise, Wise, VA. Previously, he was adjunct professor
in the department of Electrical & Computer Engineering at Florida Institute of Technology. He has over
10 years of industry experience in satellite communications systems, command & control systems,
wireless security systems, and unmanned aerial vehicle systems.
13. International Journal of Wireless & Mobile Networks ( IJWMN ), Vol.2, No.3, August 2010
153
Dr. Otero is a professional member of the ACM and senior member of the IEEE.
Dr. Ivica Kostanic was born in 1968 in Belgrade, Yugoslavia. He obtained BSEE,
MSEE and PhD from Belgrade University, Florida Institute of Technology and
University of Central Florida respectively. His principal research interests include
various topics in radio communication, cellular systems and wireless sensor networks.
Currently, he is faculty member in the Electrical and Computer Engineering
department at Florida Institute of Technology where he teaches courses related to
wireless communication, personal communication and microwave circuit design. He
is the technical director of Wireless Center of Excellence (WiCE) which is a group at Florida Tech
dedicated to promoting research in wireless communication and computing technologies.
Dr. Kostanic is a member of the IEEE Communication Society.
Dr. Luis Daniel Otero was born in 1975 in Bayamon, Puerto Rico. He received his
B.S. in Civil Engineering, M.S. in Computer Information Systems, and M.S. in
Engineering Management from Florida Institute of Technology, Melbourne, FL. He
received his Ph.D. in Industrial and Management Systems Engineering from the
University of South Florida, Tampa, FL. His research areas include simulation
modeling, decision analysis, project engineering, and systems engineering.
He is an Assistant Professor of Engineering Systems at Florida Institute of Technology. He has over 8
years of experience as a software engineer for Harris Corporation (Government Communications Systems
Division) and Northrop Grumman Corporation (Aerospace Systems).