Quality Of Service For Applications Research Articles

The Effects of Exercise Commitment Facilitated by Service Quality of Smartphone Exercise Applications on Continued Exercise Intention

The purpose of this study is to examine the effects of exercise commitment facilitated by service quality of smartphone exercise Apps on continued exercise intention and provide primary data for developing and/or improving smartphone exercise Apps.

DDL‐QoS: A dynamic I/O scheduling strategy of QoS for HPC applications

SummaryWith the increasing cloud‐trend of high‐performance computing (HPC), more users submit their applications simultaneously to the platform and wish they could finish before the deadline. Moreover, due to the severe holistic performance degradation caused by I/O contention, a deadline‐sensitive I/O scheduler is needed to allocate storage resources according to the requirements of applications and resultantly guarantee the quality of service (QoS) of concurrently running applications. In this paper, we first explore the bandwidth allocation phenomenon caused by interference in applications through the modeling of historical data, and then we quote a metric called random percentage that can represent the random degree of the applications and be used to guide I/O scheduling in the later stage. We design a dynamic I/O scheduler named DDL‐QoS that uses solid state drives(SSDs) as QoS guarantee to minimize interference and ensure applications meet their deadline. The potential of our design is that the greater the I/O interference, the greater the performance improvement, but this performance improvement will be limited by the physical properties of the storage hardware.

Slice Management for Quality of Service Differentiation in Wireless Network Slicing.

Network slicing is a technology that virtualizes a single infrastructure into multiple logical networks (called slices) where resources or virtualized functions can be flexibly configured by demands of applications to satisfy their quality of service (QoS) requirements. Generally, to provide the guaranteed QoS in applications, resources of slices are isolated. In wired networks, this resource isolation is enabled by allocating dedicated data bandwidths to slices. However, in wireless networks, resource isolation may be challenging because the interference between links affects the actual bandwidths of slices and degrades their QoS. In this paper, we propose a slice management scheme that mitigates the interference imposed on each slice according to their priorities by determining routes of flows with a different routing policy. Traffic flows in the slice with the highest priority are routed into shortest paths. In each lower-priority slice, the routing of traffic flows is conducted while minimizing a weighted summation of interference to other slices. Since higher-priority slices have higher interference weights, they receive lower interference from other slices. As a result, the QoS of slices is differentiated according to their priorities while the interference imposed on slices is reduced. We compared the proposed slice management scheme with a naïve slice management (NSM) method that differentiates QoS among slices by priority queuing. We conducted some simulations and the simulation results show that our proposed management scheme not only differentiates the QoS of slices according to their priorities but also enhances the average throughput and delay performance of slices remarkably compared to that of the NSM method. The simulations were conducted in grid network topologies with 16 and 100 nodes and a random network topology with 200 nodes. Simulation results indicate that the proposed slice management increased the average throughput of slices up to 6%, 13%, and 7% and reduced the average delay of slices up to 14%, 15%, and 11% in comparison with the NSM method.

Análisis de la Arquitectura DIFFSERV sobre redes MPLS para la provisión de QoS en aplicaciones en tiempo real (VoIP)

Actualmente, las redes IP necesitan de QoS para aplicaciones en tiempo real, donde el principal problema está en que las redes IP no tienen un mecanismo para proporcionarlo. En este trabajo, se propuso implementar la arquitectura DiffServ sobre redes MPLS, con el objetivo de mejorar las prestaciones a las redes, brindando un trato diferenciado al tráfico en tiempo real. En el análisis se diseñó un ambiente de pruebas con tres escenarios: redes IP, redes MPLS y MPLS DiffServ, realizados en GNS3 con la herramienta Dig-it 2.61 GUI 0.92, para inyectar tráfico de VoIP y datos utilizando etiquetas para su identificación. Cada contexto fue evaluado con los tres indicadores: retardo, jitter y pérdida de paquetes, mediante la herramienta Wireshark. Nuestro estudio determinó una calidad de servicio de VoIP adecuada con la implementación de MPLS y DiffServ.

Overload control for virtual network functions under CPU contention

In this paper, we analyze the problem of overloads caused by physical CPU contention in cloud infrastructures, from the perspective of time-critical applications (such as Virtual Network Functions) running at guest level. We show that guest-level overload control solutions to counteract traffic spikes (e.g., traffic throttling) are counterproductive against overloads caused by CPU contention. We then propose a general guest-level solution to protect applications from overloads also in the case of CPU contention. We reproduced the phenomena on a IP Multimedia Subsystem (IMS) testbed based on OpenStack on top of KVM. The results show that the approach can dynamically adapt the service throughput to the actual system capacity in both cases of traffic spikes and CPU contention, by guaranteeing at the same time the IMS latency requirements. • Resource contention is a common cause of overload in virtualized infrastructures. • CPU contention causes side effects on the QoS of time-critical applications. • Guest OS CPU metrics are often misinterpreted when dealing with CPU contention. • NFV Load throttling solutions can misbehave in the case of physical CPU contention. • Avoiding idle CPU time preemption helps to protect systems from contention effects.

NSAF: An Approach for Ensuring Application-Aware Routing Based on Network QoS of Applications in SDN

The advent of software-defined networking (SDN) has led to the paradigm of programmable network environments. Conceptually, the structure of SDN is divided into three layers: application, control, and infrastructure. The SDN controller in the control layer can configure and execute the routing of applications to the infrastructure layer consisting of network devices, including hosts and switches. Current studies on SDN have predominantly focused on control layer aspects, such as controller development, performance aspects of the controller, and interaction among different controllers and between controllers and network devices. However, to provide seamless network services and efficiently manage network environments, application-aware routing is essential because applications may have different quality of service (QoS) requirements, such as maximum bandwidth and minimum delay. This study proposes the Network Situation-Aware Framework (NSAF) to more efficiently handle application routing based on the QoS requirements and changing network status. A mechanism for supporting the NSAF consisting of application registration, network status monitoring, violation detection, and routing control is also presented. The applicability and feasibility of the proposed NSAF are verified by implementing a prototype. The NSAF may be used as a reference model for efficiently managing SDN-based networks to ensure application QoS.

An Adaptive Approach Towards Computation Offloading for Mobile Cloud Computing

The widespread acceptability of mobile devices in present times have caused their applications to be increasingly rich in terms of the functionalities they provide to the end users. Such applications might be very prevalent among users but the execution results in dissipating many of the device end resources. Mobile cloud computing (MCC) has a solution to this problem by offloading certain parts of the application to cloud. At the first place, one might find computation offloading quite promising in terms of saving device end resources but eventually may result in being the other way around if performed in a static manner. Frequent changes in device end resources and computing environment variables may lead to a reduction in the efficiency of offloading techniques and even cause a drop in the quality of service for applications involving the use of real-time information. In order to overcome this problem, the authors propose an adaptive computation offloading framework for data stream applications wherein applications are partitioned dynamically followed by being offloaded depending upon the device end parameters, network conditions, and cloud resources. The article also talks about the proposed algorithm that depicts the workflow of the offloading model. The proposed model is simulated using the CloudSim simulator. In the end, the authors illustrate the working of the proposed system along with the simulated results.

Cloud Resource Adaptive Scheduling Framework and Optimization Strategy Based on Swarm Intelligence

Resource scheduling framework is very important for the overall cloud service efficiency and service quality,which is the core module of cloud computing. This paper proposes an adaptive cloud computing resource scheduling framework based on swarm intelligence. The proposed adaptive framework includes resource deployment module, scheduling module, recommendation module, optimization module, and monitoring module.The simulation results show that the proposed framework is more efficient than the traditional framework in terms of task execution time, system load balancing and resource service quality, and can improve the service quality of cloud applications while improving resource utilization.

Adaptive optimization of QoS constraint transmission capacity of VANET

Safety applications would be one of the most important on-board implementations in Vehicular Ad-hoc Network (VANET). Broadcasting the Basic Safety Message (BSM) periodically could help drivers increase their awareness range for preventing casualties of traffic accidents or reducing the number of traffic accidents. Usually, the safety applications have more stringent performance requirements (e.g. time delay and reliability) than other kinds of applications. However, because the vehicle density and speed are both changed frequently, the optimal network transmission parameters should not remain the same. So, setting constant transmission parameters in all conditions may cause problems, such as channel congestion, packet collisions and so on, which could degrade Quality of Service (QoS) of safety applications. For the purpose of maximizing the transmission capacity and keeping the application-level QoS of safety applications meeting their requirements, this paper proposes an optimization scheme with standard Particle Swarm Optimization (PSO) to adjust transmission parameters dynamically. The experimental results show that the optimized transmission parameters can get better results on transmission capacity and awareness probability compared with the transmission parameters which are used in real testbeds.

Security modeling and efficient computation offloading for service workflow in mobile edge computing

It is a big challenge for resource-limited mobile devices (MDs) to execute various complex and energy-consumed mobile applications. Fortunately, as a novel computing paradigm, edge computing (MEC) can provide abundant computing resources to execute all or parts of the tasks of MDs and thereby can greatly reduce the energy of MD and improve the QoS of applications. However, offloading workflow tasks to the MEC servers are liable to external security threats (e.g., snooping, alteration). In this paper, we propose a security and energy efficient computation offloading (SEECO) strategy for service workflows in MEC environment, the goal of which is to optimize the energy consumption under the risk probability and deadline constraints. First, we build a security overhead model to measure the execution time of security services. Then, we formulate the computation offloading problem by incorporating the security, energy consumption and execution time of workflow application. Finally, based on the genetic algorithm (GA), the corresponding coding strategies of SEECO are devised by considering tasks execution order and location and security services selection. Extensive experiments with the variety of workflow parameters demonstrate that SEECO strategy can achieve the security and energy efficiency for the mobile applications. ’

Location-Aware, Context-Driven QoS for IoT Applications

In this paper, we identify the unique quality of service (QoS) needs of emerging IoT applications and propose SDN-based Application-aware Dynamic Internet of things Quality of service (SADIQ), a software-defined network (SDN) framework that addresses these needs. SADIQ provides location-aware, context-driven QoS for IoT applications by allowing applications to express their requirements using a location-based abstraction and a high-level SQL-like policy language, and the network to support these requirements through recent advances in SDNs. We implement SADIQ using commodity OpenFlow-enabled switches and an open-source SDN controller and evaluate its effectiveness using traces from two real IoT applications. Our results show that SADIQ improves the percentage of regions with error in their reported temperature for the Weather Signal application up to 45×, and improves the percentage of incorrect parking statuses for regions with high occupancy for the Smart Parking application up to 30×, under the same network conditions and drop rates.

SDN-Based Quality of Service Networking for Wide Area Measurement System

Wide area measurement system (WAMS) infrastructure is one of the most significant elements of the smart grid that measures, collects, and analyzes data in the power system. Fundamental components of the WAMS are phasor measurement units (PMUs), phasor data concentrators (PDCs), and its relevant applications. The PDC collects data from several different PMUs, integrates data and sends it to the control center. In order to achieve a stable implementation of WAMS, the communication structure should be reliable and meets the quality of service (QoS) requirements for various applications in the network. In this paper, we propose a novel WAMS communication infrastructure by utilizing the software-defined networking technology, which can enhance the reliability of the corresponding networks. In the proposed model, in order to meet the applications QoS needs, the traffic flows are categorized into different class of services, and then by applying a QoS mechanism, along with a content-aware queuing algorithm, the maximum capacity for the critical traffic is obtained. This provides a low latency for critical WAMS applications. The proposed model has been implemented in the Mininet environment using the Ryu controller. The implementation results indicate that the proposed infrastructure reduces end-to-end delay and packets loss and utilizes the network resources optimally.

The Effects of Exercise Commitment Facilitated by Service Quality of Smartphone Exercise Applications on Continued Exercise Intention

Background/Objectives: The purpose of this study is to examine the effects of exercise commitment facilitated by service quality of smartphone exercise Apps on continued exercise intention and provide primary data for developing and/or improving smartphone exercise Apps.
 Methods/Statistical analysis: A questionnaire survey was conducted amongst college students who have experiences in using exercise App(s) and regularly exercise. The questionnaire is composed of four parts asking about service quality, exercise commitment, continued exercise intention, which were measured with a 5-point Likert Scale, and demographics. Frequency analysis, factor analysis, correlation analysis, and regression analysis were carried out to analyze the obtained data with PASW 18.0.

The Application of Service Quality and Brand Image to Maintain Customer Loyalty by Utilizing Satisfaction Strategy in Insurance Companies

This study had the following aims: (1) to describe the variable of service quality, brand image, loyalty and satisfaction of Prudential customers; (2) to analyze the influence of variable service quality and brand image on customer satisfaction; (3) to analyze the influence of variable service quality and brand image on customer loyalty; (4) analyze the influence of satisfaction on customer loyalty, and (5) to analyze the influence of service quality and brand image on customer loyalty through satisfaction strategy. There were 86 respondents that were used as a sample in this study. This research employed the structural equations (Structural Equation Modeling) as its analysis technique. The results showed that service quality and brand image had an influence on satisfaction, which meant that the provision of quality services and supported by companies that had good images could increase customer satisfaction. Furthermore, the service quality and brand image influenced Prudential Malang's consumer loyalty. This meant that customer loyalty could be developed through the provision of quality services since customers chose a company that had a good image/perception. Satisfaction affected loyalty. Customer satisfaction was subjective and it oriented towards individuals. Furthermore, it could relate to various aspects including the quality of services provided by the company. Customer satisfaction could be utilized to say positive things and reference for a company. Satisfaction mediated the influence of service quality and brand image on loyalty. This meant that customer loyalty could be developed if the customers were satisfied with the service quality provided by the company and also if the company had a good brand image.

Storage Sharing Optimization Under Constraints of SLO Compliance and Performance Variability

SLO enforcement with the required strong SLO compliance and the desired low level of performance variability is necessary to ensure QoS for user applications with precisely differentiated service levels. However, for the cloud consolidating a large number of VMs rented by users, it is a great challenge to formulate an IO capacity allocation among consolidated VMs under the user-customized QoS constraints of SLO compliance and performance fluctuation for consolidated VMs. To address this challenge, we propose SASLO, an end-to-end VM-oriented control framework that supports users in customizing SLO targets and QoS constraints for each VM. SASLO can dynamically coordinate the throughput target and IO size limit for each VM adapting to the status of SLO enforcement so as to maximize the IO capacity allocation among consolidated VMs under QoS constraints. To accurately enforce time-varying throughput target, SASLO establishes a proportional-integral IO controller for each individual VM to converge the actual throughput to the target with an expected settling time. Our extensive evaluation driven by representative benchmarks demonstrates that SASLO is able to formulate a satisfactory IO capacity allocation plan for consolidated VMs under the constraints of SLO compliance and performance variability.

A cross-layer QoS model for space DTN

Delay/disruption tolerant networking (DTN) technology is considered as a new solution for highly stressed communications in space environments. IP-based DTN network can support more flexible communication services, which is one of the research hotspots of space networking. At the same time, it is still an important and difficult problem to optimise the limited network resources allocation and guarantee the QoS of different services in DTN network. For this challenge, a cross-layer QoS model that considers application, network, and node layer QoS requirements and resource limitations is proposed in this paper. In addition, a comprehensive admission control scheme that ensures productivity and fairness is employed. The results of experiments and analyses conducted demonstrate the benefits to be derived from this approach.

Adaptive Energy Aware Quality of Service for Reliable Data Transfer in Under Water Acoustic Sensor Networks

Currently, reliable data transfer, and energy management have been considered as a significant research challenge in the underwater acoustic sensor networks (UWASN) owing to high packet loss, limited ratio of bandwidth with significant incur of energy, network life time with high propagation delay, less precision with high data hold time and so on. Energy saving and maintaining quality of service (QoS) is more important for UWASN owing to QoS application necessity and limited sensor nodes. To address this issue, several existing algorithms such as adaptive data forwarding algorithms, QoS-based congestion control algorithms and several methodologies were proposed with high throughput and less network lifetime as well as the less utilization of energy in UWASN by choosing sensor nodes data based on data transfer and link reliability. However, all the conventional algorithms have fixed data hold time, which incurs more end-to-end delay with less reliability of data and consumption of high energy due to high data transfer reachability. This high end research proposes adaptive energy aware quality of service (AEA-QoS) algorithm for reliable data delivery by formulating discrete times stochastic control process and deep learning techniques for UWSAN to overcome these issues. The proposed algorithm has been validated with conventional state-of-the-art methods and results show that the proposed approach exhibits its effectiveness in terms of less network overhead and propagation delay with high throughput and less energy consumption for every reliable packet transmission.

Novel self-adaptive routing service algorithm for application in VANET

As a special MANET (mobile ad hoc network), VANET (vehicular ad-hoc network) has two important properties: the network topology changes frequently, and communication links are unreliable. Both properties are caused by vehicle mobility. To predict the reliability of links between vehicles effectively and design a reliable routing service protocol to meet various QoS application requirements, in this paper, details of the motion characteristics of vehicles and the reasons that cause links to go down are analyzed. Then a link duration model based on time duration is proposed. Link reliability is evaluated and used as a key parameter to design a new routing protocol. Quick changes in topology make it a huge challenge to find and maintain the end-to-end optimal path, but the heuristic Q-Learning algorithm can dynamically adjust the routing path through interaction with the surrounding environment. This paper proposes a reliable self-adaptive routing algorithm (RSAR) based on this heuristic service algorithm. By combining the reliability parameter and adjusting the heuristic function, RSAR achieves good performance with VANET. With the NS-2 simulator, RSAR performance is proved. The results show that RSAR is very useful for many VANET applications.

Network Location Privacy Protection Based on Game Theory

The purpose of this paper is to protect the privacy of vehicles and passengers. In recent years, with the rapid development of vehicle networking, the location privacy of vehicle networking involves sensitive information about vehicles as well as passengers. It is of great theoretical and practical significance to put forward the privacy protection of vehicle network location. This paper is based on identity concealment, fuzzy method, cryptography and information theory. The goal is to fully protect the privacy of the vehicle's networked location. Using the technical methods of game theory as a means, and the mechanism of vehicle location privacy protection in typical applications and the game model of vehicle network attack and defense are studied. This paper introduces some common privacy protection methods, such as pseudonym transformation method, elliptic fuzzy method and so on. Establish the model and evaluation method of vehicle location privacy attack and defense strategy based on measurement. By analyzing the application scenarios, service quality and other factors and establishing the theoretical model of car network location privacy protection based on game theory, a privacy protection method based on game theory is proposed. The innovation of this paper is that the game theory is applied to the privacy protection of the Internet of vehicles. Thus, we can get the best guessing strategy of the enemy and the best privacy protection mechanism between location quality of service and privacy protection trade-off.

Fundamental concepts of reactive control for autonomous drones

Autonomous drones represent a new breed of mobile computing system. Compared to smartphones and connected cars that only opportunistically sense or communicate, drones allow motion control to become part of the application logic. The efficiency of their movements is largely dictated by the low-level control enabling their autonomous operation based on high-level inputs. Existing implementations of such low-level control operate in a time-triggered fashion. In contrast, we conceive a notion of reactive control that allows drones to execute the low-level control logic only upon recognizing the need to , based on the influence of the environment onto the drone operation. As a result, reactive control can dynamically adapt the control rate. This brings fundamental benefits, including more accurate motion control, extended lifetime, and better quality of service in end-user applications. Based on 260+ hours of real-world experiments using three aerial drones, three different control logic, and three hardware platforms, we demonstrate, for example, up to 41% improvements in motion accuracy and up to 22% improvements in flight time.