QoS Evaluation Research Articles

QoS Evaluation of ATS in IEEE 802.1TSN on In-Vehicle Ethernet by Comparing with CBS and TAS

QoS Evaluation of ATS in IEEE 802.1TSN on In-Vehicle Ethernet by Comparing with CBS and TAS

Replicated multistage interconnection networks: QoS evaluation for parallel and distributed computing

Introduction to big data becomes very important with dealing in high-performance parallel distributed computing, especially in those systems where communication among a number of processors is required. The current paper takes into consideration different topologies for the Shuffle Exchange Network (SEN) in order to attain optimal data transfer among such scenarios. SEN topologies are a key feature in connecting several processors and implementing the data transfer among them where a single processor fails to handle the load. The study hereby reports in the performance, reliability, and cost analysis of these topologies. These topologies, some of which are advocated to have better performance in many studies, include replicated networks. Our research demystifies claims made in earlier papers that replicated networks have inflated reliability and higher costs due to their additional links. Researchers are therefore guided on accurate performance data that will lead them to make optimum choices of SEN topologies for targeted applications. These findings further highlight that the trade-offs between reliability and cost must be carefully considered during network design so as to arrive at better results for big data communication and computation in parallel and distributed systems. This work provides important insights into the correct evaluation of SEN topologies, helping to correct the misleading facts and to have better network selection for various real-time application realizations.

Improving Network Service Quality in parts of Sampang City: QoS Evaluation and User Perception of QoE

Improving Network Service Quality in parts of Sampang City: QoS Evaluation and User Perception of QoE

Multi-Dimensional QoS Evaluation and Optimization of Mobile Edge Computing for IoT: A Survey

Multi-Dimensional QoS Evaluation and Optimization of Mobile Edge Computing for IoT: A Survey

Shared manufacturing service evaluation based on intuitionistic fuzzy VIKOR

With the rise of the concept of sharing economy, the shared manufacturing model has gained widespread attention. The VIKOR shared manufacturing service evaluation approach is presented based on an intuitionistic fuzzy environment, which enables users to filter out acceptable shared manufacturing services from a wide pool of shared manufacturing services with similar functional qualities. Firstly, considering the QOS multi-indicator comprehensive evaluation of services by multiple stakeholders under the fundamental characteristics of shared manufacturing, the QOS evaluation index system is built from the two aspects of online and offline, which includes 2 first-level indicators and 10 second-level indicators. The paper also constructs a service recommendation model considering supply and demand constraints. Secondly, the intuitionistic fuzzy numbers are introduced to define the non-quantitative indexes, and the G1-method and variable-precision rough set theory are used for the assignment, and the maximum entropy theory is utilized to integrate the assignment method to obtain the combination weights. Thirdly, the VIKOR method based on intuitionistic fuzzy sets is used to evaluate and rank the shared manufacturing candidate services, in which the combined benefits and minimum regret values of the groups are solved based on the intuitionistic fuzzy number similarity. Finally, the reliability and feasibility of the algorithm are verified with a real case.

Method of QoS evaluation of FPGA as a service

The subject of study in this article is the evaluation of the performance issues of cloud services implemented using FPGA technology. The goal is to improve the performance of cloud services built on top of multiple FPGA platforms known as FPGA-as-a-Service (FaaS). Task: to analyze the delays in communications between host computer and FPGA; propose the steps of development to reduce the delay and perform the evaluation of the response time for the FPGA-based accelerator depending on number of involved cards; consider the reliability aspect of such systems implemented using programmable logic. According to the tasks, the following results were obtained. The FPGA-as-a-Service where FPGA resources are provided through a set of hardware/software toolset is considered. The usage of queueing theory for cloud-based services is analyzed. The contribution of the parts of FPGA-as-a-Service to the final delay of the service is discussed. The process of modeling of work the services based on FPGA accelerator cards with use of Jackson's network is analyzed in detail. The model of the delays of FaaS that considers the parameters of accelerator FPGA cards is offered. The formula of the total response time of the service combined based on the response of the components of is obtained. The proposed steps of reduce data processing delays include increase the size of data blocks for processing in FPGA by each kernel, change the communication model with kernel from sequential to pipelined, following timing closure technique and use more FPGA accelerator cards in parallel to divide the enquiring delay. Based on the proposed model the evaluation of response time of FaaS was done. The advantage of the use of many FPGAs in parallel for same data processing task instead of implementation of requests thread for each accelerator card is shown. Conclusions. The main contribution of this study is a step forward to the modeling of FPGA-based services that can be used for FPGA-based artificial intelligence (AI) applications. It helps to improve the performance of the system by means of reducing the delays at different stages of requests processing. Another side of this result is the reliability aspect that is based on modified manner of service operation in case of use the proposed steps of system optimization. It helps to improve the processing of requests to FaaS. The proposed method is the next step after prototyping of such systems because it helps to turn the FaaS from the object for development to the tool for deployment of new technologies like AI applications.

Image recognition for gastrointestinal disease detection and diagnosis in QoS and QoE evaluation of 5G network communication

Image recognition for gastrointestinal disease detection and diagnosis in QoS and QoE evaluation of 5G network communication

QoS evaluation of combination SPQ, FRER and FP for in-vehicle networks

QoS evaluation of combination SPQ, FRER and FP for in-vehicle networks

A Tensor-Based Approach for the QoS Evaluation in Service-Oriented Environments

Multi-agent technologies have been widely applied to many applications, such as in e-markets, cloud computing, service-oriented environments, etc. In real applications, service-oriented environments are open and dynamic, where loosely coupled agents interact to consume and provide services. How to accurately evaluate the potential performance (i.e., QoS) of service providers on the service requested by a service consumer in such open and dynamic environments is a challenging issue in both theory and practice. In this paper, an innovative approach is proposed to evaluate the QoS of service providers in service-oriented environments. The proposed approach first borrows the reference report mechanism from the certified reputation model, so as to efficiently collect reference reports (i.e., historical performance) of service providers in open and dynamic environments. Then, a tensor-based QoS model is proposed to construct multi-dimensional relationships between QoS evaluation factors and the QoS values of service providers based on the collected reference reports. The QoS evaluation factors include the type of services, the performance of service providers, the subjectivity of service consumers, the time slot of reference reports. Finally, a CANDECOMP/PARAFAC decomposition and gradient descent-based mechanism is used to evaluate the QoS values of service providers through completing the missing entry values in the constructed tensor. The uniform random simulation experiments indicate that the proposed approach can achieve efficient and accurate QoS evaluation in service-oriented environments with only limited collected reference reports, especially when some service providers do not have reference reports.

QoS and QoE Evaluation of TCP Multi-Pathization Method with SDN over IoT networks for Web Service

QoS and QoE Evaluation of TCP Multi-Pathization Method with SDN over IoT networks for Web Service

Energy-Aware Service Selection and Adaptation in Wireless Sensor Networks with QoS Guarantee

Workflow-based Service-oriented WSN s have recently received a lot of attention from both academia and industry. With well-defined service components, various flexible WSN applications can be developed. However, the key characteristic of WSN s is resource constraints. Sensor nodes in WSN s have limited storage, computation and especially limited energy. As service components in WSN s rely on the data gathered by sensor nodes, they are also resource-constrained. Unfortunately, traditional workflow technologies (i.e., service selection, composition and adaptation) ignore the residual energy of services. This will bring unbalanced energy consumption and furthermore shorten the network lifetime. In order to resolve this issue, we proposed an energy-aware QoS -guaranteed workflow management mechanism. In this mechanism, a new QoS model is first presented to improve the QoS evaluation. Then, based on this QoS model, an efficient service selection schema, which considers both the energy and the QoS of services, is proposed. Furthermore, an adaptation mechanism for balanced energy consumption is also proposed. Experimental evaluations demonstrate the capability of our proposed approach.

Grey Weighted QoS Evaluation based on Real-Time Scene

Grey Weighted QoS Evaluation based on Real-Time Scene

Trust-Aware and Fast Resource Matchmaking for Personalized Collaboration Cloud Service

In data-intensive cloud collaboration services with tens of thousands of users and million-level resources, means of providing personalized and trust-aware services quickly and simultaneously is a challenging issue. In this paper, we propose Per-trust, a trust-aware and fast resource matchmaking scheme for personalized QoS guaranteeing in collaboration cloud service. First, an integrated and trust-aware service broking architecture is proposed across the collaborative cloud computing environment; this architecture can provide trust computing and personalized resource matchmaking capacities. Then, a resource clustering method is proposed based on the multidimensional properties of cloud resources; this method can accurately, quickly meet the personalized requirements of users. Finally, an innovative algorithm is proposed for the trust computing of service resources based on real-time and dynamic monitoring of data, thereby quickly and effectively providing trust-aware resource matchmaking. Different from existing methods, which focus only on QoS and trust issues, our approach adds a resource clustering step before QoS and trust evaluation. Three key components are organically combined, namely, service broking architecture, resource clustering, and security and QoS-related trust computing. To the best of our knowledge, this paper is the first to construct an integrated solving scheme for cloud resource matchmaking that can simultaneously satisfy the trustworthiness and personalization required by users. Theoretical and experimental results verify the effectiveness of the proposed scheme.

QoS Prediction for Neighbor Selection via Deep Transfer Collaborative Filtering in Video Streaming P2P Networks

To expand the server capacity and reduce the bandwidth, P2P technologies are widely used in video streaming systems in recent years. Each client in the P2P streaming network should select a group of neighbors by evaluating the QoS of the other nodes. Unfortunately, the size of video streaming P2P network is usually very large, and evaluating the QoS of all the other nodes is resource-consuming. An attractive way is that we can predict the QoS of a node by taking advantage of the past usage experiences of a small number of the other clients who have evaluated this node. Therefore, collaborative filtering (CF) methods could be used for QoS evaluation to select neighbors. However, we might use different QoS properties for different video streaming policies. If a new video steaming policy needs to evaluate a new QoS property, but the historical experiences include very few evaluation data for this QoS property, CF methods would incur severe overfitting issues, and the clients then might get unsatisfied recommendation results. In this paper, we proposed a novel neural collaborative filtering method based on transfer learning, which can evaluate the QoS with few historical data by evaluating the other different QoS properties with rich historical data. We conduct our experiments on a large real-world dataset, the QoS values of which are obtained from 339 clients evaluating on the other 5825 clients. The comprehensive experimental studies show that our approach offers higher prediction accuracy than the traditional collaborative filtering approaches.

Quality Analysis for Web Services Recommendation Using Functional and Non-Functional Requirement

WS Recommendation is challenging job due to its dynamic behavior in QoS. This document explains the various web services that are provided on the internet, how they are implemented, the protocols used in order to invoke these ws, the architecture & lifecycle of ws. The document also elucidates the various Quality analysis parameters and states the quality metrics that are available in order to evaluate the QoS. The evaluation of QoS is very important for the recommendation of web services. In this document, grading or ranking of QoS is done in order to recommend web services. The formulas for computation of rank of QoS has been analyzed and deduced in this documentation. The order in which QoS is ranked, WS is recommended to the user or clients accordingly. The formulas computed in this document are more efficient and clear in terms of factors included.

A NEW QoS GUARANTEE SLA BASED-SCHEME FOR HANDOFF CALLS IN WIRELESS NETWORKS

The most important thing is guarantee QoS over wireless infrastructures. The efficient of service level agreement (SLA) is becoming increasingly important to both service providers and customers. This paper presents some traffic control schemes for improving QoS, trafficmodel and performance evaluation are described. We are defining a new scheme for improving handoff call performances in wireless networks, a finite queuing scheme for the handoff calls. SLA measurement calculates the packet delay parameter (PD) of handoff calls. The handoff calls will be accepted into queue if their PD will be smaller than the average waiting time of the queue. Important performance measures of the suggested scheme such as the blocking probability of new call and dropping probability of handoff call are described and evaluated.

Evaluation of QoS in RF/Li-Fi hybrid networks on 5th generation environments

This paper evaluates the most relevant scenarios in which establishing QoS parameters on RF/Li-Fi hybrid networks is necessary. The objective is to determine the improvement possibilities provided by this technology and realistically value its development potential, specifically for services in real time. We reviewed the alternatives in Internet of Things (IoT), applications, load balancing, scenarios of 5th generation, wireless sensors, and security, in addition to simulations and architectures of technology interoperability.

Accurate modeling and efficient QoS analysis of scalable adaptive systems under bursty workload

An accurate modeling of the workload variability and burstiness phenomena.Stochastic models of the most important features of workload in adaptive systems.We develop an efficient procedure for QoS analysis of self-adaptive systems. Fulfillment of QoS requirements for systems deployed in the Internet is becoming a must. A widespread characteristic of this kind of systems is that they are usually subject to highly variable and bursty workloads. The allocation of resources to fulfill QoS requirements during the peak workloads could entail a waste of computing resources. A solution is to provide the system with self-adaptive techniques that can allocate resources only when and where they are required. We pursue the QoS evaluation of workload-aware self-adaptive systems based on stochastic models. In particular, this work proposes an accurate modeling of the workload variability and burstiness phenomena based on previous approaches that use Markov Modulated Poisson Processes. We extend these approaches in order to accurately model the variations of the workload strongly influence the QoS of the self-adaptive system. Unfortunately, this stochastic modeling may lead to a non tractable QoS analysis. Consequently, this work also develops an efficient procedure for carrying out the QoS analysis.

Knowledge based differential evolution for cloud computing service composition

Web service composition problem has been a hot topic recently. With the development of cloud computing technology, a single Web service can no longer meet the users’ requirement. However, service composition gives a proper way to solve this problem. A knowledge based differential evolution algorithm for Web service composition was proposed in this paper. Firstly, we introduce QoS evaluation models, and propose the mathematical model of QoS applied to Web service composition optimizing problem. Secondly, we present a knowledge based differential evolution algorithm used to solve Web service composition optimizing problem. The algorithm improves the accelerate convergence velocity by importing structure knowledge. Finally, simulation experiments and evaluation methodology are given, and the results prove KDE has better performance in Web service composition problem, compared with original DE, PSO.

QoS and SLA Aware Web Service Composition in Cloud Environment

As a service-oriented paradigm, web service composition has obtained great attention from both academia and industry, especially in the area of cloud service. Nowadays more and more web services providing the same function but different in QoS are available in cloud, so an important mission of service composition strategy is to select the optimal composition solution according to QoS. Furthermore, the selected composition solution should satisfy the service level agreement (SLA) which defines users’ request for the performance of composite service, such as price and response time. A composite service is feasible only if its QoS satisfies user’s request. In order to obtain composite service with the optimal QoS and avoid SLA violations simultaneously, in this paper we first propose a QoS evaluation method which takes the SLA satisfaction into account. Then we design a service selection algorithm based on our QoS evaluation method. At last, we put forward a parallel running strategy for the proposed selection algorithm. The simulation results show that our approach outperforms existing approaches in terms of solutions’ optimality and feasibility. Through our running strategy, the computation time can be reduced to a large extent.