Quality Of Service Evaluation Model Research Articles

Green Energy Strategic Management for Service of Quality Composition in the Internet of Things Environment

With the rapid development of Internet of Things (IoT) technology, the energy consumption of service composition in the IoT environment is a key problem to be studied. At present, the problems of service composition in the IoT environment mostly focus on the evaluation research based on quality of service (QoS), ignoring the overall energy consumption in the process of dynamic configuration of service composition. Therefore, we construct the service composition structure for the IoT and propose the QoS evaluation model and energy evaluation model for the service composition in the IoT environment. Considering that the service composition in the Internet of things environment is NP hard, moth algorithm (MFO) is successfully applied to the QoS evaluation model and energy evaluation model. The simulation results reveal that MFO has good optimization effect in the abovementioned models, and the optimization effect of MFO is improved by 8% and 6% compared with the genetic algorithm and particle swarm optimization, so as to realize the green energy strategic management of QoS composition in the environment of IoT.

The Evaluation Model of Network QoS Based on Intelligent Water Droplets Algorithm

In order to solve the problem of the user demands to the quality of service (QoS) of network, this paper provides a novel QoS evaluation model based on the intelligent water droplets (IWD) algorithm. The model firstly gives the evaluation indexes of network QoS and establishes a multiobjective optimization function for solution in combination with the improved IWD. Then, mathematical simulation is used to conduct the in-depth study of the key factors influencing the evaluation model. Compared with the other methods, the algorithm has shown better adaptability in the simulation results.

QoS evaluation model based on intelligent fuzzy system for vehicular ad hoc networks

Supporting the Quality of Service (QoS) for broadcasting techniques in Vehicular Ad hoc NETetworks (VANETs) is a primordial concern. Qualitatively, QoS is an aspect reflecting the network performance, but quantitatively, it is a function of multiple parameters such as end-to-end delay, packet loss ratio and overhead. These parameters are changing over time and according to adopted protocols. Therefore, it is very difficult to estimate with a crisp value the system QoS. Besides, there is a lack of technical tools for modelling, measuring and comparing the level of QoS performed by different broadcasting protocols under different network constraints. This paper proposes FUZZYVAN-QoS a holistic model based on a fuzzy system simplifying this problem and going through discussing its dependency on different Vehicular Ad hoc NETtwork (VANET) services and applications types. Then, we use a case study; applied on multiple VANET broadcasting protocols, to illustrate the effectiveness of the proposed model.

Service quality measurement model integrating an extended SERVQUAL model and a hybrid decision support system

One of the most effective solutions to sustain an organization in competitive environments is the strategy of continuous improvement. Consequently, the proposed strategy needs a continuous performance evaluation measurements. A solution to evaluate service quality measurements is to rank the service providers. The ranking procedure in similar complex problems or selection problems can be efficiently implemented with the support of multiple attribute decision making (MADM) methods. This study aims at developing a comprehensive decision support system (DSS) based on multiple MADM methods along with an extended quality of service evaluation model to assess the service quality of certain cultural centers. The suggested service quality measurement model in this study is recognized as a valid and reliable tool based on statistical modeling and validation methods. Moreover, the suggested DSS model has been developed based on integration of target-based F-MULTIMOORA and Fuzzy Axiomatic Design (FAD) methods combined with the best-worst method (BWM). Accordingly, a case study was investigated regarding the assessment of seven art galleries in Tehran, Iran. Ultimately, an extensive managerial investigation of the DSS model has been presented based on the real-world examples to show the practicality of the propositions of the current study.

Deep-Q-Network-Based Multimedia Multi-Service QoS Optimization for Mobile Edge Computing Systems

By offloading storage and computing resources to the edge of networks, mobile edge computing (MEC) is emerged as a promising architecture to reduce the transmission delay and bandwidth waste for mobile multimedia services. This paper focuses on a multi-service scenario in the MEC systems, where the MEC server can provide three multimedia services including live streaming, buffered streaming and low latency enhanced mobile broadband applications for edge users at the same time. In order to satisfy various quality of service (QoS) requirements for different multimedia applications, the 5G QoS model is applied. Notably, the packets from the multimedia applications with the same or similar requirements are mapped into the same QoS flow, and each QoS flow is processed individually. Therefore, how to effectively schedule the limited radio resource for QoS flows is an intractable problem. To address the problem above, a QoS evaluation model is designed, and a QoS maximization problem is formulated. Furthermore, a deep reinforcement learning method, deep-Q-network, is adopted to make decisions to allocate radio resource dynamically. Compared with round-robin and priority-based scheduling algorithms, the simulation results validate that the proposed algorithm outperforms other resource scheduling algorithms for multi-service scenario.

A Rational Exchange Protocol under Asymmetric Information in Wireless Sensor Networks

P2P network is one of the most extensive network frameworks for wireless sensor network (WSN) in Internet of Things (IoT). The peers in WSN are rational and often free ride to save power of electricity and calculation, due to the fact that the usability is of great variability and unpredictability. Such a phenomenon tremendously reduces the quality of service (QoS) in WSN. Rational exchange protocol aims at promoting QoS and guaranteeing security and fairness. However, existing schemes have taken only complete information into account, which is not up to realistic environment. The peers in realistic environment indeed possess incomplete information, which is, however, still not thoroughly investigated so far. In this paper, under asymmetric information (a typical incomplete information), an entropy based incentive model is well designed based on Markov model and QoS evaluation model to help peers cooperate in WSNs. A concrete utility function with entropy is constructed to evaluate decision utility in P2P network. Finally, an entropy based rational exchange protocol is proposed based on the presented incentive model and concrete utility function, with analysis of correctness, security, fairness, and robustness, respectively. The proposed protocol can facilitate rational peers positively and sensibly participating in services and prevent free riding for rational peers. Hence, it further promotes QoS and guarantees security and fairness simultaneously in WSNs.

Manufacturing service composition method based on networked collaboration mode

“Cluster Supply Chains” (CSCs) are a new type of business mode, which can help small- and medium-sized enterprises (SMEs) to respond to the changing market demands effectively through networked collaboration. As a large number of manufacturers start to adopt the emerging services paradigm, various cross-enterprise business collaborations in CSC can be deemed as the manufacturing service composition (MSC). However, existing web service composition methods are not appropriate for satisfying the specific demands of manufacturing services composition. The reason lies in two aspects: (1) Current Quality of Service (QoS) model cannot consider the horizontal collaboration between manufacturing services, which may ignore a lot of potential candidate services; (2) current methods are not good at dealing with the rapid increase of candidate service set, which need to be improved further in the searching capability. To solve the above problems, this paper first proposes the new QoS evaluation model of manufacturing service composition according to the networked collaboration pattern in CSC; secondly, the Genetic-Artificial Bee Colony (G-ABC) algorithm is proposed to enhance the performance of searching for the optimal solution based on the available horizontal composite service; finally, the effectiveness of the above solutions is validated through simulation experiments and the results are satisfactory.

Autonomous evolution of service system in cluster supply chain

Purpose – The purpose of this paper is to provide strong theoretical and technical support for the dynamic evolution of service system in “Cluster Supply Chain”(CSC), which can deal with two kinds of context changes: the internal service component changes and the external customer requirement changes. Design/methodology/approach – A “feedback-based” evolution mechanism of service system for CSC is proposed in this study. By means of the feedback update of enterprise service’s Quality of Service (QoS) attribute and the adjustment of the assumed QoS evaluation model, the evolution of service system can be achieved to suit the dynamic market demands. Findings – Results of the study suggest: by means of the “feed-back” evolution mechanism of service system, the enterprises in CSC can handle the context changes effectively to maintain the optimized operation status. Practical implications – The implementation of evolution mechanism in service system can keep the effectiveness of enterprise service composition to face the frequent service component changes and the unpredictable market turbulence. Originality/value – This paper proposes a method to realize the autonomous evolution of service system in CSC, which can support the flexibility and adaptability of enterprise service composition in the changing environment.

An adaptive failure detector based on quality of service in peer-to-peer networks.

The failure detector is one of the fundamental components that maintain high availability of Peer-to-Peer (P2P) networks. Under different network conditions, the adaptive failure detector based on quality of service (QoS) can achieve the detection time and accuracy required by upper applications with lower detection overhead. In P2P systems, complexity of network and high churn lead to high message loss rate. To reduce the impact on detection accuracy, baseline detection strategy based on retransmission mechanism has been employed widely in many P2P applications; however, Chen's classic adaptive model cannot describe this kind of detection strategy. In order to provide an efficient service of failure detection in P2P systems, this paper establishes a novel QoS evaluation model for the baseline detection strategy. The relationship between the detection period and the QoS is discussed and on this basis, an adaptive failure detector (B-AFD) is proposed, which can meet the quantitative QoS metrics under changing network environment. Meanwhile, it is observed from the experimental analysis that B-AFD achieves better detection accuracy and time with lower detection overhead compared to the traditional baseline strategy and the adaptive detectors based on Chen's model. Moreover, B-AFD has better adaptability to P2P network.

A QoS Evaluation Model in the Environment of Cloud Computing

As the name implies, the quality of service（QoS） often reflects the service consumer satisfaction with the services provided by the service provider. In computer systems, particularly in the computer network system, as the providers of the computing and information services, It is necessary to consider the cloud user’s suitability in the process of different physical implementation in the same functional service when constructing the server cluster in the cloud. This paper is for the cloud, build a service quality model oriented user request and the implementation process, completed the choice for the physical implementation with the best users fit service.

MODM-Based Evaluation Model of Service Quality in the Internet of Things

The Internet of Things (IOT) which is considered to be the next step of the revolution of internet lets us transform everyday objects into smart objects that can understand and react to their environment. For achieving the intelligent service provision in IOT environment depending on the context resource, a mechanism for Quality of Service (QoS) management which can analyze the contexts and employ methods to evaluate QoS is greatly needed. In this paper, a multi-objective decision making (MODM) based evaluation model of service quality is proposed. Both the resource state and the user preferences are taken into consideration in order to improve the reasonableness of the QoS evaluation model. The calculated result of the proposed model can act as a metric for service evaluation and selection. © 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [name organizer]

QOS evaluation model for a campus-wide network: an alternative approach focussing on availability

This paper discusses a model for evaluating the quality of service (QOS) of a campus-wide network. The main goal is to achieve a mathematical model that can be applied to any network, providing its availability. The network where it will be tested has more than 5000 nodes with SNMP managed network devices. The model discards the classical approach to QOS that considers parameters such as delay or jitter. Instead, we evaluate quality as a function of the availability indexes for either the services or the network itself. Once the model is described, we will explain how it has been implemented at the Universitat Autònoma de Barcelona Campus network and the requirements––software and hardware––to install such a system in any network.