Quality of Service and Security on Cisco Network Devices, Coupled with the Development of a Mobile Application Prototype Software for Server Room Temperature Monitoring

In an era where digital technology is paramount, higher education institutions like the University of Zambia (UNZA) are employing advanced computer networks to enhance their operational capacity and offer cutting-edge services to their academic fraternity. Spanning across the Great East Road campus, UNZA has established one of the most extensive computer networks in Zambia, serving a burgeoning community of over 20,000 active users through a Metropolitan Area Network (MAN). However, as the digital landscape continues to evolve, it is besieged with burgeoning challenges that threaten the very fabric of network integrity—cyber security threats and the imperatives of maintaining high Quality of Service (QoS). In an effort to mitigate these threats and ensure network efficiency, the development of a mobile application to monitor temperatures in the server room was imperative. According to L. Wei, X. Zeng, and T. Shen, the use of wireless sensory networks to monitor the temperature of train switchgear contact points represents a cost-effective solution. The system is based on wireless communication technology and is detailed in their paper, “A wireless solution for train switchgear contact temperature monitoring and alarming system based on wireless communication technology”, published in the International Journal of Communications, Network and System Sciences, vol. 8, no. 4, pp. 79-87, 2015 [1]. Therefore, in this study, a mobile application technology was explored for monitoring of temperatures in the server room in order to aid Cisco device performance. Additionally, this paper also explores the hardening of Cisco device security and QoS which are the cornerstones of this study.

基于SDN的卫星网络端到端QoS类映射研究

针对在多个卫星网络域环境下域间协作困难,以及如何在各个卫星网络域内选择合适的QoS类实现端到端QoS类映射的问题,基于软件定义卫星网络架构,首先,提出一种SDN卫星网络域间通信方案,以及面向多QoS类的端到端服务交付数据包处理方法。其次,提出一种基于多准则决策的控制模块。模块利用ELECTRE方法,在ELECTRE方法中通过综合权重法计算出各个卫星网络域内QoS指标相应的权重系数,并且利用ELECTRE方法对每个QoS类的净支配指数进行排序,从而为端到端路径的每个卫星网络域选择合适的QoS类。最后,与现有端到端QoS类映射方案进行比较,仿真结果表明,上述方法在多卫星网络域环境下保证端到端的时延、时延抖动、丢包率和代价。

一种可扩展的Web Service QoS管理框架

Web Service是目前研究界和产业界广泛关注的技术之一.随着Web Service的广泛应用,研究者们普遍认识到,服务的非功能属性,即服务质量(Quality of Service,QoS)是面向服务的应用能否成功的关键因素之一.因此,研究者们尝试从多个角度对QoS相关问题展开了研究.然而,现有工作普遍关注基于QoS的动态服务选择和组装等上层应用技术,而对于如何获取、存储、度量QoS等基础支持技术研究较少,而这些基础性工作对QoS相关的研究工作具有显著的重要性.此外,不同应用领域对Web Service QoS的需求不尽相同,因此,需要有一套灵活的机制支持在QoS模型定义、QoS度量方法、QoS信息采集等方面体现出的领域特性.针对这个问题,文中提出了一个可扩展的Web Service QoS信息管理框架,详细分析了该框架涉及到的重要方法与核心技术,并给出了该框架在北京大学软件构件库系统中的设计决策和方案.最后,介绍了文中框架在一个863计划项目中的应用实例,该实例展示了用户根据其应用的领域需求对本框架进行扩展并进行Web Service QoS管理的方法,从而验证了本管理框架的可扩展性及实用性.

Web services composition with QoS bound based on simulated annealing algorithm

In order to enable quality-aware web services selection in the process of service composition,this paper first describes the non-functional requirements of service consumers and the quality of elementary service or composite service as a quality vector,and then models the QoS（quality of service）-aware composition as a multiple criteria optimization problem in extending directed graph.A novel simulated annealing algorithm for QoS-aware web services composition is presented.A normalizing for composite service QoS values is made,and a secondary iterative optimization is used in the algorithm.Experimental results show that the simulated annealing algorithm can satisfy the multiple criteria and global QoS requirements of service consumers.The algorithm produces near optimum solution with much less computation cost.

基于时间序列分析的Web Service QoS预测方法

通过网络提供服务的Web Service的服务质量会随着网络环境、服务器负载等因素的变化而变化,如何更好地帮助用户选择在未来一段时间内符合服务质量需求的Web Service,是目前服务计算领域中需要解决的关键问题之一。针对上述问题,提出了一种基于时间序列分析的Web Service QoS预测方法,并实现了相应的Web Service QoS自动预测工具。该工具能够根据Web Service的历史QoS数据,有效地预测未来短期内的QoS信息。以17832个Web Service的历史数据为基础,设计了相关实验,并验证了方法的有效性。

QoS驱动的Web services动态计价机制研究

结合Web services的服务质量(QoS)因素和用户经验,对Web services的计价机制进行研究,提出一种QoS驱动的Web services动态计价模型,描述其计价过程,并给出相应的实现算法。通过对模型的简单实现,经测试这一计价模型在准确性和合理性上具有一定优势。

悬停波动对毫米波无人机通信系统QoS的影响研究

毫米波无人机通信是未来通信中一种很有前途的候选者。然而,悬停无人机的随机波动会影响该通信系统的服务质量,并给毫米波无人机通信的应用带来挑战。该文从无人机位置波动对无人机-用户链路质量的影响的角度出发,研究无人机位置波动对空对地毫米波无人机通信系统QoS的影响。以可靠服务概率及覆盖概率作为评估系统QoS的指标,基于随机几何获得QoS评估指标的表达式并通过蒙特卡洛仿真进行验证。结果显示,QoS随无人机波动强度的增加而降低且存在使QoS最大的最优无人机高度,为毫米波无人机通信网的设计与研究提供参考依据。

数字电视信号在IP网络传输中的QoS保障技术应用

数字电视信号对传输质量有着十分严苛的要求,传统网际互连协议(Internet Protocol,IP)网络在提供端到端服务质量(Quality of Service,QoS)保障方面仍面临诸多挑战。对此,分析数字电视信号的业务特点和传输需求,梳理IP网络QoS领域的发展脉络,提出一种端到端QoS保障解决方案的总体架构,从接入网、骨干网、综合管理平台三个层面给出优化措施。

IP承载网中QOS策略的设计与优化

在网络世界中,网际互连协议(Internet Protocol,IP)承载网扮演着信息流动的骨干角色,其运行表现和服务水准至关重要。文章详细探讨了IP承载网中服务质量(Quality of Service,QoS)策略的设计与优化方法,重点涵盖分类服务与标记、流量控制与优先级队列管理以及链路和节点策略的具体实现。通过流量分析与预测、智能资源分配与调度、动态策略调整以及故障检测与容错机制,提出一系列提升网络性能和用户体验的有效措施。

Interactive Web service choice-making based on extended QoS model

Quality of Service (QoS) is a key factor in Web service advertising, choosing and runtime monitoring. Web service QoS is multi-faceted, fuzzy and dynamic. Current researches focus on implementation level performance assurance, ignoring domain specific or application level metrics which are also very important to service users. Industry Web service standards lack QoS expression. The support for QoS based service choice-making is very limited. We proposed an extended Web service QoS model based on configurable fuzzy synthetic evaluation system. Web service QoS is evaluated dynamically according to the service context. A QoS requirement description model is also given for service QoS requirement definition. An interactive Web service choice-making process is described, which takes QoS as a key factor when choosing from functionally equivalent services.

A QoS-aware Method for Web Services Discovery

The non-functional QoS (quality of service) information helps us to select a proper Web-service from the web applications, by using component services such as UDDI[1](Universal Description, Discovery, and Integration) and MDS(Monitoring and Discovery System). MDS is a suite of web services to monitor and discover resources and service on Grids, but MDS only based on function aspects. This paper studies on an approach to provide the QoS information and a discovery model by using MDS and gives a system deployment and implementation plan. The simulation results show that the method is effective in service discovery.

Service allocation based on QoS evaluation in military organization cloud cooperation

The problem of cloud cooperation of military service providers（MSPs） is addressed for allocating limited resources to military service users（MSUs） that are geographically distributed. The MSPs, also called military organization clouds, are virtualized and encapsulated by the services they can offer and each of them contains different kinds of resources that MSU needs. The MSPs are also geographically dispersed. They are required to allocate their resources to the MSU complying with the corresponding quality of service（QoS）, so that each MSU gathers the services it needs to guarantee its task to be implemented. The outline of military organization cloud cooperation is discussed and the method of service optimal selection is proposed based on QoS evaluation. The QoS evaluation method based on exponential approximation is put forward to include the users＇ will. Simulation results verify the effectiveness of the proposed algorithm.

Toward Cloud Computing QoS Architecture:Analysis of Cloud Systems and Cloud Services

Cloud can be defined as a new computing paradigm that provides scalable, on-demand, and virtualized resources for users. In this style of computing, users can access a shared pool of computing resources which are provisioned with minimal management efforts of users. Yet there are some obstacles and concerns about the use of clouds. Guaranteeing quality of service QoS by service providers can be regarded as one of the main concerns for companies tending to use it. Service provisioning in clouds is based on service level agreements representing a contract negotiated between users and providers. According to this contract, if a provider cannot satisfy its agreed application requirements, it should pay penalties as compensation. In this paper, we intend to carry out a comprehensive survey on the models proposed in literature with respect to the implementation principles to address the QoS guarantee issue. © 2014 Chinese Association of Automation.

An approach for QoS measurement and web service selection sureness

Web services have gained popularity m recent years anu prowue a new moue, u~ w^u, w,,,~,, ,^- cilitates interaction of scientific and business applications through the Internet. More often, several services with similar functionality are available from a large and changing number of service provid- ers. Quality of Service （QoS） is the dominant factor in service selection and is of great importance to users. In this paper, we propose a model for QoS measurement and web services selection. The model consists of QoS model, QoS monitoring, QoS comparison and service selection with a QoS feedback mechanism. The most suitable service is to take into account the agreed QoS, monitoring is done during invocation phase and if any deviation is recorded, next suitable service is selected. Fi- nally the model is proved to be feasible and effective by simulation experiments.

Constraint-based QoS-aware Web Service Composition in Cross-organizational Collaboration

To improve the Quality of Service (QoS)-aware Web service compositions considering constraints between cross-organizational business,this paper analyzes the types of constraints,and accordingly proposes a Chaos Genetic Algorithm (CGA). The algorithm creates an initial population of service compositions based on the chaos theory,and then processes individuals which violate constraints in the initial population using repair strategies. Next,a new fitness function is designed to gradually eliminate the infeasible compositions generated in evolution. Finally,the algorithm makes minor chaotic disturbances on the evolved group to accelerate convergence and avoid local optimum. Experimental results demonstrate the effectiveness of the proposed algorithm.

基于服务负载的时序QoS预测

网络技术的发展和多接入边缘计算的兴起使得计算和网络资源的部署逐渐靠近终端.随着服务数量的增多,为了向用户更好地推荐服务,如何在复杂、动态的边缘计算环境中实时、准确地预测服务质量(quality of service,QoS)成为一项挑战.本文提出一种基于服务负载实时预测QoS的深度神经模型(QPSL),它可以为边缘计算中的QoS预测提供缺少的负载状况感知和周期感知.首先,对服务的负载状况进行特征表示,并通过时序分解模块获取时序特征.其次,将CNN和BiLSTM结合,学习潜在的时序关系,生成不同时刻的状态向量.然后,基于Attention机制为历史时刻的状态向量分配权重,从而构造未来时刻的状态向量.最后,将上下文嵌入向量与状态向量送入感知层完成实时QoS预测.基于真实的融合数据集进行了大量的实验,结果表明QPSL在响应时间和吞吐量任务上的MAE分别平均提升了10.28%和10.87%,优于现有的时间感知QoS预测方法.

突发模型下的云服务QoS网络质量保障方法

为研究突发事件下网络的服务质量性能保障措施,重点关注高峰期的QoS网络质量,考虑云计算的技术特征和异构网络服务环境,通过对服务交付系统的服务能力优化,减少大量的网络流量对服务器的阻塞,提出一种突发模型下的云服务QoS保障方法.首先研究了云服务突发流量机制,并对限制流量优化模型性能分析.然后,基于网络演算理论与网络服务融合模型的服务速率和负载进行分析,提出限制突发模型的线上教学服务质量的模型,给出了时延上界的定量解析式为流量优化控制措施提供量化依据.最后通过仿真实验分析了服务速率和负载与时延上界的关系,验证了流量限制突发模型的有效性和可靠性.

A Real Plug-and-Play Fog: Implementation of Service Placement in Wireless Multimedia Networks

Initially as an extension of cloud computing, fog computing has been inspiring new ideas about moving computing tasks to the edge of networks. In fog, we often repeat the procedure of placing services because of the geographical distribution of mobile users. We may not expect a fixed demand and supply relationship between users and service providers since users always prefer nearby service with less time delay and transmission consumption. That is, a plug-and-play service mode is what we need in fog. In this paper, we put forward a dynamic placement strategy for fog service to guarantee the normal service provision and optimize the Quality of Service (QoS). The simulation results show that our strategy can achieve better performance under metrics including energy consumption and end-to-end latency. Moreover, we design a real Plug-and-Play Fog (PnPF) based on Raspberry Pi and OpenWrt to provide fog services for wireless multimedia networks.

BFS-SVM Classifier for QoS and Resource Allocation in Cloud Environment

In cloud computing Resource allocation is a very complex task.Handling the customer demand makes the challenges of on-demand resource allocation.Many challenges are faced by conventional methods for resource allocation in order tomeet the Quality of Service(QoS)requirements of users.For solving the about said problems a new method was implemented with the utility of machine learning framework of resource allocation by utilizing the cloud computing technique was taken in to an account in this research work.The accuracy in the machine learning algorithm can be improved by introducing Bat Algorithm with feature selection(BFS)in the proposed work,this further reduces the inappropriate features from the data.The similarities that were hidden can be demoralized by the Support Vector Machine(SVM)classifier which is also determine the subspace vector and then a new feature vector can be predicted by using SVM.For an unexpected circumstance SVM model can make a resource allocation decision.The efficiency of proposed SVM classifier of resource allocation can be highlighted by using a singlecell multiuser massive Multiple-Input Multiple Output(MIMO)system,with beam allocation problem as an example.The proposed resource allocation based on SVM performs efficiently than the existing conventional methods;this has been proven by analysing its results.

Internet Multimedia Traffic Classification from QoS Perspective Using Semi-Supervised Dictionary Learning Models

To address the issue of finegrained classification of Internet multimedia traffic from a Quality of Service(QoS) perspective with a suitable granularity, this paper defines a new set of QoS classes and presents a modified K-Singular Value Decomposition(K-SVD) method for multimedia identification. After analyzing several instances of typical Internet multimedia traffic captured in a campus network, this paper defines a new set of QoS classes according to the difference in downstream/upstream rates and proposes a modified K-SVD method that can automatically search for underlying structural patterns in the QoS characteristic space. We define bagQoS-words as the set of specific QoS local patterns, which can be expressed by core QoS characteristics. After the dictionary is constructed with an excess quantity of bag-QoSwords, Locality Constrained Feature Coding(LCFC) features of QoS classes are extracted. By associating a set of characteristics with a percentage of error, an objective function is formulated. In accordance with the modified K-SVD, Internet multimedia traffic can be classified into a corresponding QoS class with a linear Support Vector Machines(SVM) clas-sifier. Our experimental results demonstrate the feasibility of the proposed classification method.