云计算环境下基于信任推理的服务评价方法

通过服务直接交互中的服务行为来建立SC与SP实体的信任推理、演化及对SP实体的QoS评价模型。该模型基于概率密度函数来表征服务实体间的信任度,提出了基于概率密度信任关系的计算、推理及合并的演化方法,并给出了依据信任推理与QoS修正的服务评价算法。实验结果表明该方法能有效评价服务参与者的信任度,削弱不可信的实体对服务评价的影响,提高服务选择过程的质量及准确性。     

基于黑白板的信任敏感Web服务组合策略

针对网络中用户难以得到高质量的服务组合问题,提出了一种基于黑白板的信任敏感服务组合策略,通过黑板与白板信任演化模型来帮助用户得到可信的高质量的服务组合.实验结果表明该策略能够克服以往信任演化中直接信任关系稀小、前期信任匮乏的问题,同时,能够有效识别共谋欺骗.     

云计算环境下基于信任演化及集合的服务选择

针对云计算环境中服务节点的可信度参差不齐常导致用户很难获得高质量组合服务的问题,提出了一种基于信任生成树的云服务组织方法,将服务提供者与请求者的交互行为经演化后形成信任关系,使主体间可信程度达到相应级别,形成对外提供相似服务功能的云服务集合,将恶意、虚假的服务排除在信任生成树之外,使服务组合在可信场景中进行;在此基础上,采用了基于信息熵的度量策略来对服务间的信任关系进行评估,解决了现有研究中仅对可信参数进行简单加权分析的不足。实验分析表明,该方法能有效抑制云计算环境下恶意节点的欺诈行为并保护真实节点的合法利益,具有较好的服务选择质量。     

基于差值诱导的Web服务评价可信度的评估

Web 服务的评价信息为服务选择提供了重要的参考依据,但服务评价信息具有主观性。结合客观QoS（服务质量）属性数据及请求者评分数据,采用差值诱导法评估历史评价信息是否可信。首先利用不同服务请求者调用同一服务产生的不同QoS属性数据,判断请求者之间的相似关系;然后基于该相似关系,融入对应请求者的主观评分,依据差值法构造可信度评估算法;最后结合所构造的算法,得出可信度平衡因子,判断请求者的评价是否可信。算法分析以及实验结果表明该方法是可行及有效的。     

无线mesh网络中可信协同信道资源分配策略

为了有效提升无线mesh网络信道资源的利用率和网络服务质量,提出基于可信协同的信道资源分配策略.针对节点自适应特点,引入博弈理论、建立节点的信誉机制以实现节点可信协同并优化信道分配结果.仿真实验分别对节点服务等级、网络收益结果作相应评价.实验结果发现节点服务等级对节点网络收益有直接影响,当协同服务等级达到3时,网络收益状况最佳,此时节点跳数与服务等级呈协同关系;对比经典协同算法,在相同网络拓扑环境下,可信协同信道资源分配策略分别是UACRR算法、DMP-MBA算法的1.04倍、1.069倍,明显占优.     

分布式Web服务QoS注册中的高效负载均衡方法

该文提出了一种分布式Web服务QoS注册系统的负载均衡方法。提出了节点负载状态划分的概念。根据负载状态采用不同的负载信息散布策略,极大地减少了网络消耗。提出了基于简单协商的负载均衡方法。负载均衡用数据复制的方式,主要特点是在进行实际负载均衡操作以前即与复制目标节点进行协商,提出合理的复制需求,然后根据对方提供的资源情况,发起复制。提高了负载均衡的效率,降低了复制的盲目性。该方法在分布式Web服务QoS注册原型系统中进行了实验,达到了较好的效果。     

状态行为关联的可信网络动态信任计算研究

综合实体状态和行为因素,提出一种可信网络动态信任模型.通过进行实体的状态行为关联分析,提取信任信息,深入分析信任与状态和行为之间的关系,并提出基于状态行为关联的实体动态信任计算方法.仿真表明,所提出的信任模型提供实时动态信任,能够有效地发现和处理动态恶意实体策略性的行为改变和恶意攻击.为网络安全机制制定智能安全策略提供一定参考,提高网络可信性能.     

基于最优路径选择的网络感知服务组合算法

为满足用户的性能需求及服务质量保障,针对复杂网络服务组合的特点和用户个性化的服务质量(Quality of Service, QoS)需求,研究了云环境下的网络感知服务组合问题,利用云服务和网络服务的QoS属性,提出了一种基于最优路径选择(Optimal Path Selection, OPS)的网络感知服务组合算法。该算法可以提升网络服务质量水平,改善用户体验质量。仿真结果表明,该算法在求解时间和质量两个方面都表现出了良好的性能,而且能动态适应用户复杂的需求,能够有效地解决云计算环境下的服务组合问题。     

模糊自主信任建立策略的研究

该文首先从分析开放式网络环境中有关信任的问题和主观信任的模糊性入手,以模糊理论为基础,引入隶属度来描述信任的模糊性,解决了模糊信任模型的建模问题;以图论为基础,将网络环境模型化为一个无向图 ,定义了基于本地信息交互的信任评价规则;提出了基于开放式网络环境的模糊自主信任模型,具体研究了自主信任建立策略及建立完全可信网络的实现机制及条件;最后通过仿真实验讨论了网络拓扑结构对自主信任建立的影响,并以小世界网络模型(-model)为基础分析讨论了自主信任建立的速度问题,这为网络管理的研究提供了一个有价值的新思路。     

改进QoS的云服务评价模型

针对云服务具有不确定性与大规模性,传统QoS的云服务评价模型工作机制灵活性不强,回报率低下等问题,设计改进QoS的云服务评价模型,对传统QoS的云服务评价模型的QoS属性项目进行细化,并利用熵值法为各项QoS属性项目进行比重取值。在改进模型的评价过程中,先针对实时数据进行重点评价,再结合以往数据特征对评价结果做出修正,并将修正结果输入未来预测时间,指导下次QoS云服务评价工作,以提高模型可靠性。同时将传统模型资源整体切入形式改为模块化切入形式,增添网络用户反馈机制与QoS监控机制,使评价服务更加完善。实验结果表明,改进QoS的云服务评价模型的服务内容选择性强,更能满足网络用户需求。     

云计算环境下基于评价可信度的动态信任评估模型

针对云用户如何选取可信的云服务提供商问题,提出了基于评价可信度的动态信任评估模型。该模型将云服务提供商的服务能力和云用户所需求的服务能力分别划分等级,有效地解决了云服务提供商服务能力动态变化对模型存在的潜在破坏问题。建立了信任度随时间窗变化的动态信任机制,在计算信誉度时,将用户的评价可信度作为其评价证据的可信权重,通过引入评价可信度和评价相似度提高了计算推荐行为可信度的准确率。仿真结果表明,该模型的评估结果更贴近云服务提供商的真实信任度,同时能有效抵御恶意云用户的攻击。     

Trust expansion and listwise learning-to-rank based service recommendation method

In view of the problem of trust relationship in traditional trust-based service recommendation algorithm,and the inaccuracy of service recommendation list obtained by sorting the predicted QoS,a trust expansion and listwise learning-to-rank based service recommendation method (TELSR) was proposed.The probabilistic user similarity computation method was proposed after analyzing the importance of service sorting information,in order to further improve the accuracy of similarity computation.The trust expansion model was presented to solve the sparseness of trust relationship,and then the trusted neighbor set construction algorithm was proposed by combining with the user similarity.Based on the trusted neighbor set,the listwise learning-to-rank algorithm was proposed to train an optimal ranking model.Simulation experiments show that TELSR not only has high recommendation accuracy,but also can resist attacks from malicious users.     

Web service selection algorithm based on principal component analysis

Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user’s preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user’s QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.     

A cloud service composition method using a trust‐based clustering algorithm and honeybee mating optimization algorithm

One of the most critical issues in using service‐oriented technologies is the combination of services, which has become an important challenge in the present. There are some significant challenges in the service composition, most notable is the quality of service (QoS), which is more challenging due to changing circumstances in dynamic service environments. Also, trust value in the case of selection of more reliable services is another challenge in the service composition. Due to NP‐hard complexity of service composition, many metaheuristic algorithms have been used so far. Therefore, in this paper, the honeybee mating optimization algorithm as one of the powerful metaheuristic algorithms is used for achieving the desired goals. To improve the QoS, inspirations from the mating stages of the honeybee, the interactions between honeybees and queen bee mating and the selection of the new queen from the relevant optimization algorithm have been used. To address the trust challenge, a trust‐based clustering algorithm has also been used. The simulation results using C# language have shown that the proposed method in small scale problem acts better than particle swarm optimization algorithm, genetic algorithm, and discrete gbest‐guided artificial bee colony algorithm. With the clustering and reduction of the search space, the response time is improved; also, more trusted services are selected. The results of the simulation on a large‐scale problem have indicated that the proposed method is exhibited worse performance than the average results of previous works in computation time.     

多策略QoS感知的服务选择与排序模型

随着网络中具有相同功能、不同QoS服务的增多,在用户请求服务时,为了确保能找到满足用户功能与质量要求的服务,并对找到的可用候选服务集按一定的策略进行选优,提出了一种多策略QoS感知的服务选择与排序模型。在该模型中,综合考虑服务的性能与运营维护成本等属性,提出了一个扩展的服务QoS模型,在此基础上引入用户、运营商对服务满意度的计算方法,通过改变用户满意度与运营商满意度在排序选优过程中所占的不同比重,灵活设置服务选优策略,有效的解决了服务排序选优问题。搭建了服务选择与排序原型系统,并通过应用实例对上述模型进行了验证。     

Dynamic Web service selection group decision-making based on heterogeneous QoS models

In open and dynamic Internet environment, multi-periods quality of service (QoS), multiple decision-makers based on heterogeneous QoS models and uncertainty weights make optimal Web service selection hard. To solve the difficulties above, dynamic Web service selection group decision-making based on heterogeneous QoS models (DWSSGD_HQM) is proposed. Drawing on and extending technique for order preference by similarity to ideal solution (TOPSIS), DWSSGD_HQM supports multiple decision-makers based on heterogeneous QoS models expressed in real numbers, interval numbers, triangular fuzzy numbers and intuitionistic fuzzy numbers respectively, and takes multi-periods QoS and weights of user and group into account. Six steps are detailed. They are converting heterogeneous QoS models into ones expressed in interval numbers, calculating weighted normalized decision-matrix, determining the group positive-ideal and negative-ideal solutions, calculating the close-degrees of candidates, aggregating close-degrees of multi-periods for each decision-maker, and ranking the alternatives. Finally, experiments are conducted by using actual QoS data to evaluate the effectiveness of the proposed approach.     

MPLS-Linux体系结构及交换路由性能分析

本文详细介绍了MPLS-Linux的体系结构、核心数据结构、标签交换过程和QoS运行等实现技术，通过对MPLS-Linux组成的交换路由系统进行性能测试和分析，发现：在链路轻载或预留带宽的情况下，交换路由系统对数据流的服务质量优于传统路由系统；只有综合应用策略路由、数据报分类调度和标签交换才能实现Internet环境下对端到端服务质量的控制。     

Web service composition algorithm based on TOPSIS

Independent quality of service(QoS)registration center is difficult to monitor QoS with lots of requests in Internet environment with a large number of services and lots of service requests.It is able to reduce the load and decrease the failure rate by using multiple QoS registration centers to monitor QoS of some services with lots of requests.In addition,the heterogeneous QoS data close to user’s habitual expression and adapts to the environment with complexity and uncertainty.This paper introduces a novel Web service composition algorithm based on technique for order preference by similarity to an ideal solution(TOPSIS)(WSCA_TOPSIS)to solve the above difficulties for the first time.WSCA_TOPSIS can support multiple decision-makers and heterogeneous QoS data.It includes three main steps:normalizing decision matrix,evaluating alternatives synthetically and evaluating group alternatives synthetically.Other contributions of the paper include a novel algorithm of aggregating QoS and a set of experiments that demonstrate the benefits and effectiveness of our approach.Experimental results show that the proposed algorithm can better support Web service composition with heterogeneous QoS data and multiple decision-makers.     

云环境下服务信任感知的可信动态级调度方法

以社会学中的人际关系信任模型为基础,提出了一种基于服务消费者的服务满意度评价、推荐者的服务推荐和第三方服务性能反馈的可信度量模型。将用户对服务资源的信任需求和服务资源的可信度并入DLS算法得到可信动态级调度算法CTDLS,从而在计算调度级别时考虑服务资源的可信程度。模拟实验表明,该算法能有效满足任务在信任方面的服务质量需求,对提高任务调度的成功率具有实际意义。     

一种网格节点信誉评价算法及其在服务网格虚拟组织构建中的应用

 本文提出了一种新的服务网格节点信誉评价算法．通过构建由实体间的直接信任构成的有向加权图,并通过修改经典的Dijkstra算法来计算实体间的推荐信任,结合直接信任刻画实体间的信誉评价,同时,该算法参考虚拟组织发起者对虚拟组织愿景特征的理解,将组织间信任关系以及虚拟组织所需服务或资源的种类作为信誉评价的重要依据,细粒度刻画候选者实体的信誉,从而适合具有自治域的服务网格环境中虚拟组织的构建．仿真实验表明,该算法能够较为真实地反映网格实体间的信任关系,有效遏制不良节点对服务网格系统的危害,对虚假交易攻击以及诽谤攻击均具有较强的抵御能力．