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越来越多的应用以云中网络服务的形式在服务提供商的控制下发布出来,但使用这些服务的用户却没有办法判断这些服务是否是可信的。文中通过一个可信管理框架来支持在云计算环境中可信服务的建立,让用户通过一个中立第三方得以获知服务程序的可信度,实现一个可信平台服务。最后在一个支持Python/Django框架的云平台上实现了一个原型系统,让服务提供商得以在封装服务程序实例的同时再向其外部用户证明Python代码的可信度。一旦运行,服务实例可以拥有独立标识并能防止用户篡改其代码。 相似文献
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云计算环境促进了面向服务的分布式应用的发展和Web服务组合的高效实现。文章分析了云计算环境下Web服务组合模型以及工作过程,研究了Web服务组合优化的相关智能优化算法和基于Web服务顺序知识的人工蜂群算法。 相似文献
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运用信任模型进行可信评估是解决分布式网络安全问题的重要手段。然而,目前大部分研究工作把研究重点放在如何收集更完整的信任证据,以及如何利用一些新手段如机器学习、区块链等评估节点信任值,很少对如何获取节点可靠的初始信任值进行研究。实际上,针对分布式网络提出的很多信任模型都依赖于历史信任证据,而初次对网络进行可信评估时并不具备相关历史信息。基于此,该文面向分布式网络环境的安全问题,提出了基于挑战-响应模型的可信评估方法。首先利用挑战-响应模型获取节点可靠的初始信任值,并利用此初始信任值对网络中的节点进行分簇,在簇内进行信任值计算和信任值更新,完成分布式网络环境下完整的可信评估流程。仿真结果表明,相较于统一设置初始信任值的方式,该文所提方法能对恶意节点、自私节点的信任值有较准确的预测,同时对恶意节点的检测率也更高。 相似文献
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提出了一种基于企业行为证据的双滑动窗口的供应商信任量化评估机制,通过不断滑动的窗口,确定窗口更新和替换的内容以保证企业行为信任评估的可信性和可扩展性.仿真实验分析表明,该模型提供了云环境下供应商信任值计算的动态性,评估方法能够有效应用于云环境下供应商的评价中,评价结果客观有效. 相似文献
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混合云提供了一种本地资源不足以向公有云申请资源的灵活做法,但使用哪一个公有云服务或者如何选择公有云服务需要仔细斟酌。提出一种基于SLA约束的云资源调度方案。该方案将向外部云调度的关键SLA度量看作用户的满意度和最低代价,并将这些SLA分量进行量化比较,以动态调整内部云资源无法服务而需要向外调度资源的情况。实验结果表明,该方案能够实现成本和实时性的最大满意度。 相似文献
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可信计算的链式度量机制不容易扩展到终端所有应用程序,因而可信终端要始终保证其动态运行环境的可信仍然困难.为了提供可信终端动态运行环境客观、真实、全面的可信证据,提出了可信终端动态运行环境的可信证据收集机制.首先,在可信终端的应用层引入一个可信证据收集代理,并将该代理作为可信平台模块(trusted platform module,简称TPM)链式度量机制的重要一环,利用TPM提供的度量功能保证该代理可信;然后通过该代理收集可信终端的内存、CPU、网络端口、磁盘文件、策略配置数据和进程等的运行时状态信息,并利用TPM提供的可信存储功能,保存这些状态信息作为终端运行环境的可信证据,并保障可信证据本身的可信性.该可信证据收集机制具有良好的可扩展性,为支持面向不同应用的信任评估模型提供基础.在Windows平台中实现了一个可信证据收集代理的原型,并以一个开放的局域网为实验环境来分析可信证据收集代理所获取的终端动态运行环境可信证据以及可信证据收集代理在该应用实例中的性能开销.该应用实例验证了该方案的可行性. 相似文献
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云计算的安全问题是学界关注的热点,其中虚拟化技术引入和虚拟计算方式转变带来的风险和机遇都对云计算安全提出了新的要求。为了适应云计算环境的高度灵活性和动态可扩展性,传统的安全保护手段需要做出一定改进。文章针对云计算环境虚拟化安全问题,分析并研究了几种云计算环境下基于信任技术的虚拟计算可信模型,并对未来研究方向进行了展望。 相似文献
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近几年,我国科学技术水平有了明显提升,依托互联网、计算机等先进技术形成的"云计算"也更为成熟,服务规模逐渐扩大,为人们生活、工作、学习,以及企业管理、发展等提供了较大便利.虚拟机技术作为云计算的核心技术,如何保证其安全可信启动以及数据安全,成为需要解决的重要问题,对于提高云计算安全性十分重要.本文将结合实际情况,对云环... 相似文献
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为优化IaaS服务的执行效率,提出面向IaaS的信号驱动任务调度算法,该算法根据IaaS模型的结构特征建立控制子系统和节点子系统,根据任务的结构特征建立任务的DAG(directed acyclic graph)调度模型,并建立各任务分片的状态转化机制及控制子系统和节点子系统间的信号通信机制。以系统间信号交互的方式驱动任务分片的状态改变,并在每一调度时刻来临时利用并行优化选择策略分配任务分片。由于本算法采用了模拟IaaS模型的双系统控制方式,使本算法与IaaS模型的分布式体系相兼容且复杂度较低。最后通过实验验证了所提算法的有效性和实用性。 相似文献
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A workflow task scheduling algorithm based on the resources' fuzzy clustering in cloud computing environment 下载免费PDF全文
Fengyu Guo Long Yu Shengwei Tian Jiong Yu 《International Journal of Communication Systems》2015,28(6):1053-1067
Cloud computing is the key and frontier field of the current domestic and international computer technology, workflow task scheduling plays an important part of cloud computing, which is a policy that maps tasks to appropriate resources to execute. Effective task scheduling is essential for obtaining high performance in cloud environment. In this paper, we present a workflow task scheduling algorithm based on the resources' fuzzy clustering named FCBWTS. The major objective of scheduling is to minimize makespan of the precedence constrained applications, which can be modeled as a directed acyclic graph. In FCBWTS, the resource characteristics of cloud computing are considered, a group of characteristics, which describe the synthetic performance of processing units in the resource system, are defined in this paper. With these characteristics and the execution time influence of the ready task in the critical path, processing unit network is pretreated by fuzzy clustering method in order to realize the reasonable partition of processor network. Therefore, it largely reduces the cost in deciding which processor to execute the current task. Comparison on performance evaluation using both the case data in the recent literature and randomly generated directed acyclic graphs shows that this algorithm has outperformed the HEFT, DLS algorithms both in makespan and scheduling time consumed. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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在Min-Min的基础上,针对所存在的缺陷,提出了一种负载均衡的改进算法.仿真实验表明,在一定条件下,改进后的算法比传统的算法有一定的提高. 相似文献
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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. 相似文献
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云工作流调度算法是信息传输和沟通的主要方式。为适应当前活动实践需求,将云计算作为计算机运转调节的主要手段,合理进行云环境下工作调度因素的调节,在探索信息技术沟通渠道创新中发挥着不可忽视的作用。文章结合国内技术分析的基本情况,首先阐述了云工作流调度算法路径研究价值,其次着重从集合式工作调度、单元限制条件分析等方面,探究一种基于动态关键路径的云工作流调度算法要点,以达到明确技术关键条件,促进云工作服务手段调节革新的目的。 相似文献
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Zahra Shokri Baghi Nima Jafari Navimipour 《International Journal of Communication Systems》2023,36(8):e5458
Cloud computing has appeared as a technology allowing a company to employ computing resources such as applications, software, and hardware to calculate over the Internet. Scholars have paid great attention to cloud computing because of its cutting-edge availability, cost decrement, and boundless applications. A cloud database is a data storage site on the web where the optimal path is spotted to access the needed database. So, placing the ideal path to a database is crucial. The cloud database defined the scheduling problem to choose the perfect route. Cloud database path scheduling is a multifaceted procedure consisting of congestion control, routing list, and network flow distribution. It has a postponement in searching for the needed source route from the cloud database. Offering numerous infinite resources with the growing database workload is an NP-Hard optimization problem where the query request needs optimal schedules to respond to the required services. So, we have used a hybrid cuckoo search (CS) and genetic algorithm (GA), motivated by a social bird's phenomenon, to solve this problem. Integrating genetic operators has dramatically enhanced the balance between the capability of searching and utilization. 相似文献
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为了提高云计算任务调度效率,提出一种改进人工免疫算法的云计算任务调度方法。首先建立云计算任务调度的数学模型,并以任务总时间最短作为目标函数,然后采用人工免疫算法进行求解,并将粒子群优化算法作为算子嵌入人工免疫算法中,保持种群的多样性,防止局部最优解的出现,最后采用仿真实验对算法的性能进行测试。结果表明,相对于其它算法,改进人工免疫算法减少了任务的完成时间,提高了用户满意度。 相似文献