虚拟计算环境中的可扩展分布式资源信息服务

基于网络资源的"成长性"、"自治性"和"多样性",近年来,人们提出以通用DHT(distributed Hash table)信息服务的形式实现网络资源信息的发布和查询.然而,现有的资源信息服务在通用性、易用性和自适应性等方面仍存在不足.针对虚拟计算环境iVCE(Internet-based virtual computing environment)的资源聚合需求,提出构建可扩展的分布式资源信息服务SDIRIS(scalable distributed resource information service).首先,提出采用自适应DHT(adaptive FissionE,简称A-FissionE)底层架构,以对上层应用透明的方式适应不同的系统规模和稳定性;其次,基于自适应DHT提出高效的多属性区间搜索算法(multiple-attribute range FissionE,简称MR-FissionE).理论分析和模拟结果表明,SDIRIS能够高效地实现资源信息的发布与查询功能.     

一种自组织资源发现模型和算法

针对具有动态性和不稳定性资源的网格计算环境的资源发现问题,提出一种基于资源索引节点的自组织资源发现模型,该模型采用了基于组的分层资源组织方式,通过信息节点管理组内资源信息,所有信息节点形成树型覆盖网络,可以在信息节点树型覆盖网络实现分布式资源定位.并提出以资源索引节点索引所有信息节点中资源的关键属性,设计了基于资源索引节点的智能资源发现算法,实验结果表明,该算法在系统负栽变化情况下,能保持稳定的性能,相比集中式资源发现算法、结构化P2P资源发现算法和分布式资源算法性能更优.     

对等式协同设计系统数据一致性研究

为解决分布式协同设计系统中的异地编辑一致性及多副本同步等问题,提出基于分布式哈希表(DHT)的分布式互斥算法,给出该算法的实现方法。通过采用DHT化的优先队列解决了异地编辑一致性操作问题。将传统的“锁”算法扩展为“对等锁”,解决了多副本同步问题。实验结果表明,该算法的复杂度远低于其他算法,从而验证了该方法的有效性。     

实现一个基于元数据的P2P系统

分布式散列表(DHT)是现有结构化P2P系统普遍采用的一种方法,它能将资源的唯一标识映射到资源位置,Tapestry就是一个基于DHT的基础平台.资源共享是P2P技术应用较广的一个领域.本文以一类典型的带有元数据的资源MP3音乐文件为例,介绍了在Tapestry基础上实现一个基于元数据的P2P资源共享系统MPIS的详细过程,它能够根据资源的多个属性来定位所需资源.     

一种基于分层云对等网络的多属性云资源区间查找算法

为了研究多维属性云资源在云对等网络中快速定位问题,结合云对等网络的优势,提出了一种基于云对等网络的多属性云资源的查找算法。在分层云对等网络的基础上,分别利用云资源的类型和属性值建立多维索引。首先根据类型索引将相关的数据聚集在同一个资源簇内;然后将属性值的值域划分为多个区段,并将相应资源存储其中。同时建立资源簇融合、区间邻居维护等机制使算法更具效率和扩展性。仿真实验表明,该算法实现了多属性云资源的快速定位。并且它不会随着网络节点和类型维度增加而产生较大查询迟延,具有很好的扩展性。     

一种基于分布式哈希表的混合对等发现算法

使用分布式哈希表(distributed hash table,简称DHT)的应用系统必须在O(1)发现算法和O(logN)发现算法系列中选择适应的DHT协议.但是,不同网络波动程度的应用场景要求理想的DHT协议根据网络波动率能够自适应地调整.提出一种发现算法ROAD(routing on active and demand),在延时和波动率之间自适应地调整以提供更好的性能.设计ROAD的关键挑战是构建路由表和降低延时的算法.通过构建加速路由表,加快发现服务的速度,降低消息转发的延时,并通过幂次序组播算法     

基于改进DHT算法的分布式资源发现模型的研究*

为了解决大型分布式系统由集中管理导致的扩展性和鲁棒性差的问题,利用改进的结构化对等网组织分布式计算资源,构造一个SRDM（scalable resource discovery model,可扩展资源发现模型）。SRDM将逻辑空间中的节点分为主机节点和资源节点。主机节点对应分布式环境中的计算节点,用于存储peer关联信息,通过相容性hash映射到逻辑空间上;资源节点对应分布式环境中资源属性信息,其与逻辑空间的映射通过分段hash再合并的方法得到。通过对属性值采用位置保留hash方法,使改进后的DHT算法支持有效的资源节点范围查询和多属性范围查询。最后通过实验证明,基于改进DHT算法的资源发现方法比集中式的方法有更好的扩展性,更适用于大规模分布式系统下的资源发现。     

基于分布式范围树的结构化P2P多维范围查询

基于分布式哈希表（DHT）的结构化P2P网络具有扩展性好、健壮和自组织等优点,但只支持精确匹配的查询.本文提出一种基于分布式范围树的结构化P2P范围查询方法（DRT-RQ）,该方法将多维索引的分布式范围树分发到已有的结构化DHT覆盖网络中,利用DHT系统提供的数据查找接口,有效实现数据对象的范围查询.实验结果表明,基于分布式范围树的范围查询（DRT-RQ）比基于前缀哈希树的范围查询（PHT-RQ）需要更短的查询延时.     

基于路由收敛性检验的DHT安全寻径

为降低恶意节点对基于分布式哈希表(DHT)的结构化对等网络寻径造成的危害,对多种DHT寻径算法进行分析,得到一般DHT协议寻径算法的迭代函数。通过对迭代寻径函数的分析,归纳出恶意节点的共同特征,提出基于下一跳路由收敛性检测的DHT安全寻径模型SDRM。依据该模型设计基于Chord的安全寻径协议CSDSR,并通过模拟实验验证CSDSR的可行性。     

一种基于张量理论的云制造资源服务化封装与发布策略

针对云计算环境下智能制造集中资源分散服务过程中存在的数据异构与资源统一描述问题,在分析现有云制造资源服务化封装与发布技术的基础上,利用张量理论在描述异构数据上的技术特点,提出了一种基于张量理论的云资源服务化封装与发布策略。首先将云制造资源进行分类,并就不同资源给出封装方法;其次基于张量理论定义了不同类型的云制造资源的张量模型,根据不同资源服务属性建立低阶子张量,然后利用张量扩展算子对低阶子张量子进行融合,将各类属性信息嵌入至高阶张量空间,实现云制造资源的统一表示。给出了制造资源、制造能力、设计资源的统一封装模板和形式化描述。最后,给出了云制造资源的服务化部署及发布策略,设计开发了一个云制造资源服务化封装与发布系统,通过实例验证了所提方法的有效性。     

A cost‐efficient resource provisioning algorithm for DHT‐based cloud storage systems

Personal cloud storage provides users with convenient data access services. Service providers build distributed storage systems by utilizing cloud resources with distributed hash table (DHT), so as to enhance system scalability. Efficient resource provisioning could not only guarantee service performance, but help providers to save cost. However, the interactions among servers in a DHT‐based cloud storage system depend on the routing process, which makes its execution logic more complicated than traditional multi‐tier applications. In addition, production data centers often comprise heterogeneous machines with different capacities. Few studies have fully considered the heterogeneity of cloud resources, which brings new challenges to resource provisioning. To address these challenges, this paper presents a novel resource provisioning model for service providers. The model utilizes queuing network for analysis of both service performance and cost estimation. Then, the problem is defined as a cost optimization with performance constraints. We propose a cost‐efficient algorithm to decompose the original problem into a sub‐optimization one. Furthermore, we implement a prototype system on top of an infrastructure platform built with OpenStack. It has been deployed in our campus network. Based on real‐world traces collected from our system and Dropbox, we validate the efficiency of our proposed algorithms by extensive experiments. Copyright © 2016 John Wiley & Sons, Ltd.     

基于SkipNet支持多属性范围查询的云资源共享设计

在云资源共享服务模式中,针对云资源多属性范围查询的问题,提出一种改进的E-SkipNet网络。首先,E-SkipNet在传统分布式哈希表(DHT)网络SkipNet的基础上将数据属性引入到节点NameID的设置中,将物理节点加入到单个属性域中,以支持多属性范围查询;其次,在原E-SkipNet网络的基础上,将物理节点同时映射成多个逻辑节点;同时加入多个属性域,并将资源按照不同的属性发布到不同逻辑节点上;最后,采用均匀位置保留哈希函数对资源进行映射存储,从而在各个属性域中保留属性值的顺序关系,从而支持范围查询。仿真结果表明,改进后的E-SkipNet网络与改进前的E-SkipNet和多属性可寻址网络(MAAN)相比,在路由效率方面分别提高了18.09%和20.47%。结果表明,改进后的E-SkipNet网络能支持更加高效的云资源多属性范围查询,在异构环境中能较好地实现负载均衡。     

云制造环境下基于SVM的加工设备资源分类研究

云制造资源的有效分类是资源服务化封装及后续制造资源服务检索的前提条件,针对高维度特征、多类别加工设备资源的分类问题。依据描述云制造加工设备资源属性特征的XML文档,提取资源属性特征并进行向量化处理。基于SVM算法建立制造资源自动分类预测算法模型,引入SMO算法提升SVM分类算法的分类效率,并利用网格搜索寻求SVM算法的最优参数从而优化SVM算法效果。最后基于某设备资源集的原始设备信息对不同加工设备进行分类实验,验证了该分类模型的有效性以及可行性。     

基于业务预测的云资源动态调度人工智能 方法及系统研究

With the continuous development of the payment market, the data structure characteristics of new business forms such as mobile Internet have changed significantly, and intelligent cloud data center is the general trend of development in the current indus- try. This paper proposes an artificial intelligence method and system design for dynamic scheduling of cloud resources based on busi- ness prediction. The resource availability of daily physical machines has changed over time, and it is necessary to reintegrate the re- sources in order to save energy and meet the requirements of service. In the early stage of large-scale marketing, capacity analysis is combined to make prediction in advance, and intelligent multi-dimensional capacity decision expansion based on artificial intelli- gence and machine self-learning is adopted. The dynamic migration and integration method of virtual machines in cloud data centers with high energy efficiency provides a new solution for improving energy efficiency of cloud computing data centers, ensuring sys- tem reliability and reducing operation and maintenance costs of cloud data centers.     

A collaborative and integrated platform to support distributed manufacturing system using a service-oriented approach based on cloud computing paradigm

Today's manufacturing enterprises struggle to adopt cost-effective manufacturing systems. Overview of the recent manufacturing enterprises shows that successful global manufacturing enterprises have distributed their manufacturing capabilities over the globe. The successes of global manufacturing enterprises depend upon the entire worldwide integration of their product development processes and manufacturing operations that are distributed over the globe. Distributed manufacturing agents' collaboration and manufacturing data integrity play a major role in global manufacturing enterprises' success. There are number of works, conducted to enable the distributed manufacturing agents to collaborate with each other. To achieve the manufacturing data integrity through manufacturing processes, numbers of solutions have been proposed which one of the successful solutions is to use ISO 10303 (STEP) standard. However, adopting this standard one can recognize antonym effects of integration and collaboration approaches that weaken both integration and collaboration capabilities of manufacturing agents. In our latest work, we had developed an integrated and collaborative manufacturing platform named LAYMOD. Albeit the platform in question was through enough to be applied in various collaborative and integrated CAx systems, its embedded structure hampers its application for collaboration in distributed manufacturing systems. To achieve an integrated and collaborative platform for distributed manufacturing agents, this paper proposes a service-oriented approach. This approach is originated from cloud computing paradigm known as one of the technologies which enables a major transformation in manufacturing industry. Also, to maintain the product data integration based on the STEP standard, a new service-oriented approach is proposed. This approach is in parallel to the new capability of the STEP standard for supporting XML data structures. The result is a new platform named XMLAYMOD. XMLAYMOD is able to support distributed manufacturing collaboration and data integration based on the STEP standard. The different aspects of this platform to fulfill the requirements of distributed collaboration and also to overcome the lacks of the STEP standard are discussed through a brief case study.     

基于云计算的政府信息资源协同共享及实现途径

云计算的应用为政府信息资源协同与共享带来了新思路,文章分析了基于云计算的政府信息资源开发的环境和特征。梳理了其协同开发的体系架构和业务逻辑。在总结基于云计算的信息资源开发利用的最新进展基础上,就政府部门如何推动信息资源社会化开发提出了政策建议。     

A flabellate overlay network for multi-attribute search

Peer-to-peer (P2P) technology provides a popular way of distributing resources, sharing, and locating in a large-scale distributed environment. However, most of the current existing P2P systems only support queries over a single resource attribute, such as file name. The current multiple resource attribute search methods often encounter high maintenance cost and lack of resilience to the highly dynamic environment of P2P networks. In this paper, we propose a Flabellate overlAy Network (FAN), a scalable and structured underlying P2P overlay supporting resource queries over multi-dimensional attributes. In FAN, the resources are mapped into a multi-dimensional Cartesian space based on the consistent hash values of the resource attributes. The mapping space is divided into non-overlapping and continuous subspaces based on the peer’s distance. This paper presents strategies for managing the extended adjacent subspaces, which is crucial to network maintenance and resource search in FAN. The algorithms of a basic resource search and range query over FAN are also presented in this paper. To alleviate the load of the hot nodes, a virtual replica network (VRN) consisting of the nodes with the same replicates is proposed for replicating popular resources adaptively. The queries can be forwarded from the heavily loaded nodes to the lightly loaded ones through VRN. Theoretical analysis and experimental results show that FAN has a higher routing efficiency and lower network maintenance cost over the existing multi-attribute search methods. Also, VRN efficiently balances the network load and reduces the querying delay in FAN while invoking a relatively low overhead.     

A Read-Only Distributed Hash Table

A distributed hash table (DHT) is an infrastructure to support resource discovery in large distributed systems. In a DHT, data items such as resources, indexes of resources or resource metadata, are distributed across an overlay network based on a hash function. However, this may not be desirable in commercial applications such as Grid and cloud computing whereby the presence of multiple administrative domains leads to the issues of data ownership and self-economic interests. In this paper, we present R-DHT (Read-only DHT), a DHT-based resource discovery scheme without distributing data items. To map each data item back onto its resource owner, a physical host, we virtualize each host into virtual nodes. Nodes are further organized as a segment-based overlay network which increases node failure resiliency without replicating data items. We demonstrate the feasibility of our proposed scheme by presenting R-Chord, an implementation of R-DHT using Chord as the underlying overlay graph, with lookup and maintenance optimizations. Through analytical and simulation analyses, we evaluate the performance of R-DHT and compare it with traditional DHTs in terms of lookup path length, resiliency to node failures, and maintenance overhead. Overall, we found that R-DHT is effective and efficient for resource indexing and discovery in large distributed systems with a strong commercial requirement.     

容器云多维资源利用率均衡调度研究

在OpenShift容器云平台上针对其调度策略进行研究和改进,提出了基于多维资源空闲率权重的评价函数和调度方法。该方法综合考虑物理节点CPU、内存、磁盘、网络带宽空闲率和已部署的容器应用个数等因素,利用模糊层次分析法（fuzzy analytic hierarchy process,FAHP）自动建模求解容器应用多维资源权重参数。实验表明,新的调度方案能够使集群多维资源利用率更加均衡,从而提升资源的利用率和集群性能。