基于MLON结构的资源发现机制

网格资源发现机制是目前网格领域中的一个热点研究问题。本文对已有的网格资源发现方法进行了分析,指出了这些方法存在的不足;提出了一种基于MLON结构的资源发现机制,将具有同一类型资源的网格信息结点组织在一起形成域,把结点数量较多的域通过类型粒度组织成层次形结构。该机制利用类型匹配路由的资源搜索技术将资源发现请求转发
发到资源所在的域,采用Topk技术在相应的域内找出与请求匹配的最佳的k个资源,从而改善了资源发现的性能,提高了用户的满意度。     

Design and implementation of economics-based resource management system in ad hoc grid

The ad hoc grid is a spontaneous organization of cooperating heterogeneous nodes into a logical community without a fixed infrastructure and with only minimal administrative requirements. Resource management for ad hoc grids is challenging due to the participation of heterogeneous, dynamic, autonomous and ephemeral grid nodes. The paper proposes an ad hoc grid resource management system, the producers and consumers of ad hoc grid resource are modeled as the self-interested decision-makers described in microeconomic theory. All market participants in the ad hoc grid environment including grid resources and services can be represented as agents. We apply economic agents to build ad hoc grid resource management, where ad hoc grid resource consumers and providers can buy and sell ad hoc grid resource based on an underlying economic architecture. The main processes involved in ad hoc grid resource management are resource registration, discovery, and resource allocation. The experiments are conducted to compare ad hoc grid resource allocation algorithm with other ad hoc grid resource allocation algorithm. Simulation results show that our proposed algorithm is more efficient than compared allocation scheme.     

符合动态演变特性的网格资源发现机制研究

近年来人们对如何提高网格资源发现效率做了大量的研究,但却忽略了适应网格资源动态演变特性的重要性.针对这一问题,结合小世界理论的网络特征,提出了一种新的基于P2P分布式结构化的网格资源发现机制.通过计算资源节点间属性相似度的方法,将网格资源分类组织在不同的虚拟组织中,结合P2P技术构建出两层覆盖式资源发现模型,并设计出相应的资源查找算法DSRD (distributed structure grid resource discovery).仿真实验结果表明,DSRD算法既能够适应资源的动态特性,同时又可有效地提高资源发现效率.     

基于偏好和M-Flooding的网格资源发现

为了更有效地解决网格资源发现和定位问题,提出一种利用偏好划分和M-Flooding算法调整的网格资源发现方法。该方法给出衡量资源相似度的新方法及改进的消息扩散方式M-Flooding算法,将网格空间中的节点根据各自的偏好属性划分为不同的偏好组。搜索请求在组内进行传播,从而避免传统盲目搜索所带来的弊端。实验结果表明,该方法能够提高网格资源发现效率,降低资源发现平均路径长度。     

基于多属性查询的P2P网格资源发现机制

资源发现是网格环境中的关键问题,目前许多的资源发现机制并不能有效地提供资源的分类。为此,在P2P网格基础上提出一种基于多属性查询的分布式资源树的资源发现机制。该分布式资源树通过资源的主属性进行资源的组织和分类,能动态灵活地实现P2P网格中各节点的负载动态平衡。     

基于资源区域的网格资源发现方法

资源发现是整个网格系统的热点研究问题。结合P2P技术提出了一种基于资源区域的网格资源发现的新方法,按照资源的类型将网格资源划分为多个区域,具有相同类型资源的网格信息节点组织在同一区域中,各区域由一个域中心节点进行管理,各域中心节点形成P2P层。把网格中的资源分为域间－域内两类,从而大大提高了查询效率和通信效率,减少了网络流量。     

网格资源查找方法的分析与比较

在网格环境下,如何快速进行资源查找定位是影响网格性能和QoS的重要因素.本文分析了目前已有的两种用于网格资源发现的资源查找算法(集中式查找算法、分布式查找算法)的优劣,并参照网络路由器的路由转发策略,提出了改进的基于路由转发的资源查找算法.     

在网格资源发现中使用蚁群算法的应用研究

网格中包含多种多样、分布领域广、系统结构差异大、变化频繁等特点的资源．这给网格环境下的资源发现机制带来更大的难度和更多的挑战。阐述网格资源发现在网格资源管理中的重要性,分析网格资源发现中应用蚁群算法的优势,在此基础上,对网格资源发现中应用蚁群算法的方案进行综合的设计与分析．讨论在网格资源发现机制中蚁群算法的实际应用。     

网格环境中基于语义注释的服务发现算法

网格是一种大规模的资源共享技术,它通过资源的分布式协作来加大资源的共享利用率。网格服务发现是使用网格的基础和前提,但目前的网格服务发现在召回率和准确率上均未达到理想水平。针对该问题,提出了服务行为的概念,并且利用语义技术对其进行注释,在此基础上提出一种基于服务行为语义注释的网格服务发现算法。实验结果表明,与传统方法相比,该算法具有更高的准确率和召回率,并能够在一定程度上提高服务的稳定性。     

基于自组织的网格资源发现方法的研究

为了提高网格资源发现的效率以及系统的稳定性,提出了一种可以自组织的三层网格服务资源结构.这种结构能够将系统中的结点进行有效的自组织,即结点按照各自的特点,自动组成虚拟组织并选出一个主索引结点,然后主索引结点动态地选出全局索引结点,另外还能够根据系统的具体状况选择适当的资源查找算法,从而提高了查找效率.仿真结果证明,这种结构是稳定可靠的,同时具有很高的查询效率.     

A distributed resource discovery algorithm for P2P grids

Centralized or hierarchical administration of the classical grid resource discovery approaches is unable to efficiently manage the highly dynamic large-scale grid environments. Peer-to-peer (P2P) overlay represents a dynamic, scalable, and decentralized prospect of the grids. Structured P2P methods do not fully support the multi-attribute range queries and unstructured P2P resource discovery methods suffer from the network-wide broadcast storm problem. In this paper, a decentralized learning automata-based resource discovery algorithm is proposed for large-scale P2P grids. The proposed method supports the multi-attribute range queries and forwards the resource queries through the shortest path ending at the grid peers more likely having the requested resource. Several simulation experiments are conducted to show the efficiency of the proposed algorithm. Numerical results reveal the superiority of the proposed model over the other methods in terms of the average hop count, average hit ratio, and control message overhead.     

Facilitating resource discovery in grid environments with peer-to-peer structured tuple spaces

The computational grid is rapidly evolving into a large-scale computing infrastructure that facilitates resource sharing and problem solving over the Internet. Information services play a crucial role in grid environments for discovery of resources. The dynamic nature and the large-scale of a grid pose many challenges to information services in terms of scalability and resilience. This paper presents RDSpace which can be used as a substrate for resource discovery in grid environments. RDSpace builds a shared tuple space on top of a structured peer-to-peer overlay to achieve high scalability in dealing with a large number of computing nodes and to support range queries in discovery of resources. Another novelty of RDSpace lies in its capability to handle churn situations where nodes may join or leave the space frequently. RDSpace is evaluated from the aspects of scalability and churn handling, and the evaluation results are also presented in this paper.     

基于P2P框架的网格资源发现算法研究

由于资源数量的巨大,典型网格系统中的资源发现问题就成为关键,而现有网格中有许多的资源发现算法主要是集中或分层方法。P2P已经被认为是一种合适的分布式模型,它具有动态性、可伸缩等优点。在现有网格之上提出了一个P2P虚拟层,并据此提出了一个用于网格资源发现的分布式算法,从而解决现有网格系统中资源发现效率低、性能差、不具有伸缩性和可扩展性等一系列问题。     

Randomized gossip algorithms for maintaining a distributed bulletin board with guaranteed age properties

Scalable computer systems, including clusters and multi‐cluster grids, require routine exchange of information about the state of system‐wide resources among their nodes. Gossip‐based algorithms are popular for providing such information services due to their simplicity, fault tolerance and low communication overhead. This paper presents a randomized gossip algorithm for maintaining a distributed bulletin board among the nodes of a scalable computer system. In this algorithm each node routinely disseminates its most recently acquired information while maintaining a snapshot of the other nodes' states. The paper provides analytical approximations for the expected average age, the age distribution and the expected maximal age for the acquired information at each node. We confirm our results by measurements of the performance of the algorithm on a multi‐cluster campus grid with 256 nodes and by simulations of configurations with up to 2048 nodes. The paper then presents practical enhancements of the algorithm, which makes it more suitable for a real system. Such enhancements include using fixed‐size messages, reducing the number of messages sent to inactive nodes and supporting urgent information. The enhanced algorithm guarantees the age properties of the information at each node in the configurations with an arbitrary number of inactive nodes. It is being used in our campus grid for resource discovery, for dynamic assignment of processes to the best available nodes, for load‐balancing and for on‐line monitoring. Copyright © 2009 John Wiley & Sons, Ltd.     

基于Hierarchy结构的网格资源发现算法

为了解决传统资源发现机制不能很好地适应网络状态、可扩展性较差等问题,在超级节点模型的基础上,结合联系节点,建立了一种基于层次结构的网格模型,设计了成员加入协议,给出了基于跳数限定、缓存列表的资源发现算法。通过对网络架构的分析,该模型能够适应网格资源的复杂性与异构性,可扩展性好。实验结果证明：该算法缩短了查询时间,提高了网格环境下资源发现的效率。     

基于小世界特性的网格资源发现算法

对已有的网格资源发现方法进行分析,提出一种以P2P方式实现的、基于小世界特性的非集中式网格资源发现算法。算法将具有相似兴趣属性的结点组织在一起形成兴趣簇,使得搜索请求尽量在簇内进行传播。仿真测试结果表明,该算法可以很好地减少资源发现的通信开销．并有着较高的搜索成功率。     

一种网格资源空间模型及其应用

资源的表示、描述、组织、部署、发现、访问、使用、维护和最终撤销是网格计算的重要研究问题，直接影响到网格协议、网格语言与网格软件的设计和实现，将网格看成一台虚拟计算机，从计算机体系结构角度，用地址空间的方法研究了这些问题，提出了一个网格资源空间3层模型，并应用到织女星网格的GSML软件包与网格系统软件的设计和实现中，这种采用有效资源、虚拟资源、物理资源的3层方法有助于提高网格软件的好用性、透明性、自治性、模块性，这个EVP模型并不局限于科学计算网格，对数据网格、信息网格、商业网格以及对等计算中的资源空间问题研究，也有参考作用。     

网格计算中基于移动Agent的资源发现机制

网格计算中资源发现是一种相当关键的技术,为了更有效地发现并组织资源以满足应用程序的需要,分析了现有两种主要的资源发现技术,在LDAP（Light Directory Access Protocol）目录服务技术的基础上,结合移动Agent技术,提出了一种基于移动Agent的资源发现机制。详细介绍它的总体框架、工作机制,并给出了性能分析。     

OPTIMIZED QUERY FORWARDING FOR RESOURCE DISCOVERY IN UNSTRUCTURED PEER-TO-PEER GRIDS

One of the challenges of resource discovery in unstructured peer-to-peer grid systems is minimizing network traffic. The network traffic arises by query messages that are broadcasted to other peers in order to find the appropriate resources. Blind search methods that are employed in such systems do not work well because every specific query generates high query traffic, which quickly overwhelms the network. Informed search methods usually use recorded history of previous queries to decide where the new queries should be sent. Such methods can reduce network traffic but do not consider the path length. In this study, a method was proposed in which both the path length and network traffic are considered. This approach reduces the hop numbers and prevents massive flooding of query messages. To do this, it selects optimum neighbor peer(s) in order to optimize query forwarding. The proposed approach uses statistical tables that are obtained from recorded history of previous queries. Then a genetic algorithm is applied to these statistical tables to find the optimum neighbor peer(s). The proposed approach showed that query forwarding through the optimum neighbor peer(s) has a greater probability of finding a requested resource with lower hop numbers. This method was compared with random walk and flooding approaches. It was observed that the network traffic remarkably decreased in comparison to a flooding approach, whereas it was similar to the results obtained by a random walk method. Moreover, this method provided a higher success rate in comparison to the random walk approach, whereas it was similar to the results obtained by a flooding method.