Direction-aware resource discovery in large-scale distributed computing environments

As a system scales up, the peer-to-peer (P2P) approach is attractive to distributed computing environments, such as Grids and Clouds, due to the amount of resources increased. The major issue in large-scale distributed systems is to prevent the phenomenon of a communication bottleneck or a single point of failure. Conventional approaches may not be able to apply directly to such environments due to restricted queries and varied resource characteristics. Alternatively, a fully decentralized resource discovery service based on an unstructured overlay, which relies only on the information of resource attributes and characteristics, may be a feasible solution. One major challenge of such service is to locate desired and suitable resources without the global knowledge of distributed sharing resources. As a consequence, the more nodes the resource discovery service involves, the higher the network overhead incurs. In this paper, we proposed a direction-aware strategy which can alleviate the network traffic among unstructured information systems for distributed resource discovery service. Experimental results have demonstrated that the proposed approach achieves higher success rate at low cost and higher scalability.     

分布式虚拟环境中的信息服务和资源定位

在分布式虚拟环境系统中,存在多种不同的资源,如场景中的实体、用户化身、ＣＰＵ、内存、网络等,而在碰撞检测、动态负载平衡、场景数据的一致性维护、系统的安全服务等操作中都要求对系统中的资料进行查找、定位。将资料作为对象来解决分布式虚拟环境系统的信息服务和资源定位,提供对分布的不同机器上的各种不同资源动态信息的有效、可靠访问。     

Deploying Wide-Area Applications Is a Snap

The Structured overlay Networks Application Platform (Snap) is a J2EE-compatible wide-area Web application deployment infrastructure. Due to its structured peer-to-peer overlay network substrate, Snap offers three benefits to wide-area Web application deployment: easy adaptation of existent J2EE applications to a scalable network, a secure and decentralized deployment environment, and transparent embedded services, such as persistence, load balancing, fault tolerance, and edge computing     

Applying Peer-to-Peer Techniques to Grid Replica Location Services

Peer-to-peer systems offer attractive system management properties, including the ability of components that join the network to self-organize; scalability up to tens of thousands of members; the ability of the network to automatically repair its topology after node failures; and techniques for maintaining redundant information to improve reliability and load balancing. We investigate applying peer-to-peer techniques to Grid services that are oriented toward resource discovery. In particular, we apply the Chord structured peer-to-peer overlay network to the Globus Replica Location Service, which allows registration and discovery of data replicas. We describe the design and performance of a Peer-to-Peer Replica Location Service (P-RLS) that uses the Chord algorithm to self-organize P-RLS servers and exploits the Chord overlay network to replicate P-RLS mappings adaptively. We present performance measurements and simulation results for the P-RLS system. We also discuss outstanding issues for applying peer-to-peer techniques to Grid resource discovery services.     

一种能耗感知的虚拟集群CPU资源自动再配置方法

系统虚拟化技术可以动态再配置应用环境的计算资源.当前动态资源配置方法主要关注于保证具有动态负载应用的服务质量.这些方法受应用性能驱动并常常增加资源控制系统的响应延迟.针对上述问题提出了以资源使用状态为驱动的资源再配置方法(resource-use-status-drivenresource reconfigurationscheme,RUSiC),自动适应动态负载变化来满足应用性能的资源需求.RUSiC被设计成2层架构的资源再配置模型,基于实时的资源使用状态,及时用较小的开销为应用调整合适的资源配置.同时,RUSiC也考虑到电能的有效使用,在资源的新配置中通过尽可能减少激活物理节点的数量避免大量不必要的电能消耗及相关的冷却费用.实验数据表明,在应用负载变化时,RUSiC能快速监测并响应变化的资源需求,并在保证应用性能的前提下,使用较小数量的激活物理节点.     

P2P与网格的互补性研究

P2P与网格都是新型的分布式计算模型,它们的总体目标相似,对P2P和网格模型中的安全性、连通性、访问服务、资源发现与管理、容错以及协同性等几个重要问题进行分析,为将P2P模型中的技术应用到网格中来创造条件。采用P2P协议和模型来处理网格计算,并利用P2P与网格技术之间的协同和互补来构建高性能的分布式系统,从而增加网格的可扩展性,实现非分层的分散网格系统。     

基于语义覆盖网的P2P信息共享系统研究

现有P2P信息共享系统存在仅支持粗粒度、弱语义共享以及系统效率低等局限性,限制了其更大规模、更高层次的应用。基于资源相似节点通过信息聚类聚集在同一主题域,实现节点资源有序组织的思想,提出了一种基于语义覆盖网的P2P信息共享系统,建立由资源层、信息服务中心层、语义覆盖网络层和应用层四个层次组成的系统框架结构,并阐述了系统流程。分析表明,该系统有效优化了网络性能,可扩展性好,可以胜任不同的网络规模。     

Biased random walks on resource network graphs for load balancing

The currently emerging large-scale complex networks and networks of networks are becoming apparent in the pervasive supply of seamless and transparent access to heterogeneous resources and services such as network domains, applications, services and storage owned by multiple organizations. The dynamics and heterogeneous environments involved, however, pose many challenges for controlling and balancing resource access, composition and deployment across complex grid and network infrastructures. In this paper, a scheme is proposed that gives a distributed load-balancing scheme by generating almost regular resource allocation networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node refers to its free resources, and the job assignment and resource discovery processes required for load-balancing are accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources in grids and networks. The proposed solution is tested with real world data and the performance is tested against a recently reported distributed algorithm for load balancing.     

基于Hive的高可用双引擎数据仓库

打破信息孤岛，整合异构数据，汇聚共享交换，深度分析挖掘，提供行业领域辅助决策和态势分析具有深远的理论和应用价值.本文以中国科学院教育科研态势感知服务的实际需求为牵引，设计并实现了一套基于Hive的Hadoop/Spark双计算引擎大数据仓库，支持多种方式OLAP分析，进行了可用性、负载均衡、资源管理的优化设计，为后续进行全院数据汇聚挖掘、知识图谱构建、学科态势分析提供了平台支撑.实验表明，系统灵活高效，高可用可扩展，资源调度科学，负载均衡效果明显.     

P2P分布实时数据交换的高可用混合负载均衡算法

负载分配是分布式系统的资源管理和任务调度的关键问题之一，本文在分析当前已有算法在负载的实时分配方面存在的问题基础上，提出了适用于P2P分布实时数据交换的高可用性混合负载均衡算法2PLB．该算法将处理结点的处理能力和网络流情况协同考虑，以一种静态负载均衡和动态负载均衡结合的自调节混合负载均衡算法实现用于实时任务调度和负载调节．相比单纯的静态负载均衡或者动态负载均衡算法，本文所提的算法避免了纯静态负载均衡算法在处理任务时不能满足可适应性问题，又克服了纯动态负载均衡在任务处理过程中由于维护动态负载状态和任务迁移而导致的计算复杂度等问题的缺点，所提算法对于大规模实时任务处理具有实时性强，易于调度，具有显著的可比性等特点，广域网络环境下的系统测试表明所提算法能够以对等模式提供高质量实时数据交换和共享服务．     

Hybrid Architecture for Autonomous Load Balancing in Distributed Systems Based on Smooth Fuzzy Function

Due to the rapid advancements and developments in wide area networks and powerful computational resources, the load balancing mechanisms in distributed systems have gained pervasive applications covering wired as well as mobile distributed systems. In large-scale distributed systems, sharing of distributed resources is required for enhancing overall resource utilization. This paper presents a comprehensive study and detailed comparative analysis of different load balancing algorithms employing fuzzy logic and mobile agents. We have proposed a hybrid architecture for integrated load balancing and monitoring in distributed computing systems employing fuzzy logic and autonomous mobile agents. Furthermore, we have proposed a smooth and composite fuzzy membership function in order to model fine grained load information in a system. The simulation study and a detailed qualitative as well as quantitative analysis of algorithmic performances are presented. Lastly, a deployment environment is described.     

因特网上基于节点角色的计算资源共享平台——RB-CRSP

提出了因特网上基于节点角色的计算资源共享平台——RB-CRSP。设计时充分考虑节点的角色性和功能性,把因特网上的网络资源按照角色划分为服务器端节点、协调节点、工作机节点与客户机节点四类实体,通过配合RB-CRSP的应用编程模式,完成并行分布式计算。分析了RB-CRSP中的自适应资源调度策略,该策略考虑了节点的硬件信息与可信誉机制,实现了平台的负载均衡性;在动态的因特网环境下,利用面向工作机的容错方式保证了平台的可靠性。案例程序选择了典型的并行BenchMark程序：N皇后问题,测试结果表明,RB-CRSP可以方便聚集异构环境下的空闲计算资源,平台的性能与机器硬件条件和可靠性密切相关。     

Facilitating Service Discovery with Semantic Overlay

Service Oriented Architecture （SOA） and Peer-to-Peer （P2P） computing share many common characteristics. It is believed that the combination of the two emerging techniques is a very promising method in promoting the web services （WS）. Because the service discovery plays a key role in the integration, here a P2P-based framework to manage the knowledge of service and locating services is proposed. In this paper, the details of the principle, constructing and maintaining of service semantic overlay architecture have been described, and the way how the semantic overlay facilitates discovery of service resources is illustrated. To enable the semantic web service superiority, Service Ontology, which is considered as the service semantic model, is employed to depict service. The service discovery includes two phases： searching on the service semantic overlay; and local discovery in peer＇s service repository. Various solutions have been proposed to realize those two phases. Furthermore, tests are carried out to evaluate service discovery on the architecture.     

A hybrid policy for fault tolerant load balancing in grid computing environments

Due to the emergence of grid computing over the Internet, there is a need for a hybrid load balancing algorithm which takes into account the various characteristics of the grid computing environment. Hence, this research proposes a fault tolerant hybrid load balancing strategy namely AlgHybrid_LB, which takes into account grid architecture, computer heterogeneity, communication delay, network bandwidth, resource availability, resource unpredictability and job characteristics. AlgHybrid_LB juxtaposes the strong points of neighbor-based and cluster based load balancing algorithms. Our main objective is to arrive at job assignments that could achieve minimum response time and optimal computing node utilization. Major achievements include low complexity of proposed approach and drastic reduction of number of additional communications induced due to load balancing. A simulation of the proposed approach using Grid Simulation Toolkit (GridSim) is conducted. Experimental results show that the proposed algorithm performs very well in a large grid environment.     

An improved load-balancing mechanism based on deadline failure recovery on GridSim

Grid computing has emerged a new field, distinguished from conventional distributed computing. It focuses on large-scale resource sharing, innovative applications and in some cases, high performance orientation. The Grid serves as a comprehensive and complete system for organizations by which the maximum utilization of resources is achieved. The load balancing is a process which involves the resource management and an effective load distribution among the resources. Therefore, it is considered to be very important in Grid systems. For a Grid, a dynamic, distributed load balancing scheme provides deadline control for tasks. Due to the condition of deadline failure, developing, deploying, and executing long running applications over the grid remains a challenge. So, deadline failure recovery is an essential factor for Grid computing. In this paper, we propose a dynamic distributed load-balancing technique called “Enhanced GridSim with Load balancing based on Deadline Failure Recovery” (EGDFR) for computational Grids with heterogeneous resources. The proposed algorithm EGDFR is an improved version of the existing EGDC in which we perform load balancing by providing a scheduling system which includes the mechanism of recovery from deadline failure of the Gridlets. Extensive simulation experiments are conducted to quantify the performance of the proposed load-balancing strategy on the GridSim platform. Experiments have shown that the proposed system can considerably improve Grid performance in terms of total execution time, percentage gain in execution time, average response time, resubmitted time and throughput. The proposed load-balancing technique gives 7 % better performance than EGDC in case of constant number of resources, whereas in case of constant number of Gridlets, it gives 11 % better performance than EGDC.     

协同系统中可扩展的动态容错模型研究及实现

针对协同系统的特点以及其对可靠性、实时性和性能等方面的要求，提出了一种可扩展的动态容错模型xDFT（Extensible Dynamic Fault Tolerance Model，xDFT）．本容错模型将容错支持结构和容错机制结合在一起：在本模型中首先定义了一种可扩展的、动态容错支撑结构；基于此，提出了一种容错机制．xDFT模型能够根据系统负载状况设定服务节点的负载阈值，改变服务冗余度，不仅提高了服务效率，而且以一种简单有效的方式实现了负载平衡．     

负载平衡的多级并行对等计算在新药研发网格中的实现

介绍了一种在Internet环境下利用分布的计算资源实现计算/数据密集的高通量新药筛选的应用网格——新药研发网格(drug discovery grid，DDG)．对DDG中采用的多级并行对等计算模型(P2P)，自适应的动态负载平衡算法及实现，网格资源的容错技术以及系统安全做了较详细的描述，给出了一组实际环境下的实验数据．实验证明，DDG具有很好的负载平衡能力和良好的系统健壮性，新药筛选应用在大规模的互连网环境下可以获得良好的并行加速效果．     

国家地质调查应用网格体系及关键技术研究

地质调查工作中数据密集、计算密集、资源分布、异构等问题制约了行业应用和信息化发展，网格(grid)是新一代高性能计算环境和信息服务基础设施，能够实现动态跨地域的资源共享和协同工作，国家地质调查应用网格(NGG)基于网格技术，以“服务”为中心，提出并构建了从信息获取、处理到应用的完整的7层体系结构，同时结合行业应用需求，着重研究资源管理、资源交易、服务等关键技术，在Petri网和图论的基础上提出了一种新的服务链模型(服务／资源网)，实现地质调查领域的资源共享和信息服务。     

Resource scheduling algorithm with load balancing for cloud service provisioning

Cloud computing uses scheduling and load balancing for virtualized file sharing in cloud infrastructure. These two have to be performed in an optimized manner in cloud computing environment to achieve optimal file sharing. Recently, Scalable traffic management has been developed in cloud data centers for traffic load balancing and quality of service provisioning. However, latency reducing during multidimensional resource allocation still remains a challenge. Hence, there necessitates efficient resource scheduling for ensuring load optimization in cloud. The objective of this work is to introduce an integrated resource scheduling and load balancing algorithm for efficient cloud service provisioning. The method constructs a Fuzzy-based Multidimensional Resource Scheduling model to obtain resource scheduling efficiency in cloud infrastructure. Increasing utilization of Virtual Machines through effective and fair load balancing is then achieved by dynamically selecting a request from a class using Multidimensional Queuing Load Optimization algorithm. A load balancing algorithm is then implemented to avoid underutilization and overutilization of resources, improving latency time for each class of request. Simulations were conducted to evaluate the effectiveness using Cloudsim simulator in cloud data centers and results shows that the proposed method achieves better performance in terms of average success rate, resource scheduling efficiency and response time. Simulation analysis shows that the method improves the resource scheduling efficiency by 7% and also reduces the response time by 35.5 % when compared to the state-of-the-art works.     

Web应用服务器自适应负载平衡服务

Web应用服务器是为事务性Web应用提供一系列运行时服务的分布式系统.基于中间件的自适应负载平衡服务是为Web应用服务器提供高可信赖性和高伸缩性的一种有效方法,但目前还存在许多不足,如缺乏服务端透明性、负载策略不可替换等,不能满足Web应用服务器特有的需求.分析了Web应用服务器负载平衡服务的关键需要,设计了一种自适应负载平衡服务,阐述了在J2EE应用服务器WebFrame2.0上实现该服务的若干关键技术及其解决办法,包括可热插拔、负载策略可替换、负载反馈与自适应控制、状态迁移以及容错技术等,最后是相关工作介绍及其比较.该负载平衡服务已在Web应用服务器WebFrame2.0中得以实现.