Flexible and extensible load balancing

This paper presents the design philosophy and implementation of the BALANCE system. BALANCE is a flexible, network independent and computer architecture independent load balancing system which allows the building of reusable parallel and distributed applications. By implementing related services as bi generic servers with their connection endpoints registered in BALANCE, the clients can easily access the servers by server system calls. To demonstrate the flexibility of BALANCE, several widely different applications have been implemented and evaluated, including system servers, parallel and distributed applications and a scheduling testbed. The use of generic servers to improve system modularity and code reuse is also discussed. © 1997 John Wiley & Sons, Ltd.     

基于网格计算的混合负载均衡策略

根据分布式系统的静态和动态负载均衡策略的优缺点,提出了在网格计算环境下的混合负载均衡策略.为了让网络中节点在网格计算环境中有效地执行需要大量计算的复杂任务,提出了用来评估节点效率的函数,并结合模拟实验证实了在此函数下算法的优越性.     

An adaptive threshold based hybrid load balancing scheme with sender and receiver initiated approach using random information exchange

The primary objective of load balancing for distributed systems is to minimize the job execution time while maximizing the resource utilization. Load balancing on decentralized systems need effective information exchange policy so that with minimum amount of communication the nodes have up to date information about other nodes in the system. Periodic, event‐based and on‐demand information exchange are some important policies used for the same. All these approaches involve a lot of overhead and even sometime leading toward obsolete data with the nodes if there is a delay in the updation. This work presents an adaptive threshold‐based hybrid load balancing scheme with sender and receiver initiated approach (HLBWSR) using random information exchange (RIE). RIE ensures that the information is exchanged in such a way that each node in the system has up‐to‐date state of the other nodes with much reduced communication overhead. Further, the adaptive threshold ensures that almost an average numbers of jobs are executed by all the nodes in the system. The study of the effect of the use of RIE on sender initiated, receiver initiated and hybrid of sender and receiver initiated load balancing approach establishes the superior performance of HLBWSR among its RIE‐based peers. A comparative analysis of HLBWSR, with periodic information exchange strategy, modified estimated load information scheduling algorithm and load balancing on arrival reveals its effectiveness under various test conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

一种基于负载反馈的分布式数字集群动态负载均衡算法

针对传统负载均衡算法不能满足公网数字集群系统高并发用户请求和快速呼叫建立等需求,提出一种基于负载反馈的分布式数字集群动态负载均衡算法,实现公网数字集群系统负载均衡,提高用户容量。首先建立参与MCPTT服务器的静态负载和动态负载监控机制和指标;然后利用加权轮询算法为用户分配参与MCPTT服务器,并通过用户请求的处理获得复合负载参数;根据负载指标的反馈更新参与MCPTT服务器权值以动态调整服务器负载。仿真结果表明,该算法的负载均衡效果优于传统算法和其他动态反馈算法,负载均衡度更小、用户请求响应延迟更低。     

支持动态负载平衡的分层消息队列模型

中间件技术为解决异构分布式环境下的负载平衡问题提供了有力的工具,但传统的消息中间件负载平衡的实现较为复杂,其动态参数繁多且容易带来额外开销。提出了一种分层消息队列模型,该模型中利用队列组管理器对分布式队列进行组管理,并提供了丰富的任务分配策略。在该模型的基础上提出动态负载平衡实现方案:通过基于队列的阈值阈长模型实时监控成员队列的负载情况,采用集中式调度进行负载信息搜集和负载平衡决策,结合负载迁移和队列组管理进行过载处理。     

负载平衡调度问题的一般模型研究

分布式系统提供了巨大的处理能力,为了实现和充分利用这种能力,需要优良的负载平衡调度技术。因此,负载平衡问题是影响分布式系统性能的重要因素。在深入研究分布式系统中负载平衡调度问题的基础上,归纳总结了负载平衡调度的一般模型,对影响负载平衡的各个因素进行了详细的分析。此模型已在一个实际模型中得到了有效地验证。     

A Dynamic Load Balancing Mechanism for Distributed Systems

It is desirable in a distributed system to have the system load balanced evenly among the nodes so that the mean job response time is minimized.In this paper,we present a dynamic load balancing mechanism(DLB).It adopts a cntralized approach and is network topology independent.The DLB mechanism employs a set of threscholds which are automatically adjusted as the system load changes.It also provides a simple mechanism for the system to switch between periodic and instantaneous load balancing policies with ease.The performance of the proposed algorithm is evaluated by intensive simulations for various parameters.Te simulation results show that the mean job response time in a system implementing DLB algorithm is significantly lower than the same system without load balancings.Furthermore,compared with a previously proposed algorithm,DLB algorithm demonstrates improved performance,especially when the system is heavily loaded and the load is unevenly distributed.     

并行燃烧数值模拟计算优化——面向自适应非结构网格的动态负载平衡方法

燃烧数值模拟计算通常采用非结构网格模拟计算区域。在非结构网格上进行并行模拟计算时,其自适应方式使得不同进程上的计算负载频繁变动,且差异巨大,导致并行计算效率低下。为了提高并行计算的效率,一个有效的方法是采用动态负载平衡技术。提出一种针对燃烧的化学反应状态的动态负载平衡方法,该方法采用不同策略对化学反应不同阶段各进程上的计算负载进行预测,根据预测结果平均进程间的计算任务,达到负载平衡。实验分析表明,该方法能有效地降低进程间的负载不平衡程度,使得模拟计算的总体运行时间降低了10％。     

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.     

Memory-aware kernel mechanism and policies for improving internode load balancing on NUMA systems

Although nonuniform memory access architecture provides better scalability for multicore systems, cores accessing memory on remote nodes take longer than those accessing on local nodes. Remote memory access accompanied by contention for internode interconnection degrades performance. Properly mapping threads to cores and data accessed to their nodes can substantially improve performance and energy efficiency. However, an operating system kernel's load-balancing activity may migrate threads across nodes, which thus messes up the thread mapping. Besides, subsequent data mapping behavior pays for the cost of page migration to reduce remote memory access. Once unsuitable threads are migrated, it is detrimental to system performance. This paper focuses on improving the kernel's internode load balancing on nonuniform memory access systems. We develop a memory-aware kernel mechanism and policies to reduce remote memory access incurred by internode thread migration. The Linux kernel's load balancing mechanism is modified to incorporate selection policies in the internode thread migration, and the kernel is modified to track the amount of memory used by each thread on each node. With this information, well-designed policies can then choose suitable threads for internode migration. The purpose is to avoid migrating a thread that might incur relatively more remote memory access and page migration. The experimental results show that with our mechanism and the proposed selection policies, the system performance is substantially increased when compared with the unmodified Linux kernel that does not consider memory usage and always migrates the first-fit thread in the runqueue that can be migrated to the target central processing unit.     

一种基于生态捕食模型的网络负载平衡算法

针对分布式系统的负载分配问题,通过对生态捕食模型的研究,提出一种基于生态差分方程数学模型、分布式控制的网络负载平衡算法。该算法将两节点对应到生态系统的捕食者和被捕食者,将各节点的负载信息对应到种群规模,利用两种群生态差分方程数学模型动态调整节点负载信息,达到网络负载平衡。实验证明了该算法的有效性。     

多蚁群算法的网络负载动态均衡方法

针对网络资源管理中的负载均衡与优化问题,提出一种多蚁群网络负载动态均衡方法,采用网络流量工程理论中拥塞控制机制实现信息素随网络流量动态释放与更新。算法通过蚁群间信息素的动态相互作用（蚁群内信息素相互增强,蚁群间信息素相互削弱）,将代表网络负载的蚂蚁合理分配到可用路径,避免蚂蚁集中到特定路径而造成网络拥塞。实验结果表明,通过路径信息素控制能够实现网络负载均衡,有效提高网络在路径延时、平均带宽利用率和平均丢包率方面的性能。     

Dynamic load‐balancing mechanism for distributed Java applications

Program environments or operating systems generally leave the decision on the allocation of program entities to the developer, offering either placement directives, or tools available through the manipulation of a graphical interface. These approaches cannot always take into account the dynamic behavior of applications, dynamicity in the execution environment or the heterogeneity of the execution platform. Transparent deployment algorithms are necessary for automizing and optimizing application distribution. The Adaptive Distributed Applications in Java (ADAJ) project deals with placement and migration of Java objects. It automatically deploys parallel Java applications on a cluster of workstations using monitoring information about the application behavior. The transparency obtained through the integration of these tools in the middleware makes such an environment easy to use and improves efficiency. Copyright © 2005 John Wiley & Sons, Ltd.     

基于时间偏差的并行逻辑模拟的动态负载平衡

随着大规模集成电路的复杂性日益增加,逻辑模拟开始采用并行离散事件模拟技术。在现有的基于时间偏差协议的并行逻辑模拟系统的基础上,提出了一个动态负载平衡模型,模型能够针对模拟时的负载变化,进行以一组模拟对象为单位的迁移以实现负载平衡。提出模拟推进度的概念,作为对并行逻辑模拟过程中的负载进行准确的衡量标准。     

基于时间偏差协议的动态负载平衡技术*

对并行VHDL模拟的特殊性进行分析后,建立了一个并行VHDL模拟的动态负载平衡模型。在此模型中,提出动态调节最佳并行规模的动态负载平衡方法来解决系统资源紧张的问题,采用一种新的模拟中负载的度量方法——模拟推进度。此模型还包括基于标准偏差和最小通信变化量的动态负载平衡算法和一个运行中的负载迁移机制。最后对该模型进行可行性分析。     

A comparison of concurrent programming and cooperative multithreading under load balancing applications

Two models of thread execution are the general concurrent programming execution model (CP) and the cooperative multithreading execution model (CM). CP provides nondeterministic thread execution where context switches occur arbitrarily. CM provides threads that execute one at a time until they explicitly choose to yield the processor. This paper focuses on a classic application to reveal the advantages and disadvantages of load balancing during thread execution under CP and CM styles; results from a second classic application were similar. These applications are programmed in two different languages (SR and Dynamic C) on different hardware (standard PCs and embedded system controllers). An SR‐like run‐time system, DesCaRTeS, was developed to provide interprocess communication for the Dynamic C implementations. This paper compares load balancing and non‐load balancing implementations; it also compares CP and CM style implementations. The results show that in cases of very high or very low workloads, load balancing slightly hindered performance; and in cases of moderate workload, both SR and Dynamic C implementations of load balancing generally performed well. Further, for these applications, CM style programs outperform CP style programs in some cases, but the opposite occurs in some other cases. This paper also discusses qualitative tradeoffs between CM style programming and CP style programming for these applications. Copyright © 2004 John Wiley & Sons, Ltd.     

LTE系统中的分布式负载迁移协商均衡算法

为了提高长期演进计划(long term evolution,LTE)系统中业务处理资源的利用率,降低由于系统处理资源分配不均而导致的呼损率,给出了一种适用于LTE系统的分布式负载迁移协商均衡算法.分析了LTE系统通信的特点,指出可利用LTE系统eNodeB (evolved NodeB)间使用X2接口进行数据通信的特点,在组网的eNodeB问进行负载迁移.在此基础上建立了负载迁移协商均衡模型,指出了算法的适用场景,说明了算法均衡粒度的选取标准和性能评价指标.通过与传统的轮询算法进行比较,使用分布式事件驱动方法对该算法进行了性能分析,验证结果表明了该算法的有效性.     

动态负载均衡算法在校园网格中的应用

校园网格能有效消除信息孤岛,实现我国高校的计算资源和信息资源的有效共享。一个亟待解决的问题是在校园网格环境下,服务器节点响应能力低下。目前已提出多种技术与方案以解决并提高校园网格的服务器节点的响应能力,负载均衡技术就是一种全新的技术。本文根据校园网格的特点和影响负载均衡的因素,对基于校园网格的负载均衡技术进行了分析和探讨,并提出一种动态负载均衡算法。     

一种多维集合划分负载均衡资源优化分配算法

针对多处理群集系统中多个任务处理需要的资源和多个处理节点能够提供的m维资源间的合理匹配问题，给出了多维集合划分问题的优化模型，定义了资源均衡度函数，提出多维集合划分负载均衡资源优化分配算法，通过该算法可以得到资源匹配NP问题的较优解。实验结果表明，该算法具有较好的实用性和可行性，比传统的启发式算法效率高。