基于多Agent技术的多运营终端自适应负载均衡算法

当前网络用户数量、多运营终端节点数量增长趋势明显,导致网络计算资源很难达到均衡状态。提出基于多Agent技术的多运营终端自适应负载均衡算法。定义多运营终端负载状态,采集多运营终端负载信息,并量化处理负载信息。以此为基础,搭建Agent负载均衡结构,引入多Agent技术,结合多运营终端节点工作特点,构建网络资源模型,设计多运营终端自适应负载均衡算法。实验结果证明：与对比算法相比,应用提出算法获得的多运营终端的吞吐量较大,平均响应延迟较短,负载均衡度较高,证实了提出算法具有理想的负载均衡效果。     

基于多Agent网格资源调度的负载均衡研究

介绍了一种基于多Agent的网格资源调度方法,并提出了一种负载均衡算法设计思想,以改善网格环境中资源分配不均的问题.     

基于市场方法的MAS系统任务调度算法

本文探讨了在Intemet环境下,知识型MAS系统的任务负载分配问题,指出了它与网格计算的区别.本文的方法与传统的计算资源分配方法相反,将任务负载看作资源,而将Agent作为消费者,每处理一个任务,就获得一定数量的边际效用,利用市场机制,使Agent自主进行任务负载的分配.设计了基于均衡市场和连续CDA市场的两种调度算法,对算法的效果和特点进行了分析,证明市场机制的调度算法可以有效地实现MAS系统任务负载的平衡.此外,本文还给出了一个简单的确定均衡价格的方法.     

一种高效动态LEO卫星网络流量调节路由算法

针对考虑负载均衡的LEO卫星网络路由算法存在控制网络开销偏大、路由更新不及时以及流量调节机制分配不均等问题,提出了一种基于负载均衡的动态LEO卫星网络路由算法DRLB。根据卫星节点路径记录信息以及后向Agent读取策略设计新的路由机制,获得动态卫星拓扑结构;分析前向Agent的分组格式并删除冗余字段,达到减小网络开销目的;根据数据发送时间间隔构造前向Agent选址策略,提高路由更新效率,通过考虑卫星所处纬度流量分配不均问题,改进流量调节因子,获得更好的负载均衡效果。仿真结果表明,与SDRZ-MA算法相比,DRLB算法在减缓星地之间的控制开销、平均端到端时延等方面具有较好的优势。     

基于极值优化的多核集群负载均衡

针对分布式多核节点系统的负载均衡难以取得最优解的问题,提出了一种基于改进极值优化的负载均衡方法.该方法通过节点的CPU占用率发现负载不均衡情况,然后用一个衡量模型估计计算与通信开销使改进的极值优化方法能够实现集群的负载均衡.仿真与实验结果表明该算法能够提高分布式集群的计算效率,是一种理想的负载均衡算法.     

基于轮转周期的动态反馈负载均衡算法

网络管理系统中管理端逐步采用分布式集群构架,通过负载均衡算法调度客户端请求,并将客户端请求分配给多个事务节点进行并行处理。为进一步提高集群系统服务的性能,文中在研究以往负载均衡算法的基础上,提出了一种基于轮转周期的动态反馈负载均衡算法。该算法设计了一种基于剩余资源动态权值的节点剩余负载能力计算方法的动态反馈机制;并在动态反馈负载均衡算法的一个采样周期内引入轮转周期对客户端请求均衡分配。通过实验比较分析,该算法能获得更好的负载均衡效果。     

异构分布式负载均衡容错算法研究

基于基/副版本技术提出一种异构分布式容错调度模型,并在该模型上提出HDL算法。该算法克服了以前算法在故障发生前后负载均衡性不稳定问题,并在一定程序上实现均衡可控性,同时在模拟实验中给出一种基于协方差反映负载均衡性的方法。实验结果证明,该算法的负载均衡性在故障发生前后是稳定的。     

一种高效的分布式反馈流量负载均衡算法

为解决多节点路由器等系统的分布式流量负载均衡问题,提出一种基于反馈的自适应算法。该算法通过会话划分进行负载任务分组,根据各节点的反馈进行接入分配和负载参数调整,实现负载均衡,给出快速端口检测和初始负载均衡等实现该算法的关键技术。性能分析与实验表明,该算法具有较高的负载均衡度和较低的系统开销。     

IP Phone系统中组播通信Agent的设计与实现

提出了一个具有实时负载均衡和快速异常处理功能的组播通信Agent(MCA)。该Agent充分利用组播通信的优点，通过负载均衡算法，对IP Phone系统中各个服务器进行资源分配和调度，并且对异常情况做到快速处理和恢复。首先给出了MCA的组成结构，然后重点描述各模块的功能和实现，最后通过模拟实验，对MCA进行了性能分析。     

基于移动Agent的分布式测控系统任务调度研究

动态任务调度是分布式测控系统中的一项关键技术。基于移动Agent提出了一种新的分布式测控系统动态任务调度算法。算法采用IBM Aglets系统设计和执行移动Agent,利用移动Agent-Aglet在系统运行过程中动态迁移任务,从而有效地提高了系统效率,实现了负载均衡的目标。详细介绍了任务迁移的实现及Aglet通信机制。     

StreamTune: dynamic resource scheduling approach for workload skew in video data center

Video surveillance applications need video data center to provide elastic virtual machine (VM) provisioning. However, the workloads of the VMs are hardly to be predicted for online video surveillance service. The unknown arrival workloads easily lead to workload skew among VMs. In this paper, we study how to balance the workload skew on online video surveillance system. First, we design the system framework for online surveillance service which consists of video capturing and analysis tasks. Second, we propose StreamTune, an online resource scheduling approach for workload balancing, to deal with irregular video analysis workload with the minimum number of VMs. We aim at timely balancing the workload skew on video analyzers without depending on any workload prediction method. Furthermore, we evaluate the performance of the proposed approach using a traffic surveillance application. The experimental results show that our approach is well adaptive to the variation of workload and achieves workload balance with less VMs.     

一个有效的动态负载平衡方法

动态负载平衡问题是影响工作站网络并行计算性能的重要因素.首先分析出在负载平衡中产生额外开销的根本原因是负载的移动,进而定性地给出了每次移动负载的粒度公式.引入益处估计的方法,仅在有益的情况下进行负载平衡.另外还提出了一个动态负载平衡算法.最后,通过实验,将该算法的运行结果与其他人的负载平衡结果以及不作负载平衡的情况进行了对比.此负载平衡方法在工作站为空载以及不同的负载和应用问题的数据规模的情况下,都优于Siegell等人提出的方法.     

A Load Balanced Task Scheduling Heuristic for Large-Scale Computing Systems

Optimal task allocation in Large-Scale Computing Systems (LSCSs) that endeavors to balance the load across limited computing resources is considered an NP-hard problem. MinMin algorithm is one of the most widely used heuristic for scheduling tasks on limited computing resources. The MinMin minimizes makespan compared to other algorithms, such as Heterogeneous Earliest Finish Time (HEFT), duplication based algorithms, and clustering algorithms. However, MinMin results in unbalanced utilization of resources especially when majority of tasks have lower computational requirements. In this work we consider a computational model where each machine has certain bounded capacity to execute a predefined number of tasks simultaneously. Based on aforementioned model, a task scheduling heuristic Extended High to Low Load (ExH2LL) is proposed that attempts to balance the workload across the available computing resources while improving the resource utilization and reducing the makespan. ExH2LL dynamically identifies task-to-machine assignment considering the existing load on all machines. We compare ExH2LL with MinMin, H2LL, Improved MinMin Task Scheduling (IMMTS), Load Balanced MaxMin (LBM), and M-Level Suffrage-Based Scheduling Algorithm (MSSA). Simulation results show that ExH2LL outperforms the compared heuristics with respect to makespan and resource utilization. Moreover, we formally model and verify the working of ExH2LL using High Level Petri Nets, Satisfiability Modulo Theories Library, and Z3 Solver.     

MPI并行程序设计的负载平衡实现方法

MPI是目前集群系统中最重要的并行编程工具,它采用消息传递的方式实现并行程序间通信。在MPI并行程序设计中实现负载平衡有着重要的意义,可以减少运行时间,提高MPI并行程序的性能。负载平衡又可分为静态负载平衡和动态负载平衡,对于静态负载平衡,提出了一种分配任务的算法,可有效地按照节点的计算能力,在节点间分配任务;对于动态负载平衡,提出了一种在MPI并行程序中实现的方法,可有效地根据节点的负载情况,在节点间迁移任务。     

一种改进的基于动态反馈的负载均衡算法

负载均衡是集群系统研究的一个重要问题,负载均衡算法是集群任务分配的核心,介绍了LVS中的负载均衡算法,讨论了常用算法的不足,在分析这些算法各自优缺点的基础上,提出了一种改进的基于反馈的负载均衡算法,算法引入一个负载容余参数以更准确地描述集群节点的负载状况,在考虑服务节点真实负载,处理能力的基础上,尽量简化负载均衡器的任务分配算法.测试结果显示该算法优于静态算法.     

Development and validation of a behavioural video coding scheme for detecting mental workload in manual assembly

Abstract

Manual assembly in the future Industry 4.0 workplace will put high demands on operators’ cognitive processing. The development of mental workload (MWL) measures therefore looms large. Physiological gauges such as electroencephalography (EEG) show promising possibilities, but still lack sufficient reliability when applied in the field. This study presents an alternative measure with a substantial ecological validity. First, we developed a behavioural video coding scheme identifying 11 assembly behaviours potentially revealing MWL being too high. Subsequently, we explored its validity by analysing videos of 24 participants performing a high and a low complexity assembly. Results showed that five of the behaviours identified, such as freezing and the amount of part rotations, significantly differed in occurrence and/or duration between the two conditions. The study hereby proposes a novel and naturalistic method that could help practitioners to map and redesign critical assembly phases, and researchers to enrich validation of MWL-measures through measurement triangulation.

Practitioner summary: Current physiological mental workload (MWL) measures still lack sufficient reliability when applied in the field. Therefore, we identified several observable assembly behaviours that could reveal MWL being too high. The results propose a method to map MWL by observing specific assembly behaviours such as freezing and rotating parts.

Abbreviations: MWL: mental workload; EEG: electroencephalography; fNIRS: functional near infrared spectroscopy; AOI: area of interest; SMI: SensoMotoric Instruments, ETG: Eye-Tracking Glasses; FPS: frames per second; BORIS: Behavioral Observation Research Interactive Software; IRR: inter-rater reliability; SWAT: Subjective Workload Assessment Technique; NASA-TLX: National Aeronautics and Space Administration Task Load Index; EL: emotional load; DSSQ: Dundee Stress State Questionnaire; PHL: physical load; SBO: Strategisch Basis Onderzoek     

双网冗余的负载均衡算法研究

提出了双网冗余环境下的负载均衡算法,通过设计合适的包选择算法,在保持网络链接属性的前提下,对数据包的关键域进行Hash运算,在双网之间均衡流量。考虑双网的处理能力和负载情况不同,该文又提出了动态自适应的Hash算法,可以根据负载情况动态地在双网之间均衡流量。理论分析和试验结果表明,该负载均衡算法提高了高速网络环境下双网的数据采集性能,大大提高了双网的设备利用率。     

基于负载均衡的无线传感器网络路由算法

延长网络的稳定周期是无线传感器网络路由算法的重要挑战,负载均衡算法是解决上述问题的重要方法之一．提出了一种负载均衡算法（LDBRA）,它根据节点的能量分布状况及通信能耗选择簇首节点以实现负载均衡．在簇首选择过程中,在以上两个因素中选择平衡点实现最优簇头的选择．仿真结果显示LDBRA能够更好的实现负载均衡,延长网络的稳定周期．     

Parallel CBIR implementations with load balancing algorithms

The purpose of content-based information retrieval (CBIR) systems is to retrieve, from real data stored in a database, information that is relevant to a query. When large volumes of data are considered, as it is very often the case with databases dealing with multimedia data, it may become necessary to look for parallel solutions in order to store and gain access to the available items in an efficient way.Among the range of parallel options available nowadays, clusters stand out as flexible and cost effective solutions, although the fact that they are composed of a number of independent machines makes it easy for them to become heterogeneous. This paper describes a heterogeneous cluster-oriented CBIR implementation. First, the cluster solution is analyzed without load balancing, and then, a new load balancing algorithm for this version of the CBIR system is presented.The load balancing algorithm described here is dynamic, distributed, global and highly scalable. Nodes are monitored through a load index which allows the estimation of their total amount of workload, as well as the global system state. Load balancing operations between pairs of nodes take place whenever a node finishes its job, resulting in a receptor-triggered scheme which minimizes the system's communication overhead. Globally, the CBIR cluster implementation together with the load balancing algorithm can cope effectively with varying degrees of heterogeneity within the cluster; the experiments presented within the paper show the validity of the overall strategy.Together, the CBIR implementation and the load balancing algorithm described in this paper span a new path for performant, cost effective CBIR systems which has not been explored before in the technical literature.     

网络处理器负载均衡中的遗传算法研究

根据IXP28XX网络处理器多引擎并行处理机制,针对微引擎处理数据包中出现的负载过重和任务拥塞问题,通过定义微引擎负载偏差率以及适应度函数,建立解决负载均衡问题的模型,利用遗传算法可以完成对各微引擎的负载调度。提出一种多点交叉和变异的遗传算法,仿真结果表明,该算法可以减少最优值迭代次数,从而缩短调度时间,使各微引擎的负载快速达到均衡。