A Heuristic Algorithm for Task Scheduling Based on Mean Load on Grid

Efficient task scheduling is critical to achieving high performance on grid computing environment. The task scheduling on grid is studied as optimization problem in this paper. A heuristic task scheduling algorithm satisfying resources load balancing on grid environment is presented. The algorithm schedules tasks by employing mean load based on task predictive execution time as heuristic information to obtain an initial scheduling strategy. Then an optimal scheduling strategy is achieved by selecting two machines satisfying condition to change their loads via reassigning their tasks under the heuristic of their mean load. Methods of selecting machines and tasks are given in this paper to increase the throughput of the system and reduce the total waiting time. The efficiency of the algorithm is analyzed and the performance of the proposed algorithm is evaluated via extensive simulation experiments. Experimental results show that the heuristic algorithm performs significantly to ensure high load balancing and achieve an optimal scheduling strategy almost all the time. Furthermore, results show that our algorithm is high efficient in terms of time complexity.     

Strategy and Simulation of Adaptive RID for Distributed Dynamic Load Balancing in Parallel Systems

Dynamic load balancing schemes are significant for efficiently executing nonuniform problems in highly parallel multicomputer systems.The objective is to minimize the total exectuion time of single applications.This paper has proposed an ARID strategy for distributed dynamic load balancing.Its principle and control protocol are described,and te communication overhead,the effect on system stability and the performance efficiency are analyzed.Finally,simulation experiments are carried out to compare the adaptive strategy with other dynamic load balancing schemes.     

LinuxDirector: A connection director for scalable internet services

LinuxDirector is a connection director that supports load balancing among multiple Internet servers,which can be used to build scalable Internet services based on clusters of servers.LinuxDirector extends the TCP/IP stack of Linux Kernel to support three IP load balancing techniques,VS/NAT,VS/TUN and VS/DR.Four scheduling algorithms have been implemented to assign connections to different servers.Scalability is achieved by transparently adding or removing a node in the cluster.High availability is provided by detecting node or daemon failure and reconfiguring the system appropriately.This paper describes the design and implementation of LinuxDirector and presents serveral of its features including scalability,high availability and connection affinity.     

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.     

A Load Balancing Algorithm in OpenFIow Networks

The goal of load balancing algorithm in OpenFlow networks is to combine the load balancing technology with the Open lqow technology, so that load balancing can adapt to the characteristics of the OpenFlow networks.The study of this paper focused on load balancing in OpenFlow networks, proposed a new load balancing algorithm.The algorithm considered the status of servers and network comprehensively, and provided the metrics for them.To distribute the network traffic to the servers and links reasonably, the goal of load balancing is reached.     

Design of Scheduling Decision Mechanism for Agile Manufacturing System

Design of scheduling decision mechanism is a key issue of scheduling decision method and strategy for agile manufacturing system. Effective scheduling decision mechanism helps to improve the operational agility of manufacturing system. Several scheduling decision mechanisms are discussed, including scheduling forecasting mechanism, cooperation mechanism and cell scheduling mechanism. Also soft decision mechanism is put forward as a promising prospect for agile manufacturing system, and some key techniques in soft decision mechanism are introduced.     

Development of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems

This paper presents a novel design of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems.The proposed approach implements a novel strategy to achieve stable bipedal walk by decoupling the walking motion control from the sideway balancing control.This strategy allows the walking controller to execute the walking task independently while the sideway balancing controller continuously maintains the balance of the robot.The hip-mass carry approach and selected stages of walk implemented in the control strategy can minimize the efect of major hip mass of the robot on the stability of its walk.In addition,the developed smooth joint trajectory planning eliminates the impacts of feet during the landing.In this paper,the new design of mechanism for locomotion systems and balancing systems are introduced.An additional degree of freedom introduced at the ankle joint increases the sensitivity of the system and response time to the sideway disturbances.The efectiveness of the proposed strategy is experimentally tested on a bipedal robot prototype.The experimental results provide evidence that the proposed strategy is feasible and advantageous.     

A self-routing load balancing algorithm in parallel computing: comparison to the central algorithm

Load balancing is an important stage of a system using parallel computing where the aim is the balance of workload among all processors of the system. In this paper, we introduce a new load balancing algorithm with new capabilities for parallel systems, among which is the independence of a separate route-finder algorithm between the load receiver and sender nodes. In addition to simulation of the new algorithm, due to similarity in behavior to the proposed algorithm, the central algorithm is simulated. Simulation results show that, the system performance increases with the increase of the degree of neighborhood between the processors. These results also indicate the algorithm’s high compatibility with environment changes.     

Coordinated Workload Scheduling in Hierarchical Sensor Networks for Data Fusion Applications

To minimize the execution time of a sensing task over a multi-hop hierarchical sensor network,we present a coordinated scheduling method following the divisible load scheduling paradigm.The proposed scheduling strategy builds on eliminating transmission collisions and idle gaps between two successive data transmissions.We consider a sensor network consisting of several clusters.In a cluster,after related raw data measured by source nodes are collected at the fusion node, in-network data aggregation is fu...     

Research on scheduling algorithms in Web cluster servers

This paper analyzes quantitatively the impact of the load balance scheduling algorithms and the locality scheduling algorithms on the performance of Web cluster servers,and brings forward the Adaptive_LARD algorithm.Compared with the representative LARD algorithm,the advantages of the Adaptive_LARD are that:(1)it adjusts load distribution among the back-ends through the idea of load balancing to avoid learning steps in the LARD algorithm and reinforce its adaptability;(2)by distinguishing between TCP connections accessing disks and those accessing cache memory,it can estimate the impact of different connections on the back-ends‘load more precisely.Performance evaluations suggest that the proposed method outperforms the LARD algorithm by up to 14.7%.     

分层负载平衡调度系统的设计与实现

随着分布式系统的广泛应用,提高系统性能的负载平衡策略也日益为人们所重视。文章在分析负载平衡调度问题现有研究成果、提出基于规则的分层负载平衡调度模型[10]的基础之上,设计、实现了一个分层负载平衡调度系统。实验结果表明,与传统的动态调度与静态调度相比,分层负载平衡调度系统具有较好的问题求解效率和适用性。     

面向多媒体系统的负载均衡策略研究

随着多媒体应用的普及,面向多媒体应用的并行文件系统负载均衡策略的研究具有现实意义。本文根据视频点播等多媒体应用的特点,提出了面向多媒体应用的并行文件系统动态负载均衡策略,构建了该策略的均衡模型,提出了适于多媒体服务系统的动态调度算法,并对该算法进行了性能分析。最后建立了NFS文件系统负载均衡实验环境,测试了该策略的高效性,充分证明了所提出的面向多媒体应用的并行文件系统负载均衡策略的优势。     

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。     

一种用于PC存储集群的动态负载平衡策略

在大规模并行分布处理系统中,各节点间的负载平衡调度是最常见的关键性问题之一。该文首先简单介绍了负载平衡的目标和基本的集群任务调度算法,然后针对一种PC存储集群提出了一个分布式任务调度和动态负载平衡策略,对该策略进行了详细的介绍,并对其进行了性能分析。     

Task partitioning,scheduling and load balancing strategy for mixed nature of tasks

Load balancing and task partitioning are important components of distributed computing. The optimum performance from the distributed computing system is achieved by using effective scheduling and load balancing strategy. Researchers have well explored CPU, memory, and I/O-intensive tasks scheduling, and load balancing techniques. But one of the main obstacles of the load balancing technique leads to the ignorance of applications having a mixed nature of tasks. This is because load balancing strategies developed for one kind of job nature are not effective for the other kind of job nature. We have proposed a load balancing scheme in this paper, which is known as Mixed Task Load Balancing (MTLB) for Cluster of Workstation (CW) systems. In our proposed MTLB strategy, pre-tasks are assigned to each worker by the master to eliminate the worker’s idle time. A main feature of MTLB strategy is to eradicate the inevitable selection of workers. Furthermore, the proposed MTLB strategy employs Three Resources Consideration (TRC) for load balancing (CPU, Memory, and I/O). The proposed MTLB strategy has removed the overheads of previously proposed strategies. The measured results show that MTLB strategy has a significant improvement in performance.     

基于GNP算法的分布式爬虫调度策略*

针对分布式搜索引擎的任务调度及负载均衡问题,提出了基于GNP算法的分布式爬虫调度策略和负载均衡的方法。利用网络距离预估取代大规模的网络距离测量,不仅提高了系统的响应速度,还减少了系统对广域网造成的压力。通过在广域网上部署爬虫节点,构建分布式搜索引擎,应用该调度策略进行实验,验证了系统性能有较大提高。     

片上多处理器系统的多线程调度策略

本文提出了一种多线程调度策略,解决片上多处理器系统的线程分配问题。实验证实,本文的线程调度策略有效地实现了系统的负载均衡。     

Runtime incremental parallel scheduling (RIPS) on distributedmemory computers

Runtime Incremental Parallel Scheduling (RIPS) is an alternative strategy to the commonly used dynamic scheduling. In this scheduling strategy, the system scheduling activity alternates with the underlying computation work. RIPS utilizes the advanced parallel scheduling technique to produce a low overhead, high quality load balancing, as well as adapting to irregular applications. The paper presents methods for scheduling a single job on a dedicated parallel machine     

一种环境感知的仿真服务调度模型

针对传统分布式仿真框架HLA/RTI中动态调度负载平衡较差、执行可靠性较低的问题,提出一种基于环境感知的仿真服务调度模型C3SM。C3SM模型包含总体结构、调度策略和服务部署。总体结构规定各个模块的功能与交互接口,调度策略采用改进的蚁群算法进行仿真服务的动态调度,服务部署采用重叠覆盖部署策略以保证较好的服务可用性和较低的资源消耗。仿真实验结果表明,与传统分布式仿真框架HLA/RTI相比,C3SM模型通过实时获取执行环境的上下文信息,能够获得较优的负载平衡度,且重叠覆盖的仿真服务部署策略使得仿真运行系统的可靠性明显提高。