基于国产化环境的线程池模型研究与实现

为满足面向服务化和大数据的大型企业级信息系统的高并发、高吞吐、安全性需求,也为适应新形势下国防网络信息系统逐步向国产化自主平台迁移的行业发展趋势,本文通过对常用线程池模型的比较研究,提出了固定无优先级领导者/跟随者线程池和动态有优先级半同步/半异步线程池模型,并提供基于银河麒麟操作系统+飞腾CPU的国产自主环境的实现方案.     

半同步半异步线程池的设计与实现

在服务器应用开发中线程池技术被广泛地用于处理大量的并发任务请求,线程池设计的好坏决定服务器的并发处理性能和效率。本文介绍用于复杂并行系统设计的半同步半异步设计模式,根据该模式设计并实现一个线程池,该线程池具有效率高、稳定性好的特点。     

一种分布式系统中线程池的设计与实现

随着网络和分布式计算的日益发展,负载数量迅速增长,如何在大负载情况下保证高效的吞吐率是构建服务器时所面临的问题,目前广泛采用的技术之一是线程池。借鉴Leader／Followers模式,设计并实现了一类高效的线程池,并针对分布式系统环境做了进一步的改进。此方法已经应用到分布事务监控器OnceTX的实现中,并取得了很好的效果。     

基于改进线程池技术服务器程序的设计与实现

当前互联网大多是B（Browser）/S（Server）、C（Client）/S（Server）结构的应用模式.服务器要处理大量的客户请求,线程池技术被引入以提高性能.首先介绍线程池如何改进服务器程序性能,然后分析线程池在服务器程序应用中的不足,并提出一个改进的线程池机制.最后给出改进机制的实现.     

基于线程池技术的云闪定位远程控制软件设计

根据云闪定位系统远程控制软件的功能需求,采用客户端/服务器(C/S)结构模式,将远程主机作为服务器,各探测站作为客户端,服务器创建线程池分别与客户端建立网络连接,客户端和服务器之间采用自定义的应用层协议实现数据传输,用户在远程主机即可接收各探测站的数据并进行处理,最后将云闪的定位结果显示在地图上。采用线程池技术减少线程的创建与销毁开销以提高系统的工作效率,满足系统对实时性的要求。     

一种基于排队系统的启发式中间件动态线程池管理机制

以Web应用服务器为代表的中间件需要为Intcrnct应用提供有效的运行时性能保障和优化服务。线程池技术是一种常见的性能优化方法。针对Internet应用的特征,中间件的线程池管理需要在感知运行时上下文的基础上进行动态调整,然而如何挖掘有效的影响因素以使调整效果更具有适应性,仍值得深入研究。首先基于M/M/1/K/二/FCFS排队系统提出了一个应用服务器的动态线程池模型,然后在此基础上研究了引入一组启发因素和规则,这将更有效地反映运行时上下文,实现驱动线程池大小的动态调整过程,使线程池规模适应资源的变化。以上机制通过原型实验验证了启发式因素的变化对线程池规模调整的有效影响,并表明该机制能够有效改善系统性能。     

Java中的线程池及实现

本文探讨了应用线程池技术对Java多线程程序性能的优化及有效使用线程池技术的准则,研究了线程池技术的特点、工作原理、实现方法,并给出了线程池的Java实现实例.     

OpenLDAP性能测试分析与优化

OpenLDAP是开源的LDAP服务器,在分布式目录服务中得到了广泛应用.详细分析了OpenLDAP目前所采用的独特"线程池"模式.通过比较OpenLDAP在不同模式下的性能差异,发现原模式对LDAP操作存在较大的响应延迟.进一步给出了改进的"线程池"模式,该改进模式能够降低LDAP操作响应延迟.最后通过仿真实验,表明改进模式可以明显改善OpenLDAP的性能.     

数据保护技术在多线程应用程序开发中的应用研究

正确使用多线程技术能够更好地开发并发性任务和提高测控系统性能,在避免系统阻塞和减少系统运行时间方面有着明显优点.详细介绍了LabWindows/CVI环境中多线程机制以及线程池中关键的数据保护技术,设计了一个实例程序,同时实现了线程池、数据保护、异步定时器等多线程技术,实例同时说明了通过不同方法访问线程安全变量的差异.     

不确定移动机器人编队间接自适应模糊动力学控制

研究不确定非完整移动机器人Leader/Follower编队动力学控制问题,对Follower提出了自适应队形跟踪控制方法.首先,基于队形方程设计了运动学队形跟踪控制器,使用Backstepping技术扩展出队形跟踪误差动力学方程;然后,利用自适应模糊系统逼近其不确定项,构造了间接自适应模糊动力学队形跟踪控制器;最后,证明了队形跟踪误差可收敛到原点的小邻域内.仿真结果验证了所提出控制策略的有效性.     

Accurate and efficient follower log repair for Raft-replicated database systems

State machine replication has been widely used in modern cluster-based database systems. Most commonly deployed configurations adopt the Raft-like consensus protocol, which has a single strong leader which replicates the log to other followers. Since the followers can handle read requests and many real workloads are usually read-intensive, the recovery speed of a crashed follower may significantly impact on the throughput. Different from traditional database recovery, the recovering follower needs to repair its local log first. Original Raft protocol takes many network round trips to do log comparison between leader and the crashed follower. To reduce network round trips, an optimization method is to truncate the follower’s uncertain log entries behind the latest local commit point, and then to directly fetch all committed log entries from the leader in one round trip. However, if the commit point is not persisted, the recovering follower has to get the whole log from the leader. In this paper, we propose an accurate and efficient log repair (AELR) algorithm for follower recovery. AELR is more robust and resilient to follower failure, and it only needs one network round trip to fetch the least number of log entries for follower recovery. This approach is implemented in the open source database system OceanBase. We experimentally show that the system adopting AELR has a good performance in terms of recovery time.     

Robust formation control without velocity measurement of the leader robot

In this paper a control problem of leader–follower motion coordination of multiple nonholonomic mobile robots is addressed and subsequently in the proposed scheme, a reference trajectory generated based on the information from the leader is tracked by the follower robots. To alleviate demanded information on the leader, specifically to eliminate the measurement requirement or estimation of the leader's velocity and dynamics, a virtual vehicle is constructed whereby its trajectory converges to the reference trajectory of the follower. Trajectory tracking controller is then designed to allow the follower robot to track the virtual vehicle using neural network approximation, in combination with the backstepping and Lyapunov direct design technique and finally the performance and effectiveness of the controller is verified throughout the experiments.     

Coordinated transportation of a single object by two nonholonomic mobile robots

We propose a decentralized control algorithm for transporting a single object by two nonholonomic mobile robots. One of the robots acts as a leader, whose trajectory is planned by itself or defined previously, whereas the other robot, referred to as a follower, follows the leader by keeping a constant distance from the leader. The follower can also avoid obstacles while following the leader without any absolute information about their position. Furthermore, the two mobile robots can realize an omnidirectional motion of the object when the leader broadcasts some simple information to the follower. Some simulation results show a good performance by the proposed decentralized control algorithm. This work was presented, in part, at the Seventh International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002.     

Efficient and stable quorum-based log replication and replay for modern cluster-databases

The modern in-memory database (IMDB) can support highly concurrent on-line transaction processing (OLTP) workloads and generate massive transactional logs per second. Quorum-based replication protocols such as Paxos or Raft have been widely used in the distributed databases to offer higher availability and fault-tolerance. However, it is non-trivial to replicate IMDB because high transaction rate has brought new challenges. First, the leader node in quorum replication should have adaptivity by considering various transaction arrival rates and the processing capability of follower nodes. Second, followers are required to replay logs to catch up the state of the leader in the highly concurrent setting to reduce visibility gap. Third, modern databases are often built with a cluster of commodity machines connected by low configuration networks, in which the network anomalies often happen. In this case, the performance would be significantly affected because the follower node falls into the long-duration exception handling process (e.g., fetch lost logs from the leader). To this end, we build QuorumX, an efficient and stable quorum-based replication framework for IMDB under heavy OLTP workloads. QuorumX combines critical path based batching and pipeline batching to provide an adaptive log propagation scheme to obtain a stable and high performance at various settings. Further, we propose a safe and coordination-free log replay scheme to minimize the visibility gap between the leader and follower IMDBs. We further carefully design the process for the follower node in order to alleviate the influence of the unreliable network on the replication performance. Our evaluation results with the YCSB, TPC-C and a realistic micro-benchmark demonstrate that QuorumX achieves the performance close to asynchronous primary-backup replication and could always provide a stable service with data consistency and a low-level visibility gap.     

Models and algorithms for competitive facility location problems with different customer behavior

Competitive facility location problems arise in the context of two non-cooperating companies, a leader and a follower, competing for market share from a given set of customers. We assume that the firms place a given number of facilities on locations taken from a discrete set of possible points. For this bi-level optimization problem we consider six different customer behavior scenarios from the literature: binary, proportional and partially binary, each combined with essential and unessential demand. The decision making for the leader and the follower depends on these scenarios. In this work we present mixed integer linear programming models for the follower problem of each scenario and use them in combination with an evolutionary algorithm to optimize the location selection for the leader. A complete solution archive is used to detect already visited candidate solutions and convert them efficiently into similar, not yet considered ones. We present numerical results of our algorithm and compare them to so far state-of-the-art approaches from the literature. Our method shows good performance in all customer behavior scenarios and is able to outperform previous solution procedures on many occasions.     

A new approach of formation navigation derived from multi-robots cooperative online FastSLAM

A new formation navigation approach derived from multi-robots cooperative online FastSLAM is proposed. In this approach,the leader and follower robots are defined.The posteriori estimation of the leader robot state is treated as a relative reference for all follower robots to correct their state priori estimations.The control volume of individual follower will be achieved from the results of the corrected estimation.All robots are observed as landmarks with known associations by the others and are considered in their landmarks updating.By the method,the errors of the robot posterior estimations are reduced and the formation is well kept.The simulation and physical experiment results show that the multi-robots relative localization accuracy is improved and the formation navigation control is more stable and efficient than normal leader-following strategy.The algorithm is easy in implementation.     

Finite time time-varying formation tracking for second-order multiagent systems with prescribed transient performance

This paper studies the finite time output formation tracking for a class of second-order multiagent systems subject to prescribed transient performance. The considered leader–follower time-varying formation tracking is realized under a directed communication topology. First, a performance function is introduced into a time-varying barrier Lyapunov function (TV-BLF) for the purpose of shaping the transient behavior. Then, based on the TV-BLF and adding a power integrator technology, a distributed formation control law is constructed such that all followers can form a predefined formation pattern while tracking the leader in finite time with satisfied transient performance. Moreover, a robust term is designed in the proposed controller to improve the disturbance rejection capability of the formation system. Finally, a simulation example is carried out to verify the effectiveness and superiority of the presented formation control protocol.     

Neural adaptive PID formation control of car-like mobile robots without velocity measurements

A virtual leader–follower formation control of a group of car-like mobile robots is addressed in this paper. First, the kinematic and dynamic models of car-like robots are transformed into a second-order leader–follower formation model which inherits all structural properties of the robot dynamic model. Then, a new observer-based proportional–integral-derivative formation controller is proposed to force that all robots construct a desired formation with respect to a predefined virtual leader. To improve the formation tracking and observation performance, the integral action is incorporated into the design of the observer–controller scheme. Adaptive robust and neural network techniques are also employed to compensate uncertain parameters, unmodeled dynamics, and external disturbances. Lyapunov’s direct method is utilized to show that the formation tracking and observation errors are semi-globally uniformly ultimately bounded. Then, the proposed controller is extended to the leader–follower formation of a team of tractor–trailer systems. Finally, simulation results illustrate the efficiency of the proposed controller.     

Fuzzy Policy Reinforcement Learning in Cooperative Multi-robot Systems

A multi-agent reinforcement learning algorithm with fuzzy policy is addressed in this paper. This algorithm is used to deal with some control problems in cooperative multi-robot systems. Specifically, a leader-follower robotic system and a flocking system are investigated. In the leader-follower robotic system, the leader robot tries to track a desired trajectory, while the follower robot tries to follow the reader to keep a formation. Two different fuzzy policies are developed for the leader and follower, respectively. In the flocking system, multiple robots adopt the same fuzzy policy to flock. Initial fuzzy policies are manually crafted for these cooperative behaviors. The proposed learning algorithm finely tunes the parameters of the fuzzy policies through the policy gradient approach to improve control performance. Our simulation results demonstrate that the control performance can be improved after the learning.