使用网络节点信息传递策略的分布式优化新算法

本文基于统计学习中众所周知的信度传播理论来研究非线性凸优化问题的分布式算法.通过对优化问题中的网络图中节点上和节点之间的计算以及信息传递过程的深入研究,结合信度传播理论得出适合分布式优化算法的信息传递策略.在集中式经典牛顿法和原始对偶方法框架下,所提分布式算法通过网络中的信息传递策略来完成设计.所提的分布式牛顿–拉夫森算法在无圈连通图情形下是集中式牛顿法的分布式实现.所提分布式原始对偶算法在无圈图情形下有集中式原始对偶算法的收敛效果,且对于有圈连通图也有较好的适应性和鲁棒性.仿真实验说明了我们所提信息传递策略和算法的收敛效果和适合的应用场景.     

多智能体协同任务分配问题研究综述

研究了给定通信基础设施和可用计算资源情况下,多智能体系统协同任务分配问题中集中式、分布式和分散式系统结构运用的适应条件及异步、同步交互方式在不同结构中的应用;分析了分布式或分散式的任务规划中诸如决策一致性策略和一致性算法等必须考虑的问题及其面临的挑战;最后,探讨了多智能体协同任务分配问题分布式和集中式的求解算法。     

分布式优化: 算法设计和收敛性分析

近年来,随着高科技的蓬勃发展,特别是云计算和大数据等新兴领域的出现,分布式优化理论和应用得到了越来越多的重视,并逐渐渗透到科学研究、工程应用和社会生活的各个方面,分布式优化是通过多智能体之间的合作协调有效地实现优化的任务,可用来解决许多集中式算法难以胜任的大规模复杂的优化问题.如今如何设计出有效的分布式优化算法并对其进行收敛性和复杂性的分析成了优化研究的主要任务之一.与集中式算法的主要区别在于分布式算法还不得不考虑通讯和协调在优化中起到的重要作用.本文集中讨论了近年来分布式优化研究中的一些典型热门的研究问题,从一个侧面介绍了包括无约束优化、带约束优化、以及分布式博弈等方向的部分最新成果.同时也比较详尽地论述了笔者最近的相关研究成果.最后,本文简要地对分布式优化的研究和应用前景进行了展望.     

基于分布式压缩感知的联合检测与跟踪算法

多基雷达系统对隐身目标的检测与跟踪具有良好的效果,但是在集中式融合框架下应用于 多基雷达的检测与跟踪算法具有计算复杂、计算量大的缺点.对此,提出一种应用于 多基雷达系统的基于分布式压缩感知的联合检测与跟踪算法.首先,应用分布式紧凑感知 矩阵追踪算法直接重构出表征目标状态空间信息的稀疏网格反射向量;然后,应用检测 前跟踪算法得到精确的目标运动状态和轨迹.仿真实验表明了所提出算法的有效性.     

动态的分布式环境下Top-k查询计算

分布式Top-k查询计算在多媒体近似匹配、网络监控、文档检索和Web数据搜索等技术中具有重要意义.分析分布式Top-k查询计算算法性能的重要标准是网络延迟和带宽消耗.早期的算法主要研究在集中式的环境中,提供有效地处理分布式Top-k查询计算.然而,在动态的、分布式环境中,这些方法还显得不够成熟.因此,提出了一种在网络查询过程中建立的树形拓扑结构,利用直方图统计信息和Bloomfilter数据压缩技术,有效地执行局部优化,及在中间节点(peer)进行部分结果的合并,最终得到全局处理的Top-k查询计算方法(称做TTC算法).这种算法不仅降低了网络延迟,有效地支持动态变化的分布式环境,而且减少网络带宽的消耗.实验结果表明,TTC算法在全局带宽的消耗和网络的响应时间上效果非常显著.     

认知无线网络中基于多用户公平性的功率分配

研究认知无线网络中保证多用户场景下保证用户速率需要的功率分配问题.提出了保证用户公平性的最小化用户实际传输速率与期望速率差值的优化模型,给出了一种集中式功率分配算法1;为了减少减少迭代次数,提出了一种改进的集中式算法2;最后给出了一种分布式的求解算法3.仿真结果表明三种求解算法都收敛于最优解,且集中式算法2的迭代次数明显小于集中式算法1,分布式功率分配算法有利于减少实现的复杂度.     

不确定数据上两种查询的分布式聚集算法

不确定数据查询技术在军事、金融、电信等领域中起到了越来越重要的作用.不确定性数据在传感器网络、分布式Web Server及P2P系统等分布式系统中广泛存在.从这些系统中收集所有数据进行集中式查询将带来巨大的通信开销、时间延迟和存储代价.同时,由于不确定数据的特点,大多数集中式不确定查询算法在分布式环境下并不适用.给出不确定数据的最大值和Top-k聚集查询定义,并分别提出了基于过滤策略的分布式聚集算法.算法根据给出的3个过滤策略,利用数据的分布区间和概率进行筛选概率上限的计算,尽可能将不影响查询结果的数据抛弃.同时,算法以相对较小的代价归并保存并传输了计算最终查询结果所需要的不可丢弃数据.实验结果表明,在各类系统和数据条件下,过滤算法都能够正确地得到查询结果并显著降低系统的数据通信开销.     

可伸缩分布式动态区间映射算法

提出一种支持权重分布数据的可伸缩分布式动态区间映射算法.该算法能够在存储节点发生变化时,根据可用的资源情况立即重新均衡数据对象分布,从所有存储节点中并行迁移数据对象,且迁移的数据对象数目是最少的.在此基础上提出分布式节点地址计算算法,支持计算节点通过视图校正算法自主学习,自动适应新的系统规模,消除了现有的集中式访问性能瓶颈,使系统具有高可伸缩性.     

一种具有信元保序能力的Clos网络分布式调度算法

分组交换三级Clos网络信元调度算法可分为集中式和分布式两种实现方式.分布式调度具有良好的可扩展性,适于在高速大容量环境中应用.然而由于分布式调度会带来同一分组各个信元间的乱序问题,给其实现带来困难.该文提出了一种具有信元保序能力的三级Clos网络分布式调度算法.该算法包括第一级的均匀负载分配、中间级的并行调度和第三级的按序输出调度三部分.文中对算法的性能进行了严格的理论证明和相关的仿真分析,表明该算法可以很好地解决传统分布式调度中的信元乱序问题,具有良好的性价比.     

分布式环境下的决策树挖掘研究

针对分布式环境中数据自治、异构和私有的特点,提出将现有数据挖掘算法分解为分布式统计信息获取和模型生成两部分.以决策树为研究对象,分析了分布式信息需求并设计了分布式挖掘算法步骤.通过性能分析,文中算法在数据自治和通信费用上比集中式算法有优势.     

Synchronized Distributed Termination

An efficient decentralized algorithm for synchronized termination of a distributed computation is presented. It is assumed that distributed processes are connected via unidirectional channels into a strongly connected network, in which no central controller exists. The number of processes and the network configuration are not known a priori. The number of steps required to terminate distributed computation after all processes met their local termination conditions is proportional to the diameter D of the network (D + 1 steps).     

A mechanical proof of Segall's PIF algorithm

We describe the construction of a distributed algorithm with asynchronous communication together with a mechanically verified proof of correctness. For this purpose we treat Segall's PIF algorithm (propagation of information with feedback). The proofs are based on invariants, and variant functions for termination. The theorem prover NQTHM is used to deal with the many case distinctions due to asynchronous distributed computation. Emphasis is on the modelling assumptions, the treatment of nondeterminacy, the forms of termination detection, and the proof obligations for a complete mechanical proof. Finally, a comparison is made with (the proof of) the minimum spanning tree algorithm of Gallager, Humblet, and Spira, for which the technique was developed.     

An efficient parallel termination detection algorithm

In this paper, we present a new, easy to implement algorithm for detecting the termination of a parallel asynchronous computation on distributed-memory MIMD computers. We demonstrate that it operates concurrently with the main computation, adding minimal overhead, and we prove that it correctly detects termination when it occurs. Experimental results confirm that the termination detection routine imposes an overhead smaller than the experimental uncertainty.     

Efficient Algorithms for Distributed Snapshots and Global Virtual Time Approximation

This paper presents snapshot algorithms for determining a consistent global state of a distributed system without significantly affecting the underlying computation. These algorithms do not require channels to be FIFO or messages to be acknowledged. Only a small amount of storage is needed. An important application of a snapshot algorithm is Global Virtual Time determination for distributed simulations. The paper proposes new and efficient Global Virtual Time approximation schemes based on snapshot algorithms and distributed termination detection principles.     

Distributed termination detection for dynamic systems

A symmetric algorithm for detecting the termination of a distributed computation is presented. The algorithm does not require global information concerning the system and does not assume any communication features, barring finite delays in the delivery of messages. It permits dynamic creation and destruction of processes participating in the computation, and also permits destruction of a process by external processes, such as the OS kernel. It also provides for external processes spontaneously joining an ongoing computation. Proofs of safety and liveness are provided.     

A family of optimal termination detection algorithms

An important problem in distributed systems is to detect termination of a distributed computation. A computation is said to have terminated when all processes have become passive and all channels have become empty. In this paper, we present a suite of algorithms for detecting termination of a non-diffusing computation for an arbitrary communication topology under a variety of conditions. All our termination detection algorithms have optimal message complexity. Furthermore, they have optimal detection latency when message processing time is ignored. A preliminary version of the paper first appeared in the 18th Symposium on Distributed Computing (DISC), 2004 [27].     

Termination Detection for Parallel Shortest Path Algorithms

Shortest path computation is required by a large number of applications such as VLSI, transportation, and communication networks. These applications, which are often very complex and have sparse networks, generally use parallel labeling shortest path algorithms. Such algorithms, when implemented on a distributed memory machine, require termination detection methods; these methods consist of some type of synchronization among all processors. Because global synchronization can be costly, it is assumed that the best termination detection methods synchronize as infrequently as possible. The frequency, however, can significantly impact the idle time of parallel labeling shortest path algorithms. In this paper we analyze the impact of this frequency on the performance, in particular the idle time, and identify when low versus high frequency detection is best. The analysis and results indicate that when the size of the subnetwork assigned to processor is small enough so that the computation time is less than or equal to the communication time within an iteration, high frequency termination detection methods should be used. Otherwise, low frequency methods should be used.     

Safe termination detection in an asynchronous distributed system when processes may crash and recover

The termination detection problem involves detecting whether an ongoing distributed computation has ceased all its activities. We investigate the termination detection problem in an asynchronous distributed system under the crash-recovery model. It has been shown that the problem is impossible to solve under the crash-recovery model in general. We identify two conditions under which the termination detection problem can be solved in a safe manner. We also propose algorithms to detect termination under the conditions identified.     

Development of a class of distributed termination detectionalgorithms

Accessing and updating information in a self organizing data structure in a distributed environment requires execution of various distributed algorithms. Design of such algorithms is often facilitated by the use of a distributed termination detection algorithm superimposed on top of another distributed algorithm. The problem of distributed termination detection is considered, and message counting is introduced as an effective technique in designing such algorithms. A class of efficient algorithms, based on the idea of message counting, for this problem is presented. After termination has occurred, it is detected within a small number of message communications. These algorithms do not require the FIFO (first in, first out) property for the communication lines. Assumptions regarding the connectivity of the processes are simple. The algorithms are incrementally developed, i.e. a succession of algorithms leading to the final algorithms is presented