采用配置完成优先策略的可重构任务调度算法

如何隐藏和减少配置时间是相依性可重构任务调度的关键问题.提出一种采用配置完成优先策略的相依性可重构任务调度算法,通过基于预配置优先级的列表调度算法,实现将后续任务的配置时间隐藏于前驱任务的运行时间中,并采用基于配置完成优先策略的配置重用机制,减少了任务调度后的配置过程,从而在总体上缩短了相依性任务集合的运行时间.仿真结果表明,该调度算法能有效避免调度死锁,并可减少相依性可重构任务的整体运行时间.     

基于模糊控制的分布式服务流程引擎自动配置策略

在面向大规模业务的分布式服务流程应用环境中,服务流程的分布式执行引擎的自动配置管理是一个非常重要的问题.现阶段,简单的、静态的引擎节点配置并不能达到很好的效果.为此,提出了一种新的引擎自动配置管理算法,即基于模糊控制的服务流程引擎自动配置算法,同时在一个基于JINI的分布式服务流程引擎系统中,比较了该动态配置算法和常见的静态算法的性能.实验结果表明,该自动配置策略较静态策略而言能明显提高服务流程引擎系统整体响应时间的稳定性,使得服务流程引擎服务器能够根据外部请求负载情况进行自动的调节和配置,从而更好地适应不断变化的运行环境.     

一种基于报文过滤系统的规则批量配置算法

首先对报文过滤系统进行简单概述,提出对该系统规则进行批量配置的必要性;在介绍与该系统相关理论基础之后,着重讨论具有批量配置功能的算法设计;最后,对该系统批量配置算法的实现做详细地论述。     

基于混合二进制粒子群的Web系统优化算法

随着网络用户量的急剧增加,Web服务器被广泛应用于大型软件系统中,系统在运行前通常需要配置与性能相关的多个参数。人工配置参数的过程太繁琐且需要专业知识与经验,为了更便捷、更快速获取合理的系统配置参数,提出了一种基于混合二进制粒子群的Web系统优化算法。该算法加入了经验因子、爬山算法、线性递减惯性权重,对Web系统自动迭代寻找最优配置参数,解决了传统二进制粒子群算法寻优效率低、容易陷入局部最优解等问题。实验结果表明,该算法寻优效率高,能跳出局部最优解,可以获得效果更好的全局最优解。     

面向产品优化配置的粒子群优化算法

针对产品配置大规模、多约束、多目标及组合优化等特性,建立一种有效的配置模型,将复杂的产品优化配置问题转化为图的路径寻优问题。针对基本粒子群算法(PSO)的缺陷,将遗传原理、蚁群机制和模拟退火理论引入PSO算法,提出一种改进的PSO算法。根据产品优化配置问题的离散特点,对PSO算法进行离散化处理,重新定义粒子的位置和速度表示,确立这些量的运算规律和粒子运动方程。典型产品配置实例验证了提出的模型和算法的可行性。     

An address configuration protocol for 6LoWPAN wireless sensor networks based on PDAD

In a wireless sensor network (WSN), data collected by a sensor node need to be associated with location information in order to support real-world applications. Taking the WSN characteristics into account, this paper proposes an address configuration scheme based on location information and passive duplicate address detection (PDAD). In this scheme, the network architecture based on location information is presented, and based on this architecture the address initialization algorithm and address maintenance algorithm are proposed. The address initialization algorithm is performed once the network starts, and it is made up of the initialization address configuration sub-algorithm (IAC) and the initialization location PDAD sub-algorithm (ILPDAD). The address maintenance algorithm is performed after the initialization algorithm is complete, and it is composed of the maintenance address configuration sub-algorithm (MAC) and the maintenance location PDAD sub-algorithm (MLPDAD). During the address initialization process (address maintenance process), a new node first uses IAC (MAC) to obtain an address and then performs ILPDAD (MLPDAD) to ensure the address uniqueness. Since beacon frames are employed to achieve IAC (MAC) and ILPDAD (MLPDAD), the address configuration cost and delay are reduced. Moreover, IAC (MAC) is based on location information and ILPDAD (MLPDAD) is based on PDAD, so there are always the sufficient address resources for address configuration without address reclamation. In this way, the extra cost and delay caused by both the address reclamation and the address configuration failure are avoided. This paper evaluates the performance of this scheme, and the data results show that this scheme effectively reduces the address configuration delay and cost.     

基于混沌PSO算法的Hadoop配置优化

针对Hadoop的组合优化问题,提出一种基于混沌粒子群优化算法的配置优化策略。为保证算法在进行局部搜索的同时避免陷入局部最优,对陷入局部最优的标准值和混沌处理的迭代次数的不同组合进行实验,获得使Hadoop性能达到最优的配置。实验结果表明,算法得出的最优配置方案能够有效提高Hadoop的性能,具有较好的稳定性。     

基于混合离散二进制粒子群-遗传算法的测试配置方法研究

针对目前测试性建模工作中尚无具体方法指导测试配置这一问题,通过对系统内故障传播关系进行分析,提出了一种混合离散二进制粒子群-遗传算法用于求解测试配置的最优方案,使系统的测试性模型在满足规定测试性指标下使用的测试数量最少。将系统测试配置方案进行二进制粒子编码,并在粒子群算法中引入遗传算子,使混合算法具有较快的搜索速度的同时避免陷入局部最优。最后通过实例计算与仿真,证明所提出算法计算结果正确且对于指导复杂系统测试性建模工作具有实际应用价值。     

可重构混合任务调度算法

隐藏和减少配置时间是可重构任务调度的关键问题。针对同时存在相关联的软、硬件任务的可重构混合任务,提出一种可重构混合任务调度算法。通过预配置策略和优先级算法确定需要预先配置的任务及其预配置顺序,将后继任务的配置过程隐藏在前驱任务的运行时间中,并采用配置重用策略,减少相同任务的配置次数。实验仿真结果表明,同已有的算法相比,该调度算法调度效果明显,减少了可重构任务调度的整体开销。     

A new compression based approach for reconfiguration overhead reduction in virtex based RTR systems

The advantage of RTR systems usually comes with some costs. The required time to map some areas of a program to an FPGA is considerable and affects the performance of RTR systems. Several methods have been developed to speed up the configuration process in these systems. Configuration compression can reduce the total number of write operations to load a configuration and it has been proven to be an efficient technique for dealing with the configuration overhead. In this paper, we have developed a new approach for reconfiguration overhead reduction in Virtex Based RTR Systems by using a compression technique based on Lempel-Ziv (LZ) algorithm. Since the order of the sequence of configuration frames affects the compression rate, we have proposed an algorithm based on Genetic Algorithm for finding the optimal configuration sequence of frames. The proposed algorithm will be applied to the input configuration file in a batch (offline) manner, and its time complexity is tolerable considering the overhead reduction obtained by having the optimal sequence of frames in run-time configuration decompression. Also, corresponding to our approach, a hardware model has been designed for configuration decompression.