Price-based congestion control and local channel-link assignment for multi-radio wireless mesh networks

In multi-radio multi-channel wireless mesh networks, engineering the network capacity requires a complex cross-layer design. In this paper, in order to make the complex problem implementable in a distributed manner, we make a decoupling approach that breaks down the entire design space into routing and initial channel assignment, and distributed congestion control and local channel reassignment. We propose a unified priced-based framework for distributed congestion control and localized channel-link assignment algorithms. We demonstrate the convergence of the proposed algorithms with respect to different fairness objectives (i.e., proportional fairness and max–min fairness) via simulation on both grid and random topologies. The proposed algorithms achieve faster convergence with less overhead in the control and forwarding plane than previous multi-path based algorithms.     

基于工作流导向的“网络信息安全”实训教材建设

针对"网络信息安全"教材建设的现状进行分析,提出建设基于工作流导向的任务式实训模式教材的必要性,并从教材的指导思想、整体结构、内容结构及其特色等方面进行了阐述。实践证明,该新型教材的建设和使用能够激发学生学习网络安全知识的兴趣,提升动手能力,有效提高教学质量和效率。     

“网络营销”课程改革实施方案

"网络营销"课程知识体系须随着互联网应用的出现和普及而逐渐得到完善,为此提出了该课程的教学改革实施方案。网络营销课程的教学始终要以实践应用为主导,在教学过程中采用案例教学、任务驱动、结合竞赛、学科互动、团队合作等方法。考核应采用灵活分配学分比例的办法。最终使得学生能够将课堂上的知识灵活地运用到工作当中。     

多编组协同任务分配模型及DLS-QGA 算法求解

为解决多智能体编组协同任务分配问题, 定义任务、智能体编组和相关的分配过程变量, 建立以最高任务执行效率为目标的数学模型. 在问题模型中设计考虑资源损耗的编组资源能力更新机制, 提出用于求解该模型的动态列表规划和量子遗传算法的混合任务分配算法, 使用动态列表规划选择处理的任务, 利用量子遗传算法为选定任务分配最合适编组. 最后通过算例表明, 所提出的方法在解决时序逻辑任务分配时能够得到更优更稳定的方案.

     

基于分区的航电系统调度分析工具实现

针对仅含纯周期任务集合、符合ARINC653多分区构架航电系统两级调度模型的可调度性判定问题,提出一种基于分区的航电系统调度分析工具。通过设定时钟变量模拟航电系统各分区中任务集调度过程,依据纯周期任务集及分区航电系统时间片分派特性确定仿真区间,设计优化的调度分析算法,判定航电系统分区级时间片分派的正确性及各分区中任务集的可调度性。测试及实例分析结果表明,该工具能自动、准确、快速地判定航电系统分区以及任务级调度模型的可调度性,并能以甘特图的方式绘制系统调度过程,较现有工具更为直观、高效。     

The locomotive assignment problem: a survey on optimization models

The objective of the locomotive assignment problem (LAP) is to assign a fleet of locomotives to a set of trains while satisfying a rich set of operational and budget constraints and optimizing one or more crucial objectives. This paper presents a survey on optimization models for this class of scheduling problems. Depending on the context of application, the kind of model used to solve the LAP varies; accordingly, this influences the solution methodology and algorithms used. In this paper, we review and also suggest a classification of the various models.     

A multiobjective hybrid ant colony optimization approach applied to the assignment and scheduling problem

The assignment and scheduling problem is inherently multiobjective. It generally involves multiple conflicting objectives and large and highly complex search spaces. The problem allows the determination of an efficient allocation of a set of limited and shared resources to perform tasks, and an efficient arrangement scheme of a set of tasks over time, while fulfilling spatiotemporal constraints. The main objective is to minimize the project makespan as well as the total cost. Finding a good approximation set is the result of trade‐offs between diversity of solutions and convergence toward the Pareto‐optimal front. It is difficult to achieve such a balance with NP‐hard problems. In this respect, and in order to efficiently explore the search space, a hybrid bidirectional ant‐based approach is proposed in this paper, which is an improvement of a bi‐colony ant‐based approach. Its main characteristic is that it combines a solution construction developed for a more complicated problem with a Pareto‐guided local search engine.     

一种非对称多核SDR的任务调度和分配算法

针对软件无线电(SDR)应用同步数据流的特点,提出一种非对称多核SDR的任务调度和分配算法。该算法综合考虑任务之间的通信时间和任务固定流水,保证任务调度和分配的通用性和并行性。利用整数线性规划(ILP)方法对任务调度和分配进行建模,采用任务拆分方法优化调度和分配的结果,进一步提高任务调度和分配的执行效率。在目标SDR平台上实现IEEE 802.11a频偏估计处理的任务调度和分配,实验结果表明,该算法能提高5.97%的软件无线电平台吞吐量和3.03%的处理器核平均利用率,并减少34.31%的处理器核最长空闲等待时间。     

云环境下基于DPSO的任务调度算法

针对云计算任务调度问题,结合粒子群优化(PSO)算法的种群个体协作和信息共享特点,提出一种基于离散粒子群优化(DPSO)的任务调度算法。采用随机方法生成初始种群,利用时变方式调整惯性权重,并在位置更新中使用绝对值取整求余映射法进行合法化处理,提高PSO算法的离散化程度。搭建并重新编译了CloudSim云计算仿真平台进行实验,结果显示,当迭代次数为200时,DPSO、PSO、GA算法的所有任务最终调度时间分别为457.69 s、467.90 s、472.41 s,从而证明DPSO算法能够有效解决云计算环境下的任务调度问题,并且算法收敛速度优于PSO和GA算法。     

基于同构多核处理器的任务调度

随着现代应用对计算机性能要求的提高,计算机主频不断提升。由于功耗和半导体工艺的限制,仅靠提高单核主频难以继续维持“摩尔定律”,同构多核处理器（Homogeneous Multi-core）应运而生。在同构多核处理器的支持下,一个芯片汇集多个地位对等、结构相同的通用处理器核,以最小的代价满足了提高系统性能、负载均衡、处理器容错的需要。并行体系结构需要结合与之适应的软件实现性能效益的倍增。本文从操作系统层面,针对处理器结构的变化,研究并实现多核任务调度。系统采用混合调度策略,簇间独立调度,簇内统一调度。从调度模式、调度算法、分配算法、调度时机等方面详细分析了多核调度的原理和实现机制。最后通过模拟实验证明功能正确性及算法可调度性。