基于拟态防御架构的服务功能链执行体动态调度方法

面对静态、滞后的传统防御技术无法有效应对新型网络攻击的问题,根据拟态安全防御理论,提出了一种建立在数据转发层面的拟态服务功能链(mimic service function chain,MSFC)防御架构,基于该架构进一步提出了一种基于判决反馈的执行体动态调度方法。该方法以判决器反馈的异常执行体信息、执行体的异构度以及系统的实际负载量作为调度影响因素,使调度方法可以根据网络实际变化进行自适应调整。此外,该调度方法利用判决反馈对调度时间进行调整,以达到系统花费与安全性的最佳平衡,降低了系统的资源开销。仿真结果表明,该调度方法可以在平衡系统花费与安全性的基础上,选出更符合当前网络需求的高异构度执行体集合,从而提升系统的安全性及可靠性。     

拟态多执行体调度算法研究进展

拟态防御是一种基于动态异构冗余架构的新型主动防御技术,具有内在不确定、异构、冗余及负反馈等特性,从而能显著提高系统稳健性和安全性.其中多执行体调度算法是拟态防御技术的关键,其优劣直接影响拟态系统抵抗基于已知或未知漏洞后门攻击的能力.基于此,首先介绍了拟态调度算法技术和目标,然后从调度对象、调度数量及调度时机这3个方面对...     

基于滚动周期粒子群算法的雷达组网协同分配方法

针对反导预警系统执行饱和弹道导弹目标攻击场景中的雷达实时任务分配问题,提出一种资源约束下基于动态自适应滚动周期混合粒子群算法的多任务协同分配方法。根据弹道导弹的目标特性,建立了任务综合优先级规划模型;为了实现分配效能最大化,考虑资源约束的基础上建立了雷达资源利用率、任务综合价值实现率、雷达切换次数、任务调度成功率为目标函数的雷达组网多任务资源分配模型,基于离散粒子群算法进行粒子迭代逻辑优化,满足算子自适应的选择、变异及交叉操作;为适应战场环境的动态复杂特性,建立了滚动周期调度模型和事件重调度模型,设计的协同调度策略很好地满足了实时性的要求。仿真结果表明,在饱和场景下使用基于动态自适应滚动周期混合粒子群算法能够有效解决实时雷达组网多任务协同分配问题。     

面向持久性连接的自适应拟态表决器设计与实现

针对当前拟态表决器以连接为单位“连接内数据传输结束后再表决、转发”的机制难以适应HTTP 1.1协议在持久性连接、分块传输编码的应用场景中开销过大的问题,设计实现了面向持久性连接的自适应拟态表决器,在数据持续传输过程中滑动窗口式表决、释放异构冗余执行体的分块传输编码报文,通过分析滑动窗口式表决的分块传输编码报文的数据特征,构建了表决算法选择策略集,给出了表决准确性维护方案;提出了基于存贮模型的自适应表决窗口控制策略,为待表决数据提供最佳的切分方案。基于原型系统的实验结果表明,自适应拟态表决器在具有可接受的表决准确度下,降低了内存开销并提升了拟态表决效率。     

基于高阶异构度的执行体动态调度算法

针对当前动态异构冗余系统中异构体调度缺乏动态性和仅考虑二阶异构性,导致系统易被攻击者找到共模漏洞从而攻破系统的问题,提出了一种同时考虑执行体高阶异构度和历史信息的异构执行体动态调度算法——基于高阶异构度的负反馈调度算法.该算法首先计算等待池中执行体的高阶异构度矩阵,然后在每次调度执行体时同时考虑历史威胁和异构体间的高阶...     

基于执行体划分的防御增强型动态异构冗余架构

针对DHR系统服务体在面临共同漏洞时的系统脆弱性问题,提出了一种改进的DHR架构——IDHR.该架构在DHR的基础上,首先引入根据执行体间的异构性对执行体集进行划分的执行体划分模块,以极大增强各执行体池之间的异构性.在此基础上,改进调度模块中的动态选择算法,即采用先随机选择执行体池,再从执行体池中随机选择执行体的方式,...     

面向拟态云服务的异构执行体调度算法

针对当前异构调度模型仅从空间或者时间特性进行建模设计,缺少对时空特性的综合考虑且存在动态性和异构性不够均衡的问题。为使拟态云服务系统的动态、异构和冗余特性能够平衡互补,提出一种基于优先级和时间片的执行池调度算法,该算法基于执行池相似性指标进行优先级预排序,结合时间片等策略进行方案调度。实验结果表明,所提算法有较好的动态性,结合时间片策略能够获得动态性和异构性的综合平衡,且算法耗时较低。     

基于自适应调度间隔的雷达事件调度算法

针对雷达事件调度中基于固定调度间隔进行调度时雷达资源利用率不高、调度成功率较低的问题,提出一种基于自适应调度间隔的调度算法：设置一时间指针,调取该指针下所有可执行事件,依次计算这些事件收益并选取收益最高事件执行;递推该指针直至该调度间隔内无法执行任何事件;提前结束该调度间隔并将该间隔剩余资源“传递”至下一调度间隔;重复上述步骤直至调度完结。仿真实验表明,与基于固定调度间隔的调度算法相比,基于自适应调度间隔的调度算法能够有效减少“时间碎片”的形成,提高实现价值率与时间利用率。     

边缘计算环境下网络拓扑拟态关联图与主动防御模型研究

为了提高网络攻击的防御能力,提出一种边缘计算环境下网络拓扑拟态关联图与主动防御模型,该模型在半盲攻击的情况下,根据网络安全可靠性来动态调整网络拓扑拟态关联图,在保证网络通信路径多样性的基础上动态调整网络存活时隙,实现网络攻击的主动有效防御。实验证明,的算法与简单拓扑算法相比,动态调整存活时隙增加DDoS攻击的难度,从而保证网络具有主动防御的功能,更加适用于边缘计算网络环境。因此,算法在实际边缘计算的网络环境中将具有较好的应用价值。     

一种面向安全的虚拟网络功能动态异构调度方法

网络功能虚拟化(NFV)为服务链构建带来了灵活性与动态性,然而,软件化与虚拟化环境可能存在软件漏洞、后门等安全风险,对服务链(SC)的安全产生影响。为此,该文提出一种服务链上虚拟网络功能(VNF)调度方法。首先,为虚拟网络功能构建异构镜像池,避免利用共模漏洞的大范围攻击;随后,以特定周期选择服务链虚拟网络功能进行调度,加载异构镜像对该网络功能的执行实体进行替换;最后,考虑调度对网络功能性能的影响,应用斯坦科尔伯格博弈对攻防过程建模,以最优化防御者收益为目标求解服务链上各网络功能的调度概率。实验表明,该方法能够降低攻击者攻击成功率,同时将调度产生的开销控制在可接受范围内。     

面向业务可达性的广域工业互联网调度算法研究

工业互联网业务呈现出小规模、确定性的特征,通常运行在大规模、异构的网络环境中,业务的调度与功能链的编排难以与异构承载网资源匹配。基于此该文提出非工作保持型的多节点联合调度模型,首先采用全路径时间协调算法,将功能链从空间维度的拓扑编排扩展至时空维度;其次,针对网络节点中的同步调度问题,提出了基于紧急度的流调度算法来平滑时延抖动,进一步,将时间触发调度延拓到大规模、异构且非同步的承载网中,提出了虚拟到达队列编排算法,利用业务同步机制替代时间同步,保障了业务确定的可达性需求。仿真实验表明该文所提算法可提升业务的可达性,保障其满足及时性、准时性、协同性需求。     

Heterogeneous redundancies scheduling algorithm for mimic security defense

The scheduling of heterogeneous redundancies is one of the key lines of mimic security defense,but the existing scheduling strategies are lack of consideration about the similarity among redundancies and the scheduling algorithms are incomprehensive.A new scheduling algorithm called random seed & minimum similarity (RSMS) algorithm was proposed,which combined dynamics and reliability by determining a scheduling scheme with minimum global-similarity after choosing a seed-redundancy randomly.Theoretical analysis and simulation results show that RSMS algorithm possessed a far longer scheduling cycle than maximum dissimilarity algorithm,as well as a far lower failure rate than random scheduling algorithm,which represents an effective balance between dynamics and reliability.     

A genetic algorithm‐based task scheduling for cloud resource crowd‐funding model

With the rapid development of cloud computing, the number of cloud users is growing exponentially. Data centers have come under great pressure, and the problem of power consumption has become increasingly prominent. However, many idle resources that are geographically distributed in the network can be used as resource providers for cloud tasks. These distributed resources may not be able to support the resource‐intensive applications alone because of their limited capacity; however, the capacity will be considerably increased if they can cooperate with each other and share resources. Therefore, in this paper, a new resource‐providing model called “crowd‐funding” is proposed. In the crowd‐funding model, idle resources can be collected to form a virtual resource pool for providing cloud services. Based on this model, a new task scheduling algorithm is proposed, RC‐GA (genetic algorithm for task scheduling based on a resource crowd‐funding model). For crowd‐funding, the resources come from different heterogeneous devices, so the resource stability should be considered different. The scheduling targets of the RC‐GA are designed to increase the stability of task execution and reduce power consumption at the same time. In addition, to reduce random errors in the evolution process, the roulette wheel selection operator of the genetic algorithm is improved. The experiment shows that the RC‐GA can achieve good results.     

分层异构信号处理平台调度方法研究

异构多处理器的高效性和可靠性能够满足日趋复杂的信号处理任务需求,因此分层异构系统已成为信号处理平台的发展趋势.为提高平台强实时性并解决高吞吐量的问题,文中对分层异构信号处理平台的软硬件模块及架构进行了研究,并采用有向无环图对组件任务及硬件资源进行建模.将已提出的调度算法按照任务类型、调度目标、调度过程和研究方法进行分类...     

基于双仲裁机制和田口正交法的猫群优化任务调度算法

针对异构计算系统任务调度过程中通信冲突以及算法运行时间的问题,该文提出一种基于双仲裁机制和田口正交法的猫群优化任务调度算法。首先利用双仲裁机制对任务资源进行管理,动态判决任务的分配,有效避免通信冲突,再将田口正交法应用到猫群优化过程的跟踪模式中,降低算法运行时间,提高解的质量。实验结果表明,该算法运行速度明显高于其他算法至少约10%,算法在处理大量任务时的并行化效果最优,在异构环境中也体现出其相当大的优势。     

Resource scheduling in mobile edge computing using improved ant colony algorithm for space information network

With the development of space information network (SIN), new network applications are emerging. Satellites are not only used for storage and transmission but also gradually used for calculation and analysis, so the demand for resources is increasing. But satellite resources are still limited. Mobile edge computing (MEC) is considered an effective technique to reduce the pressure on satellite resources. To solve the problem of task execution delay caused by limited satellite resources, we designed Space Mobile Edge Computing Network (SMECN) architecture. According to this architecture, we propose a resource scheduling method. First, we decompose the user tasks in SMECN, so that the tasks can be assigned to different servers. An improved ant colony resource scheduling algorithm for SMECN is proposed. The heuristic factors and pheromones of the ant colony algorithm are improved through time and resource constraints, and the roulette algorithm is applied to route selection to avoid falling into the local optimum. We propose a dynamic scheduling algorithm to improve the contract network protocol to cope with the dynamic changes of the SIN and dynamically adjust the task execution to improve the service capability of the SIN. The simulation results show that when the number of tasks reaches 200, the algorithm proposed in this paper takes 17.52% less execution time than the Min-Min algorithm, uses 9.58% less resources than the PSO algorithm, and achieves a resource allocation rate of 91.65%. Finally, introducing dynamic scheduling algorithms can effectively reduce task execution time and improve task availability.     

前言

人们对后3G的要求是:在全球范围内实现无缝覆盖,进行包括语音、文本、图像、视频等在内的高速多媒体通信。为此,在有限频谱资源条件下,必须缩短无线信号的传输半径,极大限度地复用频谱资源,提高单位空间的信道容量。采用各种先进的无线传输技术的无线传输网络则在中、小范围内提供高速率、高质量的无线移动通信服务。因而WLAN和WPAN的需求和应用在不断增长,超宽带(UWB,ultra wide-band)等短距离、高空间容量的技术日益兴起,成为目前无线通信领域的热点。UWB的核心是冲激无线电技术,即利用持续时间非常短(纳秒、亚纳秒级)的脉冲波形来…     

Scheduling strategy for networked control system based on variable sampling period and deadband feedback

A scheduling strategy of variable sampling period combined with deadband feedback for networked control system is proposed. Variable sampling period algorithm can allocate a reasonable sampling period to each controlled loop according to the network utilization and packet transmission time. Deadband feedback algorithm can alleviate network congestion by appropriately adjusting the packets in the network when the networked control system cannot be scheduled. According to the actual overload and utilization of the network, the designed scheduling strategy dynamically adjusts the sampling period and priority, and improves the performance of the system combined with deadband feedback. Based on the TrueTime platform, the proposed scheduling strategy is verified on a three controlled loops networked control system with interference nodes and limited network resources. The simulation results demonstrate that the designed scheduling strategy can overcome the uncertainty of the upper bound of network resources, improve output control performance, reduce integral absolute error value of the controlled loop, and shorten the packet transmission time. The overall control performance of the system is improved. The designed scheduling strategy is effective.