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1.
在相控阵雷达完成精密跟踪和目标识别等不同任务时,波形、数据率和积累时间等雷达资源需要自适应改变,基于固定长度调度间隔的自适应调度算法较为复杂且不能充分利用雷达资源。提出了一种基于变长度调度间隔的自适应资源调度算法,根据任务请求的重要性函数安排待执行的雷达事件顺序,并根据雷达资源的动态变化情况,自适应地调整调度间隔的时间长度。利用VC语言建模弹道导弹目标和多功能地基相控阵雷达,进行分布式仿真,通过直观观测资源调度的执行过程,以及通过目标跟踪数量和时间利用率两个指标,评价了资源调度算法性能。改进算法的软件实现较为容易,可以增加目标跟踪数量,节约时间资源。  相似文献   

2.
把相控阵雷达各雷达事件交迭编排,可以大大提高雷达的资源利用率。分析了自适应调度算法的设计原理,结合时间、能量和计算机资源等约束条件提出了一种基于交迭编排的自适应调度算法。仿真结果表明其原理上可行,为此算法在相控阵雷达上的应用提供了分析基础。  相似文献   

3.
多功能相控阵雷达自适应调度算法研究   总被引:12,自引:2,他引:10  
由于阵列天线的波束捷变能力 ,多功能相控阵雷达可对多个目标交替进行搜索、验证、跟踪等工作方式的操作。为此 ,需要一种调度策略以有效地分配雷达时间和能量等资源 ,达到优化雷达整体性能的目的。针对多功能相控阵雷达 ,在分析自适应调度算法的设计原则基础上提出一种自适应调度算法 ,并给出具体的性能评估指标。算法能够根据雷达事件的优先级、驻留长度、期望发射时间及时间窗合理地安排一个调度间隔内的雷达事件序列 ,仿真结果验证了调度算法的有效性。  相似文献   

4.
相控阵雷达需要在完成作战空域搜索的同时完成多个目标捕获以及精确跟踪。为了能够及时有效、充分地调度安排雷达时间资源,本文提出了基于动态优先级的雷达自适应调度模型,根据雷达事件调度时间窗偏移及其需求时间片与离散时间片的契合对优先级进行动态调整和排序,完成雷达事件自适应调度,并给出了相控阵雷达应用实例。与基于固定优先级的雷达自适应调度模型相比较,该模型能够提高雷达波束调度成功率和时间资源利用率。  相似文献   

5.
针对相控阵雷达波束快速扫描能力,提出了一种基于时间指针的相控阵雷达在线脉冲交错调度算法。首先建立了雷达驻留任务模型并分析了调度约束条件,然后引入时间指针来指向当前调度分析时刻,分别从波束的角度和脉冲的角度分析了驻留任务交错的几种方式,并给出了三种脉冲重叠方式的时间约束条件,最后在满足时间和能量资源约束的条件下,选取综合优先级最高的雷达驻留任务进行调度。仿真结果表明,与基于收益的调度算法相比,此算法能有效地降低任务丢失率,提高时间利用率和能量利用率。  相似文献   

6.
相控阵雷达与常规机械扫描雷达相比,其对空中目标的探测更加灵活、快速,能够在微秒量级形成定位的雷达波束,先进事件调度方式是发挥这一优势的关键所在。对于固定调度间隔和优先级调度算法,级别较高的事件抢占位置后不再调整,对于冲突的同等级别或级别低的事件进行时间窗内调整。其优点就是运算简单,无需反复调整,同时也产生较多破碎的时间片段,对于平均时间偏移率也无法实现优化调整,浪费雷达有限的资源。本文将弹簧振子模型引入到雷达事件调度算法中,利用弹簧双向调整原理,在最小能量的约束下,实现对雷达申请事件有反馈地自适应调度。结合对弹簧振子固有参数的设计可以在计算量与评价指标之间进行取舍,增加了算法可设计的空间。  相似文献   

7.
现有相控阵雷达资源调度策略通常没有考虑成像任务的要求,需要分出一部分固定资源实现成像功能。该文将认知成像的思想引入到雷达资源自适应调度中,提出一种基于稀疏孔径认知ISAR成像的雷达资源自适应调度算法,并给出了具体的性能评估指标。在对目标特征进行认知的基础上,根据反馈信息对雷达的时间资源进行自适应调度,能够在对不同目标进行跟踪和搜索的同时实现认知成像,从而显著提高了雷达的工作效率。仿真实验验证了该算法的有效性。  相似文献   

8.
针对相控阵雷达事件调度问题中求解目标综合优先级时未考虑事件驻留时间的问题,提出一种基于“价值密度”的相控阵雷达事件调度算法。通过引入作业车间调度领域“价值密度”概念,根据目标属性、运动状态、雷达硬件条件、事件截止期等参数,共同计算雷达完成该事件时单位时间内所能具有的价值,即该事件的价值密度;并基于价值密度进行调度。仿真实验表明,基于价值密度的调度算法与传统基于综合优先级排序调度算法相比,能有效提高调度成功率和实现价值率。  相似文献   

9.
在目标搜索领域,合理安排调度序列能有效提高雷达搜索性能。针对相控阵雷达同时多任务需求,提出了一种基于最大信息增益原则的自适应资源调度搜索算法。在目标先验信息引导下,给出重点搜索区域内波位编排方法,采用最大信息增益原则,在满足时间和能量资源的约束条件下,解决重点区域内目标的最优搜索问题。仿真结果表明,与传统相控阵雷达基于顺序搜索方式相比,该算法能快速发现目标并有效提高搜索数据率和能量利用率,在工程应用中证明该方法是行之有效的。  相似文献   

10.
基于分支定界法的相控阵雷达事件调度算法   总被引:1,自引:0,他引:1       下载免费PDF全文
段毅  谭贤四  曲智国  王红 《电子学报》2019,47(6):1309-1315
为解决相控阵雷达事件调度问题中调度成功率、时间偏移率与算法时效性三者之间的矛盾,本文提出一种基于分支定界法的调度算法;该算法首先在现有调度结果上调取所有可执行事件,即获得若干"节点",多步递推后由多"层"节点形成若干条备选"分支",扩大解空间范围,提高算法性能;然后通过"删减"操作删减掉收益较低分支,将解空间控制在一适当范围内,减小搜索盲目性,降低算法计算量.仿真实验表明,与基于综合优先级算法的调度结果相比,利用本文算法调度时调度成功率提升了52%;与基于时间指针算法的调度结果相比,本身算法时间偏移率降低了61%;与基于遗传算法的调度结果相比,本文算法调度耗时仅为前者1~2%.  相似文献   

11.
公平调度的分组调度算法设计   总被引:2,自引:1,他引:1  
针对无线实时多媒体业务应用,该文在算法Exponential rule (Exp)基础上提出了一种增强调度公平性能的Modified Exponential rule (MExp) 分组调度算法.通过理论分析和系统级仿真对算法性能进行了分析和验证.  相似文献   

12.
We consider the problem of distributed scheduling in wireless networks subject to simple collision constraints. We define the efficiency of a distributed scheduling algorithm to be the largest number (fraction) such that the throughput under the distributed scheduling policy is at least equal to the efficiency multiplied by the maximum throughput achievable under a centralized policy. For a general interference model, we prove a lower bound on the efficiency of a distributed scheduling algorithm by first assuming that all of the traffic only uses one hop of the network. We also prove that the lower bound is tight in the sense that, for any fraction larger than the lower bound, we can find a topology and an arrival rate vector within the fraction of the capacity region such that the network is unstable under a greedy scheduling policy. We then extend our results to a more general multihop traffic scenario and show that similar scheduling efficiency results can be established by introducing prioritization or regulators to the basic greedy scheduling algorithm  相似文献   

13.
Leakage-Aware Multiprocessor Scheduling   总被引:2,自引:0,他引:2  
When peak performance is unnecessary, Dynamic Voltage Scaling (DVS) can be used to reduce the dynamic power consumption of embedded multiprocessors. In future technologies, however, static power consumption due to leakage current is expected to increase significantly. Then it will be more effective to limit the number of processors employed (i.e., turn some of them off), or to use a combination of DVS and processor shutdown. In this paper, leakage-aware scheduling heuristics are presented that determine the best trade-off between these three techniques: DVS, processor shutdown, and finding the optimal number of processors. Experimental results obtained using a public benchmark set of task graphs and real parallel applications show that our approach reduces the total energy consumption by up to 46% for tight deadlines (1.5× the critical path length) and by up to 73% for loose deadlines (8× the critical path length) compared to an approach that only employs DVS. We also compare the energy consumed by our scheduling algorithms to two absolute lower bounds, one for the case where all processors continuously run at the same frequency, and one for the case where the processors can run at different frequencies and these frequencies may change over time. The results show that the energy reduction achieved by our best approach is close to these theoretical limits.
Ben JuurlinkEmail:
  相似文献   

14.
The long and increasing test application time for modular core-based system-on-chips is a major problem, and many approaches have been developed to deal with the problem. Different from previous approaches, where it is assumed that all tests will be performed until completion, we consider the cases where the test process is terminated as soon as a defect is detected. Such abort-on-fail testing is common practice in production test of chips. We define a model to compute the expected test time for a given test schedule in an abort-on-fail environment. We have implemented three scheduling techniques and the experimental results show a significant test time reduction (up to 90%) when making use of an efficient test scheduling technique that takes defect probabilities into account. The research is partially supported by the Swedish National Program STRINGENT.  相似文献   

15.
《中兴通讯技术》2017,(1):15-20
结合窄带物联网(NB-IoT)系统的上下行帧结构、复用方式、调度单元的特点,提供了适用于NB-IoT系统的资源调度的设计方案,包括非连续的下行调度、动态的上下行调度定时以及跨多个调度单元的上下行资源分配。采用上述方案,避免了在极端或增强覆盖场景下,因下行资源的连续占用所导致的对其他终端设备的上下行授权和下行业务传输的阻塞以及下行控制资源的浪费,同时确保了相对灵活的资源分配。  相似文献   

16.

This paper presents a Function-as-a-Service (FaaS) approach for deploying managed cloud functions onto heterogeneous cloud infrastructures. Current FaaS systems, such as AWS Lambda, allow domain-specific functionality, such as AI, HPC and image processing, to be deployed in the cloud while abstracting users from infrastructure and platform concerns. Existing approaches, however, use a single type of resource configuration to execute all function requests. In this paper, we present a novel FaaS approach that allows cloud functions to be effectively executed across heterogeneous compute resources, including hardware accelerators such as GPUs and FPGAs. We implement heterogeneous scheduling to tailor resource selection to each request, taking into account performance and cost concerns. In this way, our approach makes use of different processor types and quantities (e.g. 2 CPU cores), uniquely suited to handle different types of workload, potentially providing improved performance at a reduced cost. We validate our approach in three application domains: machine learning, bio-informatics, and physics, and target a hardware platform with a combined computational capacity of 24 FPGAs and 12 CPU cores. Compared to traditional FaaS, our approach achieves a cost improvement for non-uniform traffic of up to 8.9 times, while maintaining performance objectives.

  相似文献   

17.
针对资源受限的项目调度问题,提出了一种离散粒子群算法与扩展调度机制相结合的优化方法.离散粒子群算法中每个粒子的位置代表一组项目任务的优先权,迭代中通过交叉策略和局部搜索策略来更新粒子的位置,这既保持了粒子位置的离散性,又增加了粒子的多样性,避免早熟收敛.每个粒子的位置通过扩展串行调度机制转换成可行的调度方案.实算表明,扩展调度机制的引入显著地加速了收敛的进程,提高了解的精度.这种基于粒子群算法的扩展调度优化方法是求解资源受限项目调度问题的有效方法.  相似文献   

18.
Cache的缺失严重影响着计算机系统的运行效率.现代构件化软件架构中模块化程度越来越高,操作系统中传统的调度策略忽视任务的模块特性,若模块具有特定的代码/数据访问集合,模块间不合理的任务调度会导致严重的Cache缺失.本文提出了一种基于模块的调度策略MBS,可以尽量连续调度同一模块中的任务,尤其适应于构件化的服务系统.分析与实验结果表明,MBS可以有效减少此类系统的Cache缺失,明显提高系统性能.  相似文献   

19.
Gang scheduling is an efficient resource management scheme for distributed systems which combines elements of time sharing and space sharing. It is a suitable technique particularly in the case when parallel tasks have to be running concurrently to make progress in communication. This paper studies the impact on scheduling performance when dynamically generated sequential gangs exist in the workload. In the case of sequential gangs, a subsequent gang can be dynamically generated after the execution of the initial gang based on affinity information which resides on the caches of the previously seized processors. The performance of different gang‐scheduling algorithms is examined for various cases of workload compositions which range from cases with a low demand for dynamically generated gangs to cases with a high ratio of sequential gangs to solitary gangs. A simulation model is implemented to address associated performance issues. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

20.
Reducing energy consumption has become an important issue in designing hardware and software systems in recent years. Although low power hardware components are critical for reducing energy consumption, the switching activity, which is the main source of dynamic power dissipation in electronic systems, is largely determined by the software running on these systems.In this paper, we present and evaluate several instruction scheduling algorithms that reorder a given sequence of instructions taking into account the energy considerations. We first compare a performance-oriented scheduling technique with three energy-oriented instruction scheduling algorithms from both performance (execution cycles of the resulting schedules) and energy consumption points of view. Then, we propose three scheduling algorithms that consider energy and performance at the same time. Our experimentation with these scheduling techniques shows that the best scheduling from the performance perspective is not necessarily the best scheduling from the energy perspective. Further, scheduling techniques that consider both energy and performance simultaneously are found to be desirable, that is, these techniques are quite successful in reducing energy consumption and their performance (in terms of execution cycles) is comparable to that of a pure performance-oriented scheduling. We also illuminate the inherent approximations and difficulties in building energy models for enabling energy-aware instruction scheduling and explore alternative options using cycle-accurate energy simulator. The simulation results show that the energy-oriented scheduling reduces energy consumption by up to 30% compared to the performance-oriented scheduling.  相似文献   

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