基于改进人工免疫算法的云计算任务调度

为了提高云计算任务调度效率,提出一种改进人工免疫算法的云计算任务调度方法。首先建立云计算任务调度的数学模型,并以任务总时间最短作为目标函数,然后采用人工免疫算法进行求解,并将粒子群优化算法作为算子嵌入人工免疫算法中,保持种群的多样性,防止局部最优解的出现,最后采用仿真实验对算法的性能进行测试。结果表明,相对于其它算法,改进人工免疫算法减少了任务的完成时间,提高了用户满意度。     

基于遗传算法的Pareto多目标配电网重构

配电网重构一般采用对单一目标优化,而配电网重构却是一个多目标优化问题。因此,在此提出了基于小生境思想的遗传算法,以配电网的经济性、安全性和供电可靠性为目标,并采用Pareto寻优方式,得出Pareto最优解集,实现了和以往不同的另一种寻优方式,即先寻优后决策。在寻优过程中,通过小生境环境和交叉率和变异率的自适应机制,提高了遗传算法的全局收敛能力和收敛速度,并通过算例验证了方法的有效性。     

CoMP系统低复杂度集中式调度算法研究

在3GPPLTE—A网络中,可以使用CoMP（多点协作）技术来提高边缘用户的性能。为了最大化全网边缘用户的总吞吐量,关键是要确定在每个PRB（物理资源块）中同时被服务的用户集合、每个被调度用户所对应的协作基站、以及各基站的传输功率。基于每个边缘用户的RSRP（参考信号接收功率）,提出一种低复杂度的集中式传输调度算法,针对每个PRB中被服务的边缘用户和相应的协作基站进行动态选择,并通过仿真实验验证算法的性能增益。     

基于BPEL和Drools的车间调度研究

现代企业的应用程序和信息已成为公司相当重要的资产,大多数企业都希望此应用能够提供业务流程全面的支持.这就意味着应用程序和业务流程应该紧密结合,然而,应用程序的每次修改都会减少其结构对其未来变化的鲁棒性.基于对业务流程通信便捷性的目的,本文采用实例验证的方法,结合Drools优化车间调度问题,用Web Sevices 和BPEL加以实现,并以机械加工流程为例加以验证,得出了BPEL和Drools结合能够较好实现加工流程的多服务调用和交互和通信的结论.     

西康铁路远动系统改造设计

本文介绍了将西安至安康铁路牵引供变电设施纳入襄渝二线电力牵引远动系统实施实时数据采集和集中监控管理的改造设计,并明确了改造后达到的的调度系统功能及系统基本技术指标。     

The Role of Test Protocols in Automated Test Generation for Embedded-Core-Based System ICs

Modular testing is an attractive approach to testing large system ICs, especially if they are built from pre-designed reusable embedded cores. This paper describes an automated modular test development approach. The basis of this approach is that a core or module test is dissected into a test protocol and a test pattern list. A test protocol describes in detail how to apply one test pattern to the core, while abstracting from the specific test pattern stimulus and response values. Subsequent automation tasks, such as the expansion from core-level tests to system-chip-level tests and test scheduling, all work on test protocols, thereby greatly reducing the amount of compute time and data involved. Finally, an SOC-level test is assembled from the expanded and scheduled test protocols and the (so far untouched) test patterns. This paper describes and formalizes the notion of test protocols and the algorithms for test protocol expansion and scheduling. A running example is featured throughout the paper. We also elaborate on the industrial usage of the concepts described.     

Response Time in Data Broadcast Systems: Mean,Variance and Tradeoff

Data broadcast has been suggested as a promising method of information dissemination [2,33]. In such an environment, the information server cannot afford to serve the requests from a large population of users individually. Instead, the server uses a broadcast channel to deliver information to all users. A single transmission of a data item satisfies all pending requests for that item. The response time of a request depends on the broadcast time of the desired data item, which is scheduled by the server according to the overall demands for various data items. Therefore, the response time may vary in a large range. We argue that, in addition to mean response time, the variance of response time should also be taken into account by the broadcast scheduler. In this paper, we address the issue of variance optimization in regard to response time. Building on our previous research on mean response time optimization, we propose an algorithm which can minimize the variance of response time. Furthermore, we evaluate an algorithm that facilitates a tradeoff between the mean and variance of response time. Numerical examples that illustrate the performance of our algorithms are also presented.     

IMPACCT: Methodology and Tools for Power-Aware Embedded Systems

Power-aware systems are those that must exploit a widerange of power/performance trade-offs in order to adapt to the power availabilityand application requirements. They require the integration of many novel powermanagement techniques, ranging from voltage scaling to subsystem shutdown.However, those techniques do not always compose synergistically with eachother; in fact, they can combine subtractively and often yield counterintuitive,and sometimes incorrect, results in the context of a complete system. Thiscan become a serious problem as more of these power aware systems are beingdeployed in mission critical applications.To address the problem of technique integration for power-aware embedded systems, we propose a new design tool framework called IMPACCT and the associated design methodology. The system modeling methodology includes application model for capturing timing/powerconstraints and mode dependencies at the system level. The tool performs power-awarescheduling and mode selection to ensure that all timing/power constraintsare satisfied and that all overhead is taken into account. IMPACCT then synthesizesthe implementation targeting a symmetric multiprocessor platform. Experimentalresults show that the increased dynamic range of power/performance settingsenabled a Mars rover to achieve significant acceleration while using lessenergy. More importantly, our tool correctly combines the state-of-the-arttechniques at the system level, thereby saving even experienced designersfrom many pitfalls of system-level power management.     

Earliest Deadline First Scheduling with Active Buffer Management for Real-Time Traffic in the Internet

We studied the problem of QoS guarantee for differentiated services. A two-level hierarchical scheduling framework was deployed to separate QoS metrics. Due to its desirable property of minimizing the maximum packet lateness, the Earliest Deadline First (EDF) scheduling was adopted to provide the in-class scheduling for the time-sensitive traffic. We employed an EDF scheduler combined with an active buffer management scheme (CHOKe) to improve the fairness of resource allocation and to maintain a good delay performance for real-time applications. Simulation results showed that the proposed scheme can achieve a better delay performance and make a more fair bandwidth allocation between the real-time TCP and UDP connections than the First Come First Served (FCFS) scheduling with the drop-tail buffer management which is commonly deployed in traditional IP routers.     

Dual-Radio传感器网络中一种多功率多信道数据收集调度策略

MMDC首先为每个节点构造数据收集的能量消耗最优路径;然后考虑网内通信冲突、数据收集时延等因素,构建MPST,使数据收集能耗小、冲突少、时延低;最后在MPST的基础上运用CALS完成数据收集,CALS借助较少的Radio和信道,消除链路间的通信冲突与干扰,实现多条链路无冲突并行收发数据,从而优化数据收集效率.实验结果表明,MMDC可有效降低数据转发时延,缩短数据收集时间,减少网络能量消耗,提高网络吞吐量.