Vertical partitioning for flash and HDD database systems

Recent advances in flash memory technology have greatly enhanced the capability of flash memory to address the I/O bottleneck problem. Flash memory has exceptional I/O performance compared to the hard disk drive (HDD). The superiority of flash memory is especially visible when dealing with random read patterns. Even though the cost of flash memory is higher than that of HDD storage, the popularity of flash memory is increasing at such a pace that it is becoming a common addition to the average computer. Recently, flash memory has been made into larger devices called solid state drives (SSDs). Although these devices can offer capacities comparable to HDDs, they are considerably more expensive per byte.Our research aims to increase the I/O performance of database systems by using a small amount of flash memory alongside HDD storage. The system uses a fully vertically partitioned storage structure where each column is stored separately on either the HDD or SSD. Our approach is to assign the columns into the SSD which will benefit the most from the characteristics of flash memory. We prove this problem is NP-complete and propose an optimal dynamic programming solution and a faster greedy heuristic solution.A system simulator has been implemented and experiments show that the overall I/O costs can be greatly reduced using only a limited amount of flash memory. The results show the greedy heuristic solution performed similarly to the more expensive dynamic programming solution for the situations tested.     

Asymptotic stability of block boundary value methods for delay differential-algebraic equations

Block boundary value methods are applied to solve a class of delay differential-algebraic equations. We focus on the asymptotic stability of the numerical methods for linear delay differential-algebraic equations with multiple delays. It is shown that A-stable block boundary value methods satisfying a restrictive condition can preserve the asymptotic stability of the analytical solution. Numerical experiments further confirm the effectiveness and stability of the methods.     

Partition oriented frame based fair scheduler

Proportionate fair schedulers provide an effective methodology for scheduling recurrent real-time tasks on multiprocessors. However, a drawback in these schedulers is that they ignore a task’s affinity towards the processor where it was executed last, causing frequent inter-processor task migrations which ultimately results in increased execution times. This paper presents Partition Oriented Frame Based Fair Scheduler (POFBFS), an efficient proportional fair scheduler for periodic firm and soft real-time tasks that ensures a bounded number of task migrations. Experimental results reveal that POFBFS can achieve 3 to 100 times reduction in the number of migrations suffered with respect to the General-ERfair algorithm (for a set of 25 to 100 tasks running on 2 to 8 processors) while simultaneously maintaining high fairness accuracy.     

Delay‐dependent robust H∞ control for uncertain stochastic time‐delay systems

This paper investigates the robust H_∞ control problem for stochastic systems with a delay in the state. Sufficient delay‐dependent conditions for the existence of state‐feedback controllers are proposed to guarantee mean‐square asymptotic stability as well as the prescribed H_∞ performance for the closed‐loop systems. Moreover, the results are further extended to the stochastic time‐delay systems with parameter uncertainties, which are assumed to be time‐varying norm‐bounded appearing in both the state and the input matrices. The appealing idea is to partition the delay, which differs greatly from the most existing results and reduces conservatism by thinning the delay partitioning. Numerical examples are provided to show the advantages of the proposed techniques. Copyright © 2009 John Wiley & Sons, Ltd.     

Combining temporal partitioning and temporal placement techniques for communication cost improvement

In this paper, we present a typical temporal partitioning methodology that temporally partitions a data flow graph on reconfigurable system. Our approach optimizes the communication cost of the design. This aim can be reached by minimizing the transfer of data required between design partitions and the routing cost between FPGA modules. Consequently, our algorithm is composed by two main steps. The first step aims to find a temporal partitioning of the graph. This step gives the optimal solution in term of communication cost. Next, our approach builds the best architecture, on a partially reconfigurable FPGA, that gives the lowest routing cost between modules. The proposed methodology was tested on several examples on the Xilinx Virtex-II pro. The results show significant reduction in the communication cost compared with others famous approaches used in this field.     

一种基于剪枝的横向分块概念格构造算法

概念格是形式概念分析中的核心数据结构,随着数据量的日益剧增,概念格的构造效率始终是关键.本文首先引入横向分块概念格,给出其若干结论;针对横向分块概念格构造过程中存在冗余信息,提出一种基于剪枝的横向分块概念格渐进式构造算法PHCL,从而进一步提高了概念格的构造效率;最后采用恒星天体光谱数据作为形式背景,实验验证了算法PHCL的正确性和有效性.     

复杂区域节点定位算法研究

传统的无线传感器网络节点定位算法假设节点间的最短路径长度与实际几何距离之间存在函数映射关系.然而对于布设在复杂区域的无线传感器网络而言,这种函数映射关系不再成立,直接应用传统定位算法将会带来较大的定位误差.针对复杂区域中各向异性的无线传感器网络节点定位问题,提出了一种基于参考节点凸包划分的测距无关定位算法CHP.首先,...     

集群计算环境下基于复杂网络的社会学仿真负载划分优化算法

负载划分是决定集群计算环境下基于复杂网络的并行社会学仿真性能的核心因素之一.由于背景负载等因素的影响,集群系统中往往需要根据实际可用计算资源非均匀分配仿真任务,而现有针对无标度特性拓扑结构的并行仿真负载划分算法无法适应集群环境下计算负载非均匀划分的需求.针对这一问题,提出了一个基于集散节点聚合的负载划分算法,将集群计算...     

基于OPNET的一种典型现场总线的研究与仿真

随着网络规模的扩大,使用仿真软件对网络进行仿真,对关键参数和原理进行验证,已经是一种流行的网络开发模式.首先对现场总线和仿真软件OPNET进行了相关介绍和分析,接着对一种典型的现场总线的特征进行了详细说明,然后基于OPNET对该典型总线进行了建模仿真.基于对采集数据的分析,验证了仿真模型的时延符合典型现场总线标准的要求...     

A new heuristic algorithm for the operating room scheduling problem

Due to the great importance of operating rooms in hospitals, this paper studies an operating room scheduling problem with open scheduling strategy. According to this strategy, no time slot is reserved for a particular surgeon. The surgeons can use all available time slots. Based on Fei et al.’s model which is considered to be close to reality, we develop a heuristic algorithm to solve it. The idea of this heuristic algorithm is from dynamic programming by aggregating states to avoid the explosion of the number of states. The objective of this paper is to design an operating program to maximize the operating rooms’ use efficiency and minimize the overtime cost. Computational results show that our algorithm is efficient, especially for large size instances where our algorithm always finds feasible solutions while the algorithm of Fei et al. does not.