改善iSCSI存储系统性能的优化策略

针对iSCSI在磁盘I/O和网络传输速度上存在的瓶颈问题,提出了一种改进的iSCSI存储架构.根据请求包大小动态的选择存储策略,目标端采用提出的并行算法对包进行处理,并且消除了写冗余并减少了对同一扇区多次读操作的冗余.实验结果表明,该策略有效地缩短了系统的响应时间,提高了系统的吞吐量,从而达到优化iSCSI存储系统性能的目的.     

Using intermediate objects to improve the efficiency of visual search

When using a mobile camera to search for a target object, it is often important to maximize the efficiency of the search. We consider a method for increasing efficiency by searching only those subregions that are especially likely to contain the object. These subregions are identified via spatial relationships. Searches that use this method repeatedly find an “intermediate” object that commonly participates in a spatial relationship with the target object, and then look for the target in the restricted region specified by this relationship. Intuitively, such searches, calledindirect searches, seem likely to provide efficiency increases when the intermediate objects can be recognized at low resolutions and hence can be found with little extra overhead, and when they significantly restrict the area that must be searched for the target. But what is the magnitude of this increase, and upon what other factors does efficiency depend? Although the idea of exploiting spatial relationships has been used in vision systems before, few have quantitatively examined these questions. We present a mathematical model of search efficiency that identifies the factors affecting efficiency and can be used to predict their effects. The model predicts that, in typical situations, indirect search provides up to an 8-fold increase in efficiency. Besides being useful as an analysis tool, the model is also suitable for use in an online system for selecting intermediate objects.     

混合策略改进正弦余弦算法

为提高正弦余弦算法在求解函数优化问题的性能,提出混合策略改进正弦余弦算法。首先,利用正切函数作为调节因子代替原本线性变化的参数,用于平衡算法的全局探索和局部开发;然后,引入权重系数,用于控制位置更新处个体上一代位置的影响力,有效提高算法开发能力和寻优速度;最后,构建逐维交叉学习策略,克服最优解无更新的缺点,对最优个体进行扰动更新,跳出局部最优,避免早熟收敛。在不同维数的八个基准函数上进行仿真实验。实验表明,该算法相对于其他群智能优化算法具有更高的寻优精度和收敛速度,相比于最新的正弦余弦改进算法,也表现出更好的收敛性能和稳定性。     

混合策略改进的蝴蝶优化算法

针对蝴蝶优化算法存在的求解精度低、易陷入局部最优等缺陷,提出混合策略改进的蝴蝶优化算法.首先,利用Circle映射初始化蝴蝶个体的位置,增加初始个体的多样性;其次,在局部搜索阶段利用动态切换概率控制改进正弦余弦算法与蝴蝶优化算法的转换,充分利用少量的蝴蝶个体,增强算法的局部开发能力;然后,在全局和局部位置更新处引入自适应余切权重系数,控制蝴蝶个体下一代的移动方向和距离,提高算法的收敛速度和精度;最后,引入逐维变异策略,对全局最优位置变异,引导种群向最优位置进化,避免陷入局部最优.对八个基准函数进行仿真实验,结果表明,改进算法的收敛性能更佳,与其他改进算法相比具有一定的竞争力.     

快速提高NSGA-Ⅱ算法双目标优化效率的方法

NSGA-Ⅱ是一种性能优良的多目标进化算法,近年来非常流行。为了进一步改进NSGA-Ⅱ在双目标优化时的效率,采取了按需分层的策略,提出了一种新的非支配前沿集分层方法以替代NSGA-II原有的分层方法。与NSGA-Ⅱ的时间复杂度O(N2)相比,新方法的时间复杂度减少为O(kN+NlogN),k为所分前沿层数(k<相似文献   

An algorithm to improve the computational efficiency of genetic linkage analysis

The computational complexity of genetic linkage analysis can increase exponentially with the square of the number of alleles at a marker locus. Many of the most informative marker loci have a large number of associated alleles. The precise identities of the alleles are irrelevant to the linkage analysis so long as identity-by-descent and linkage-phase information are preserved. This paper introduces an algorithm which, by relabeling, reduces the number of alleles at the marker locus, thereby increasing the speed of the analysis. The relabeling scheme preserves linkage-phase and identity-by-descent information so the results of the analysis are unaffected. Unlike previously published methods, this algorithm can be applied to pedigrees of arbitrary structure with both complete and incomplete phenotypic information.     

Fuzzy FMEA application to improve decision-making process in an emergency department

Hospitals are one of the important service industries of health care for patients. The emergency department is the heart of every hospital, because the errors or failures occurring in it will significantly affect the safety of patients and the goodwill of the hospital. Therefore, emergency departments should be monitored carefully. This study proposed the application of Fuzzy failure mode and effects analysis (FMEA) for prioritization and assessment of failures that likely occur in the working process of an emergency department. All individuals were assessed independently without the interference of team members. In addition, this method could reduce the limitations of traditional FMEA. The prioritization of risks could also help the emergency department to choose corrective actions wisely. In conclusion, the Fuzzy FMEA method was found to be suitably adopted in the emergency department. Finally, this method helped to increase the level of confidence on hospitals.     

Using interpolation to improve efficiency of multiparametric predictive control

Multi-parameteric quadratic programming (MPQP) gives a full offline solution to a time-varying quadratic programming (QP) problem arising during constrained predictive control. However, coding and implementation of this solution may be more burdensome than simply solving the original QP. This paper shows how interpolation can be used in conjunction with MPQP to achieve a large decrease in both the online computation and data storage requirements with negligible deterioration of performance. Extensive simulation results are given to back this claim and contrast the TWO proposed interpolation schemes.     

提高SoC设计效率的基于组件方法综述

片上系统本身的异构性和并发性导致了对系统进行统一建模的困难,从而阻碍了设计效率的提高.对现有系统级方法的分析表明:这类方法不能对不同设计之间更加细节的共同特性进行抽象,限制了复用的范围,不能带来设计效率的进一步提高.因此,通过对面向对象设计、软件工程、形式化语义和系统级EDA这4种基于组件方法描述模型及其对复用影响的讨论,确定了系统的刻画特征,采用这些特征来描述片上系统将带来设计效率的提高.     

Measurement designs to improve the computational efficiency of linear system state estimators

A design procedure for the measurement process is proposed to decrease the computational burden of state estimation in linear discrete-time systems. System order reduction is involved, which is achieved by a derived transformation, yielding an alternative system and measurement process representation that includes time delays in both the system and the measurement process. Without loss of filter optimality, measurement designs yielding reductions in the computational requirements of the Kalman filter applied to the reduced order system are derived. A computational comparison is included to show that the proposed method, as opposed to the direct application of the Kalman filter, can yield large reductions in the filter computation time.     

Using reduced-processing training to improve decision efficiency among perfectionists

Cognition, Technology & Work - Previous research has demonstrated performance inefficiencies among perfectionists, which may be mitigated via the adoption of ‘good enough’...     

Sunday字符串匹配算法的效率改进

字符串匹配算法一直是网络监测与审计方面的研究热点。介绍了几种经典的字符串匹配算法,提出了一种基于Sunday算法的改进算法RoSunday算法,该算法主要是在匹配开始前通过一个条件判断语句减少了无意义的匹配次数,提高了算法的执行速度。分析了改进后算法的性能,通过实验结果进一步证明了该算法的有效性。     

以正向变异的遗传算法提高求解VRP问题效率

遗传算法求解车辆路径问题时,优秀基因片段易被破坏,导致算法效率不高等问题,因此遗传算法在解决车辆路径问题时有一定的局限性。通过对该问题的深入分析,提出基于正向变异的遗传算法。控制变异的方向,尽量避免破坏优秀基因的同时大量破坏较差基因,得到更多较优的新基因片段。实验结果表明,该算法有效提高了遗传算法解决车辆路径问题的效率。     

提高支持QoS的Web服务选择效率的新方法

针对当前因网络上Web服务数量的剧增而导致的服务选择效率不高的问题,提出了一种提高支持QoS的Web服务选择效率的新方法.利用巴莱多定律对已有的Web服务发现模型进行了改进,提出了新的交互时序和Web服务选择步骤,有效避免了Web服务选择的重复计算问题,提高了Web服务的选择效率.实验结果表明,该方法可以对大部分Web服务快速选择,有效地提高了Web服务的选择效率.     

A method to improve computational efficiency for CSSO and BLISS

A considerable portion of the computational cost results from the solution of sensitivity information in concurrent subspace optimization and bi-level integrated system synthesis. A novel method to update sensitivity information is suggested to improve the computational efficiency in this brief note. Firstly, both the approximate insensitive terms and approximate linear terms in sensitivity information are identified, and then their values are temporarily kept constant for multiple multidisciplinary design optimization cycles. A practical engineering case study is presented to demonstrate the effectiveness of the proposed method.     

By-pass valve control to improve energy efficiency of pneumatic drive system

In order to improve the performance and energy efficiency of the pneumatic drive, the by-pass valve control scheme is designed and studied. For pneumatic positioning application, in the constant speed phase, the inlet and outlet chambers will be connected via by-pass valve to reduce the overshoot and allow some exhaust compressed air to be reused. Therefore, compared with the traditional control of the motion of the asymmetric cylinder, a 12–28% saving in energy use can be acquired and meanwhile the position accuracy is maintained. Preliminary results from the simulation and experiment studies will be reported.     

An instructional strategy planning model to improve learning and cognition

Developments in cognitive science (e.g., psychology, artificial intelligence, and expert systems) provide a framework to propose an instructional strategy planning model that links knowledge acquisition and employment with specific instructional strategies. The model presented in this article identifies unique computer-based instructional strategies to improve both learning and cognition. Using a meta-learning theory, the storage memory system components of declarative, procedural, and conceptual knowledge are respectively linked to drill and practice, tutorial, and task-oriented simulation strategies. Likewise, for the retrieval memory system components (i.e., differentiation, integration, and creation), the instructional strategies include problem-oriented simulations and self-directed experiences. Each of the instructional strategies are composed of variables and conditions that have been empirically tested and shown to improve specific forms of knowledge acquisition and employment.     

Hierarchical data replication strategy to improve performance in cloud computing

Cloud computing environment is getting more interesting as a new trend of data management. Data replication has been widely applied to improve data access in distributed systems such as Grid and Cloud. However, due to the finite storage capacity of each site, copies that are useful for future jobs can be wastefully deleted and replaced with less valuable ones. Therefore, it is considerable to have appropriate replication strategy that can dynamically store the replicas while satisfying quality of service (QoS) requirements and storage capacity constraints. In this paper, we present a dynamic replication algorithm, named hierarchical data replication strategy (HDRS). HDRS consists of the replica creation that can adaptively increase replicas based on exponential growth or decay rate, the replica placement according to the access load and labeling technique, and finally the replica replacement based on the value of file in the future. We evaluate different dynamic data replication methods using CloudSim simulation. Experiments demonstrate that HDRS can reduce response time and bandwidth usage compared with other algorithms. It means that the HDRS can determine a popular file and replicates it to the best site. This method avoids useless replications and decreases access latency by balancing the load of sites.