Preventive replacement policies with time of operations,mission durations,minimal repairs and maintenance triggering approaches

When a mission arrives at a random time and lasts for a duration, it becomes an interesting problem to plan replacement policies according to the health condition and repair history of the operating unit, as the reliability is required at mission time and no replacement can be done preventively during the mission duration. From this viewpoint, this paper proposes that effective replacement policies should be collaborative ones gathering data from time of operations, mission durations, minimal repairs and maintenance triggering approaches. We firstly discuss replacement policies with time of operations and random arrival times of mission durations, model the policies and find optimum replacement times and mission durations to minimize the expected replacement cost rates analytically. Secondly, replacement policies with minimal repairs and mission durations are discussed in a similar analytical way. Furthermore, the maintenance triggering approaches, i.e., replacement first and last, are also considered into respective replacement policies. Numerical examples are illustrated when the arrival time of the mission has a gamma distribution and the failure time of the unit has a Weibull distribution. In addition, simple case illustrations of maintaining the production system in glass factories are given based on the assumed data.     

Reward optimization of a repairable system

This paper analyzes a system subject to repairable and non-repairable failures. Non-repairable failures lead to replacement of the system. Repairable failures, first lead to repair but they lead to replacement after a fixed number of repairs. Operating and repair times follow phase type distributions (PH-distributions) and the pattern of the operating times is modelled by a geometric process. In this context, the problem is to find the optimal number of repairs, which maximizes the long-run average reward per unit time. To this end, the optimal number is determined and it is obtained by efficient numerical procedures.     

一种面向固态硬盘的Cache置换算法

固体硬盘的出现改变了现有存储子系统的框架,也逐渐成为了嵌入式应用的主流存储设备.但是其自身的写机制由于需要先擦后写,成为了影响SSD性能的瓶颈.针对此问题,出于减少写操作次数这一思路提出了LRU-AB算法,力图在基于Cache数据的访问频度上改进SSD置换算法.同时对现有算法进行了分析.     

Web proxy cache replacement scheme based on back-propagation neural network

Web proxy caches are used to reduce the strain of contemporary web traffic on web servers and network bandwidth providers. In this research, a novel approach to web proxy cache replacement which utilizes neural networks for replacement decisions is developed and analyzed. Neural networks are trained to classify cacheable objects from real world data sets using information known to be important in web proxy caching, such as frequency and recency. Correct classification ratios between 0.85 and 0.88 are obtained both for data used for training and data not used for training. Our approach is compared with Least Recently Used (LRU), Least Frequently Used (LFU) and the optimal case which always rates an object with the number of future requests. Performance is evaluated in simulation for various neural network structures and cache conditions. The final neural networks achieve hit rates that are 86.60% of the optimal in the worst case and 100% of the optimal in the best case. Byte-hit rates are 93.36% of the optimal in the worst case and 99.92% of the optimal in the best case. We examine the input-to-output mappings of individual neural networks and analyze the resulting caching strategy with respect to specific cache conditions.     

Performance evaluation of Web proxy cache replacement policies

The continued growth of the World-Wide Web and the emergence of new end-user technologies such as cable modems necessitate the use of proxy caches to reduce latency, network traffic and Web server loads. In this paper we analyze the importance of different Web proxy workload characteristics in making good cache replacement decisions. We evaluate workload characteristics such as object size, recency of reference, frequency of reference, and turnover in the active set of objects. Trace-driven simulation is used to evaluate the effectiveness of various replacement policies for Web proxy caches. The extended duration of the trace (117 million requests collected over 5 months) allows long term side effects of replacement policies to be identified and quantified.

Our results indicate that higher cache hit rates are achieved using size-based replacement policies. These policies store a large number of small objects in the cache, thus increasing the probability of an object being in the cache when requested. To achieve higher byte hit rates a few larger files must be retained in the cache. We found frequency-based policies to work best for this metric, as they keep the most popular files, regardless of size, in the cache. With either approach it is important that inactive objects be removed from the cache to prevent performance degradation due to pollution.     

A study of replacement rules for a parallel fleet replacement problem based on user preference utilization pattern and alternative fuel considerations

Parallel fleet replacement problems deal with determining an optimal replacement schedule that results in a minimal total cost of owning and operating a fleet within a finite planning horizon. In this paper, the fleet consists of service vehicles, varying in age and cumulative mileage, commonly owned by government agencies or private business organizations. The paper focuses on three main aspects of the problem, including the effects of some widely used replacement rules, consideration of alternative fuel vehicles for replacement, and a new “user preference” utilization pattern. The vehicle replacement rules under study include purchase-new-vehicles-only, no-splitting-in-selling, one-purchase-choice, older-vehicles-selling, and all-or-none rules. The initial fleet consists of gasoline vehicles, while alternative-fuel vehicles using either compressed natural gas (CNG) or liquefied petroleum gas (LPG) are included as challengers in every replacement decision period. The user preference utilization pattern denotes a pattern in which yearly usage of vehicles declines as the vehicles grow older or have higher cumulative mileage. Integer programming formulation of the defined problem that incorporates these new factors is provided. Small numerical examples under various scenarios and a large problem instance with model parameters estimated from actual data are solved to optimality to gain some insights about the replacement rules and other considered factors.     

Deletion, replacement and mean-shift for diagnostics in linear mixed models

Deletion, replacement and mean-shift model are three approaches frequently used to detect influential observations and outliers. For general linear model with known covariance matrix, it is known that these three approaches lead to the same update formulae for the estimates of the regression coefficients. However if the covariance matrix is indexed by some unknown parameters which also need to be estimated, the situation is unclear. In this paper, we show under a common subclass of linear mixed models that the three approaches are no longer equivalent. For maximum likelihood estimation, replacement is equivalent to mean-shift model but both are not equivalent to case deletion. For restricted maximum likelihood estimation, mean-shift model is equivalent to case deletion but both are not equivalent to replacement. We also demonstrate with real data that misuse of replacement and mean-shift model in place of case deletion can lead to incorrect results.     

位置相关信息服务移动终端缓存替换研究

随着无线网络的快速发展,相应的无线应用服务越来越多,位置相关信息服务(LDISs)就是其中典型的例子。无线网络受信道带宽以及终端计算能力等因素的限制,缓存技术减少了网络开销并且支持在网络断接下使用数据的优点而成为研究热点。本文根据无线应用环境的特点,结合位置相关信息数据的特征,运用粗糙集(RoughSet,RS)这一强有力的数学工具,给出一种更加准确、实用的移动缓存替换策略。     

复合地基综合处理的原理探讨

探讨了深层搅拌或粉喷桩与砂石或石灰桩共同处理软弱土地基的技术，给出了综合处理的计算表达式和实际算例．在实用中，可起到提高承载力和抗液化能力以及应用灵活的作用