Proposed Replacement Policy Research Articles

Optimal age replacement time for coherent systems under Geometric Point Process

In spatial context, the understanding of event dynamics and point distributions is a fundamental requirement. This study addresses a critical need by introducing the Geometric Point Process (GPP) and explaining its potential impact on optimizing the determination of optimal replacement ages for coherent systems. Our paper has three overarching aims: firstly, to bridge the gap by presenting the novel GPP model that effectively captures the geometric distribution of points, filling a void in point process theory. Secondly, we calculate the optimal replacement age for the coherent system based on the principles of GPP. This involves employing the Infinitesimal-Look Ahead stopping rule within the framework of Smooth Semi-Martingale (SSM) decomposition. A comprehensive comparative analysis is conducted to assess the distinct features and advantages of the GPP in relation to other point processes, offering valuable insights into its applicability and performance. Lastly, we extend the practical application of GPP by examining optimal replacement strategies for components in coherent systems, offering a bridge between theory and real-world practices, especially in the context of aircraft and wind turbine component deterioration. Additionally, we conduct reliability and sensitivity analyses, providing management suggestions, and present Monte Carlo simulations as an alternative method for validating optimal solutions. This research invites the industrial community to utilize the proposed replacement policy, paving the way for exploring geometric characteristics in stochastic processes. The timeliness and significance of this work are underscored by the relatively unexplored field of smooth semi-martingales, with the most recent publication dating back to 2015 by Bueno.

Adaptive LRFU replacement policy for named data network in industrial IoT

In this paper, an adaptive least recently frequently used (LRFU) replacement policy is proposed for named data network (NDN) in the industrial internet of things (IIoT) environment. Low-latency network communication has become the main focus in IIoT development. By applying NDN architecture with the proposed replacement policy, the system can minimize the network latency of IIoT due to the NDN router’s capabilities to cache content. The simulation result shows that the proposed adaptive LRFU outperforms other popular replacement policies based on various network performances metrics. In addition, future research trends regarding the testbed implementation NDN replacement policy are suggested.

Maintenance policies with minimal repair and replacement on failures: analysis and comparison

The main objective of a maintenance policy consists of conducting maintenance actions at lower costs. This paper proposes an approach for comparing numerically three maintenance strategies, involving minimal repairs at failure, replacement with complete renewal only at the first failure, and replacement with complete renewal at each failure. These strategies are integrated into a modified block replacement policy that includes corrective and preventive maintenances. The approach proceeds by presenting the mathematical models at the component level and at the system level. As the renewal function for generalised Weibull distributions is impossible to obtain, a novel asymptotic algorithm is introduced for estimating the replacements number. However, a multi-component industrial example is proposed for selecting the strategy that minimises the maintenance costs. A sensitivity analysis is performed for comparing an opportunistic maintenance policy with the proposed replacement policy to check if substantial cost reduction still possible. The experiment results show clearly that the third strategy is the most efficient and reduces maintenance costs to a very low level. Finally, we think that the developed study provides a flexible and less costly solution to deal with maintenance decision-making for systems that do not have modern technological equipment to collect data from system breakdowns.

A novel replacement policy for a linear deteriorating system using stochastic process with dependent components

AbstractIn this study, a mechanical system with linear deterioration and preventive maintenance is considered. The state of the system over time is represented by a semicontinuous stochastic process with dependent components. The system cycles through on and off periods during its lifetime. The state of the system deteriorates linearly as a function of the usage time during on periods. When the system is offline, preventive maintenance is conducted, which improves the system state by a random amount. The system's on and off times and random improvement amounts are assumed to have general distributions. For such a system, our objective is to determine the expected value and variance for the number of preventive maintenance activities needed during the system lifetime and to propose a novel replacement policy for the system based on delay‐time modeling. Finally, the effectiveness of the obtained asymptotic results and the proposed replacement policy are tested through simulation.

Optimal overhaul\u2013replacement policy for a multi-degraded repairable system sold with warranty

In this research, we study an optimal overhaul–replacement policy of a multi-degraded repairable system sold with a free replacement warranty. In the proposed replacement policy, a maintenance action and failure are dependent on a system degradation level and the system age, and hence the replacement model will provide more effective maintenance decisions. Failure of the system is modeled using a rate of occurrence of failure for the system, which is as a function of a degradation level of the system and its age. We develop the optimal replacement policy for a multi-degraded repairable system from the buyer’s point of view, who plans to use the system for a horizon planning T. The buyer conducts a periodic evaluation and selects an appropriate maintenance option based on the revealed system condition together with the system operational age. At each evaluation point, three alternative decisions are available, i.e., keep running the system, overhaul, or replace it with a new one. We formulate the sequential decision (keep, overhaul, or replace) problem as a dynamic programming model and obtain an optimal policy that minimizes total cost over T. Numerical examples are presented using several hypothetical data sets to illustrate the structure of optimal solution and its sensitivity against the change in parameter values. The main contribution of the paper is to offer a decision tool that will help in deciding the overhaul–replacement action based on the degradation level and the operational age of the system.

A Modified Replacement Model for Items That Fail Suddenly with Variable Replacement Costs

Several researches have been done to provide better alternative to the existing replacement models, but the research works did not adequately address the replacement problem for items that fail suddenly. Hence, a modified replacement model for items that fail suddenly has been proposed using the knowledge of probability distribution of failure times as well as that of variable replacement cost. The modified cost functions for implementing both individual and group replacements were derived. The modified cost functions were minimized using the principle of classical optimization in order to find the age at which replacement of items would be appropriate. Conditions under which the individual and group replacement policies should be adopted were derived. Two real data sets on failure time of LED bulbs and their replacement costs were used to validate the theoretical claims of this work. In essence, goodness-of-fit test was used to select appropriate probability distribution of failure times as well as that of replacement costs for data sets I and II respectively. The goodness-of-fit results showed that failure times of LED bulbs follow the Smallest Extreme Value and Laplace distributions for data sets I and II respectively. Similarly, it was observed that individual replacement cost followed the two-parameter Gamma and Largest Extreme Value distributions for data sets I and II respectively. Further, the group replacement cost was found to follow the log-normal and two-parameter Weibull distributions for data sets I and II respectively. Based on the empirical study, we observed that individual replacement policy is better than group replacement policy in terms of cost minimization for both existing model and the proposed model. In view of the results, the proposed replacement policy was recommended over the existing one because it yielded lower replacement costs than the existing replacement model.

An exclusive cache replacement policy based on read priority and dynamic sliding

The conventional cache replacement algorithms have massive hardware cost with ambiguous logic and measurability. Increasing the cache levels do not give a better solution for the hardware complexity and performance issues in multi-core processors. Rather number of read misses on executing the complex memory intensive program can increase the execution time in multi-core processors. This paper proposes a new way of cache replacement policy weight-based read priority replacement (WRPR), which works on the read priority of a cache line in all levels of cache. By making it read prior instead of write, the cache lines with more read access are highly weighted. During replacement, the cache eviction is done from dynamic logical cache regions based on its weight. The algorithm performance is tested using multi-core cache simulator with different benchmark workloads in the SMPCache simulator. The proposed replacement policy can work on any exclusive cache level in a multi-level hierarchy. It shows an improved performance from the hit rate context.

Optimal Replacement of Heterogeneous Items With Minimal Repairs

In this paper, a new replacement policy for a deteriorating item from a mixed population is suggested. The item is randomly selected from a mixed population composed of two stochastically ordered subpopulations and the corresponding subpopulation from which the item is selected is unknown. As the operational history contains the information about the subpopulation from which the item is selected, it is reasonable to employ this information in determining the replacement policy. In the new replacement policy, the age at which the item will be replaced is not determined before the operation of the item, but it is determined based on the failure/repair history of the item observed during the initial operation. It is shown that the proposed replacement policy outperforms the ordinary periodic replacement policy. The properties of the optimal replacement policy will be studied in detail.

Age replacement policies for two-component systems with stochastic dependence

Purpose – The purpose of this paper is to investigate age replacement policies for two-component parallel system with stochastic dependence. The stochastic dependence considered, is modeled by a one-sided domino effect. The failure of component 1 at instant t may induce the failure of component 2 at instant t+τ with probability p 1→2. The time delay τ is a random variable with known probability density function h p 1→2 (.). The system is considered in a failed state when both components are failed. The proposed replacement policies suggest to replace the system upon failure or at age T whichever occurs first. Design/methodology/approach – In the first policy, costs and durations associated with maintenance activities are supposed to be constant. In the second replacement policy, the preventive replacement cost depends on the system’s state and age. The expected cost per unit of time over an infinite span is derived and numerical examples are presented. Findings – In this paper and especially in the second policy, the authors find that the authors can get a more economical policy if the authors consider that the preventive replacement cost is not constant but depends on T. Originality/value – In this paper, the authors take into account of the stochastic dependence between system components. This dependence affects the global reliability of the system and replacement’s periodicity. It can be used to measure the performance of the system et introduced into design phase of the system.

Improving Performance in Sub-Block Caches with Optimized Replacement Policies

Recent advances in computer processor design have led to the introduction of sub-blocking to cache architectures. Sub-block caches reduce the tag area and power overhead in caches without reducing the effective cache size by using fewer tags to index the full data RAM array. In spite of achieving reduced area and power overhead, sub-block caches suffer performance degradation due to cache trashing. This occurs when a wider cache line (super-block), made up of multiple valid cache lines (sub-blocks), is replaced or evicted when only a sub-block is to be allocated into the wider super-block. To address this problem, we propose cache replacement policies as they relate specifically to sub-block caches. We propose new replacement policies that are tuned for sub-block caches by adding more intelligence based on the valid state of individual sub-blocks of a super-block. We also investigate the effect of using a few level-0 registers to bypass a few level-1 cache pipe stages on sub-block cache performance. To evaluate the performance improvement offered by our proposed replacement policies and the use of level-0 registers, we developed a sub-block cache simulator based on the Simplescalar toolset for single-core evaluations and the Sniper Simulator for multicore evaluations. We show that, with minimal architectural updates to existing conventional cache replacement policies, we are able to improve level-1 cache hit rates by up to 4.17% using our proposed policies alone on SPEC2006 benchmarks and up to 14% in shared level-2 caches using multicore benchmark suites: PARSEC and SPLASH2.

LDF-CLOCK: The Least-Dirty-First CLOCK Replacement Policy for PCM-based Swap Devices

Phase-change memory (PCM) is a promising technology that is anticipated to be used in the memory hierarchy of future computer systems. However, its access time is relatively slower than DRAM and it has limited endurance cycle. Due to this reason, PCM is being considered as a high-speed storage medium (like swap device) or long-latency memory. In this paper, we adopt PCM as a virtual memory swap device and present a new page replacement policy that considers the characteristics of PCM. Specifically, we aim to reduce the write traffic to PCM by considering the dirtiness of pages when making a replacement decision. The proposed replacement policy tracks the dirtiness of a page at the granularity of a sub-page and replaces the least dirty page among pages not recently used. Experimental results with various workloads show that the proposed policy reduces the amount of data written to PCM by 22.9% on average and up to 73.7% compared to CLOCK. It also extends the lifespan of PCM by 49.0% and reduces the energy consumption of PCM by 3.0% on average.

Cooperative Cache Replacement Policy for MANETs

Mobile Adhoc Networks (MANETs) are autonomously structured multi-hop wireless links in peer to peer fashion without aid of any infrastructure network. In MANETs network topology is dynamic, as nodes are mobile. Due to this dynamic topology and multi-hop environment data availability in MANETs is low. Caching of frequently accessed data in ad hoc networks is a potential technique that can improve the data access, performance and availability. While caching the new data items, it is very important which data item is to be removed, as in MANETs the data is not stored only on behalf of caching node but interest of the vicinity is also considered. In this paper the authors presented a new cache replacement policy for MANETs. This policy is based on multi-parameter value called SAT. We simulate the proposed work on OMNET++ and the simulation results shows that proposed replacement policy helps to improve the data availability in network.

A future location‐aware replacement policy for the cache management at the mobile terminal

AbstractWhile the traditional data shipping systems use physical information to organize data, a newer data caching technique maintains both associated answers (data items) of previous queries and their meaning (purpose). This form of information description is called semantic description, and it makes it possible to reason about and derive knowledge from the given description. In a distributed heterogeneous environment, such as the mobile environment, the semantic data caching paradigm is an important technique for improving the performance of wireless data dissemination systems. Data caching performance depends heavily on the replacement policy being used for the cache management. However, future location uncertainty, limited client resources and frequent client disconnections make cache management a challenge.This paper proposes a future location‐aware cache replacement policy to manage a semantic cache. The proposed replacement policy uses the validity of the data fetched from the server and the neighboring locations to decide which of the cache entries is less likely to be needed in the future, and therefore a good victim for eviction when cache space is needed. The replacement policy's preference for cached items to be evicted is modeled as a general function that declines with distance between the mobile user's current location and the candidate for replacement cached item's bound location. For better efficiency, the overall replacement granularity is dynamically achieved along three levels: ring, cell and data item. Simulation study of the proposed approach shows that it outperforms both the least recently used (LRU) and furthest away replacement (FAR) schemes, where only temporal locality is considered. Moreover, the proposed scheme is easier to implement than other research and development proposals. Copyright © 2008 John Wiley & Sons, Ltd.

Maintenance optimization for subsea oil pipelines

In this paper, the classical PF interval model, proposed for reliability centered maintenance, is used to optimize the preventive replacement policy of a subsea oil pipeline. The pipeline is subject to failure modes that may lead to oil release and pollution of the sea. The proposed replacement policy is based on regular condition measurements of the quality of an internal pipeline coating (lining). Holes in the coating will expose the pipe material (steel) to a corrosive environment. It is, therefore, important to identify holes in the coating and take action before the corrosion penetrates the pipe wall. The model proposed in the paper can be used to determine the inspection interval that minimizes the average maintenance cost per time unit. The model formulation is outlined and illustrative examples are solved. The mathematical evaluation of the replacement policy requires numerous assumptions. These assumptions have to be tailored to the specific application. The assumptions and the data provided are included for illustrative purposes to exemplify potential results that may be obtained by using the replacement policy.

A new cache document replacement policy considering the contribution to sales

Most traditional cache document replacement policies are focused on the efficiency aspect and these documents are replaced according to their last access times, request frequencies, and sizes. However, in addition to providing efficient document acquisition service, a successful commercial website also has to create incentives for customers, so as to gain sufficient revenues to support the continuing operation of the website. For this reason, a new cache document replacement policy considering the contribution-to-sales of every document is proposed in this study. In order to evaluate the contribution-to-sales of a document, two web mining techniques are applied. Then the traditional GDSF policy is modified to incorporate this new factor. To evaluate the effectiveness of the proposed methodology, an experimental EC website has been constructed, and a series of computer programs have been developed to simulate the accesses by various kinds of users to the website and to obtain some data for rudimentary analyses. The results showed that the proposed replacement policy could at most increase the hit rate and the byte hit rate by 16% and 9%, respectively, for customers compared with traditional replacement policies.

이동환경에서 연속미디어 서비스를 위한 협력적인 프록시 캐슁

본 연구는 이동환경에서 연속 미디어 객체에 대한 사용자 요구들에 대하여 효율적으로 자원을 관리하기 위하여, 사용자의 이동성 정보를 반영하는 협력적 프록시 캐슁 정책을 제안한다. 제안된 정책은 담당영역 내에서 사용자의 요구들을 참조함으로서 캐슁하는 기존의 프록시 캐슁정책과는 다르게 인접한 영역의 많은 사용자 요구 정보들을 이용하여 캐슁 객체를 선택함으로써 이동환경에서 발생하는 사용자들의 랜덤 액세스 요구들을 충분히 반영할 수 있도록 한다. 그리고 제안된 캐슁 정책을 위해서 각 프록시에서 발생한 요구 정보의 가중치와 재생량을 기반으로 하는 재배치 기법을 제안한다. 그래서 객체단위와 세그먼트 단위로 재배치 기법을 수행하여 결과를 평가하고 캐슁 정책의 성능을 분석하였다. 그 결과, 이동환경에서 적절한 사용자의 이동성 비율이 협력적 캐슁의 성능에 영향을 미치는 중요한 요인이 된다는 것을 알았다. This paper proposes a user's mobility based cooperative proxy caching policy for effective resource management of continuous media objects in mobile environments. This policy is different from the existing proxy caching policies in terms of how to exploit users' mobility. In other words, existing caching policies work based on the information about objects by referring to user's requests within a specified domain whereas the proposed caching policy runs by utilizing a number of user's requests across several domains. So, the proposed policy is applicable to random requests in mobile environments Moreover, we also propose a replacement policy based on weights and playback time. To check the efficiency of the proposed caching policy, the proposed replacement policy is run with different size of caching unit object or segment. The result of performance analyze tells what a ratio of user's mobility is are major factors for the efficient operation of the cooperative caching.

An Extended Opportunity-Based Age Replacement Policy

The present study proposes an extended opportunity-based age replacement policy where opportunities occur according to a Poisson process. When the age, x of the system satisfies x for a prespecified value S , a corrective replacement is conducted if the objective system fails. In case x satisfies S ≤ x for another prespecified value T , we take an opportunity to preventively replace the system by a new one with probability p , and do not take the opportunity with probability 1 - p . At the moment x reaches T , a preventive replacement is executed independently of opportunities. The long-term average cost of the proposed policy is formulated. The conditions under which optimal values for S and T exist for a prespecified value of T and S , respectively, are then clarified. Numerical examples are also presented to illustrate the theoretical underpinnings of the proposed replacement policy formulation.