Replacement Policy Research Articles

A generalized age-dependent minimal repair with random working times

Two extended preventive replacement models for systems that execute projects at random times are discussed in this paper. The system is subject to shocks at which the system experiences one of two kinds of failures whose probabilities depend on age. A type I failure will cause a minor failure of the system and is fixed by a minimal repair. A type II failure will lead to a catastrophic failure of the system, and a corrective replacement is required at such failure. First, we investigate a preventive replacement policy where the system is replaced at the m-th type I failure, or at the time instant when the n-th working project is completed, or at age τ, or at the first type II failure, whichever occurs first. In addition, we also investigate another preventive replacement model where the system is replaced preventively at the time instant when the n-th working project is completed, or at the m-th type I failure, or at age τ, whichever occurs last, and is replaced correctively at the first type II failure. We formulate the long-run expected cost rate for each replacement policy, and determine analytically the optimum preventive replacement policy. We also show that several previous replacement models in the literature are special cases of our models. Finally, a procedure for finding the optimum preventive replacement schedule is presented and some numerical examples are given illustrating the present policies.

Simplified swarm optimization for bi-objection active reliability redundancy allocation problems

The reliability redundancy allocation problem (RRAP) is a well-known tool in system design, development, and management. The RRAP is always modeled as a nonlinear mixed-integer non-deterministic polynomial-time hardness (NP-hard) problem. To maximize the system reliability, the integer (component active redundancy level) and real variables (component reliability) must be determined to ensure that the cost limit and some nonlinear constraints are satisfied. In this study, a bi-objective RRAP is formulated by changing the cost constraint as a new goal, because it is necessary to balance the reliability and cost impact for the entire system in practical applications. To solve the proposed problem, a new simplified swarm optimization (SSO) with a penalty function, a real one-type solution structure, a number-based self-adaptive new update mechanism, a constrained nondominated-solution selection, and a new pBest replacement policy is developed in terms of these structures selected from full-factorial design to find the Pareto solutions efficiently and effectively. The proposed SSO outperforms several metaheuristic state-of-the-art algorithms, e.g., nondominated sorting genetic algorithm II (NSGA-II) and multi-objective particle swarm optimization (MOPSO), according to experimental results for four benchmark problems involving the bi-objective active RRAP.

Reliability and maintenance of systems subject to Gamma degradation and shocks in dynamic environments

Many systems or devices may experience degradation and shocks simultaneously whose behaviors may have discrepancies in different system operating environments. In this paper, a reliability model is developed for systems subject to both sudden shocks and natural wear processes in randomly evolving environments. The natural wear behavior of the system under different environment is governed by a distinct Gamma process. The system fails when the overall degradation which contains the natural wear and the cumulative damage caused by previous arrival shocks hits a preset threshold. To calculate the cumulative distribution function of the first passage time, the explicit computation formula based on analytical methods and the simulation algorithm based on Monte Carlo simulation methods are provided, which could verify each other. Further, a corrective replacement policy is considered in the case where the environment switching process takes place only when the system is functioning, and then the formula for the system availability is analytically derived. Finally, a study case of the lithium-ion battery is given to illustrate the proposed model and obtained results.

Revisiting discrete time age replacement policy for phase-type lifetime distributions

For a system (or unit) whose lifetime is measured by the number cycles, according to the discrete time age replacement policy, it is replaced preventively after n cycles or correctively at failure, whichever occurs first. In this paper, discrete time age replacement policy is revisited when the lifetime of the system is modeled by a discrete phase-type distribution. In particular, the necessary conditions for the unique and finite replacement cycle which minimizes the expected cost per unit of time are obtained. The necessary conditions are mainly based on the behavior of the hazard rate. The results are illustrated for some special discrete phase-type lifetime distributions. Computational results are also presented for the optimal replacement cycle under specific real life setups.

On the reliability and optimal maintenance of systems under a generalized mixed δ-shock model

This article is a study on the reliability characteristics of a system under a failure model called the generalized mixed [Formula: see text]-shock model. We assume that the system is subject to shocks according to a stochastic process. Each shock may cause some damage to the system. The system fails either the magnitude of the damage caused by a shock exceeds a threshold [Formula: see text] or the time between two consecutive shocks is less than a pre-specified threshold [Formula: see text] and simultaneously magnitude of the damage is bigger than a pre-specified critical threshold [Formula: see text] ([Formula: see text]). The survival function and other characteristics of the system lifetime are investigated. By imposing a cost function, we arrive at an optimal replacement policy for the system based on the proposed failure model. Several examples are provided under which we illustrate the theoretical results numerically and graphically.

Contextual dimensions for cache replacement schemes in information-centric networks: a systematic review.

In recent years, information-centric networks (ICNs) have gained attention from the research and industry communities as an efficient and reliable content distribution network paradigm, especially to address content-centric and bandwidth-needed applications together with the heterogeneous requirements of emergent networks, such as the Internet of Things (IoT), Vehicular Ad-hoc NETwork (VANET) and Mobile Edge Computing (MEC). In-network caching is an essential part of ICN architecture design, and the performance of the overall network relies on caching policy efficiency. Therefore, a large number of cache replacement strategies have been proposed to suit the needs of different networks. The literature extensively presents studies on the performance of the replacement schemes in different contexts. The evaluations may present different variations of context characteristics leading to different impacts on the performance of the policies or different results of most suitable policies. Conversely, there is a lack of research efforts to understand how the context characteristics influence policy performance. In this direction, we conducted an extensive study of the ICN literature through a Systematic Literature Review (SLR) process to map reported evidence of different aspects of context regarding the cache replacement schemes. Our main findings contribute to the understanding of what is a context from the perspective of cache replacement policies and the context characteristics that influence cache behavior. We also provide a helpful classification of policies based on context dimensions used to determine the relevance of contents. Further, we contribute with a set of cache-enabled networks and their respective context characteristics that enhance the cache eviction process.

Energy-oriented joint optimization of machine maintenance and tool replacement in sustainable manufacturing

With the increasing attention on sustainable manufacturing, operation and maintenance (O&M) management focuses on not only budget limit, but also energy saving. For modern CNC systems, besides the energy consumption to operate and maintain the machine, a majority of energy consumption generated from tool wear should be considered. It means both machine degradation and tool wear are required to be modelled for the global saving energy. Thus, this paper proposes an energy-oriented joint optimization of machine maintenance and tool replacement (EJMR) policy by integrating energy consumption mechanisms and joint maintenance opportunities in a machine-tool system. The key issue is to combine the preventive maintenance (PM) scheduling of the machine and the polish/preventive replacement (PR) optimization of sequential tools to form energy-effective schemes. Therefore, joint maintenance opportunities of PM actions are utilized to perform tool polish/PR based on energy consumption mechanisms. Four successive procedures (energy consumption analysis, energy-oriented PM scheduling, machine-tool PR model and integrated decision-making process) are developed. Thereby optimal intervals of machine PM and tool polish/PR are obtained to save energy. The case study illustrates that compared with conventional maintenance policies, this proposed EJMR policy can significantly reduce the total non-value-added energy consumption (TNVE) in sustainable manufacturing.

RUE: A caching method for identifying and managing hot data by leveraging resource utilization efficiency

AbstractIn this study, we propose a caching method called RUE for dynamic large‐scale data streams. We define a data model to facilitate hot data identification and management. At the heart of RUE model is hot degree that takes into account two factors data resource utilization efficiency and reuse distance, aiming to quantitatively reflect data popularity in a dynamic data stream. Based on data's hot degree, RUE classifies data into four types, each of which is assigned with an associated cache residence time. Guided by RUE model, we develop HM algorithm to identify and manage hot data in a dynamic data stream. HM algorithm is implemented by four stacks, namely, new stack, short stack, long stack, and temp stack. Moreover, an eviction and a migration algorithms are integrated into HM to facilitate block replacement and migration. To evaluate the performance of HM algorithm, we quantitatively compare the performance of RUE with three state‐of‐art algorithms, namely, LRU, LIRS, and ARC under various replacement policies, operations, and workloads. Experimental results show that RUE outperforms these three existing algorithms in terms of both read and write hit rates. Furthermore, we show that with the four stacks in place, the computing overhead of HM is negligible.

Hybrid Cache Management in Ad Hoc Networks

With the consistent growing maneuver and applications of mobile technologies, dynamic handling of queries related to information on electronic media (Broadcast Queries) plays a vital role. Broadcast Queries (BQs) consists of some authentic characteristics that are not addressed when compared to conventional spatial query processing. It is possible to achieve a considerable reduction in latency while maintaining the highest accuracy and scalability related to queries related to peer-to-peer allocation and thereby allows finishing queries with no interruption at a mobile congregation. In this paper, we propose a hybrid cache management algorithm in order to proficiently encourage accessing of data in ad hoc networks. The verification algorithm gathers the neighboring peer data items to provide the spatial query solutions. The network utilization in the network is related with the available bandwidth and the free space through efficient cache management. The hybrid cache management is combined with $$Cach{e}_{Data}$$ and $$Cach{e}_{Path}$$ techniques utilizing the concept of cache replacement policies with the motivation to further improve the performance of BQs. The experimental results indicate that the proposed scheme works well in reduction of query delay and also message complexity than the related techniques.

Truncated Inverted Kumaraswamy: Estimation andPredication Based on Maximum Likelihood Method

Truncation arises in many situations when failure of a unit is observed only if it fails before and/or after a certain period; since any unit, either industrial or biological cannot operate in the same condition forever. A random variable is said to be truncated if it is observed over part of its range where it can occur in various situations. For instance, in survival analysis, failures during the warranty period may not be counted. Items may also be replaced after certain time following the replacement policy, so that failures of the item are ignored.

The COVID-19 exams fiasco across the UK: four nations and two windows of opportunity

All four UK and devolved governments performed a ‘U-turn’ on their COVID-19 school exams replacement policies. After cancelling exams, they sought teacher estimates on their grades, but supported an algorithm to standardise the results. When the results produced a public outcry over unfair consequences, they initially defended their decision but reverted quickly to teacher assessment. We explain these developments by comparing two ‘windows of opportunity’ overseen by four separate governments, in which the definition of the problem, feasibility of each solution, and motive of policymakers to select one over the other lurched dramatically within a week of the exams results. These experiences highlight the confluence of events and choices and the timing and order of choice. A policy solution that had been rejected during the first window, and would have been criticised heavily if chosen first, became a lifeline during the second. As such, while it is important to understand why the standardisation process went so wrong, we focus on why the policymaking process went so wrong.

Performance-oriented risk evaluation and maintenance for multi-asset systems: A Bayesian perspective

In this article, we present a risk evaluation and maintenance strategy optimization approach for systems with parallel identical assets subject to continuous deterioration. System performance is defined by the number of functional assets, and the penalty cost is measured by the loss of performance. To overcome the practical challenges of information sparsity, we employ a Bayesian framework to dynamically update unknown parameters in a Wiener degradation model. Order statistics are utilized to describe the failure times of assets and the stepwise incurred performance penalty cost. Furthermore, based on the Bayesian parameter inferences, we propose a short-term value-based replacement policy to minimize the expected cost rate in the current planning horizon. The proposed strategy simultaneously considers the variability of parameter estimators and the inherent uncertainty of the stochastic degradation processes. A simulation study and a realistic example from the petrochemical industry are presented to demonstrate the proposed framework.

Leaking Information Through Cache LRU States in Commercial Processors and Secure Caches

The Least-Recently Used (LRU) cache replacement policy and its variants are widely deployed in modern processors. This article shows in detail that the LRU states of caches can be used to leak information: any access to a cache by a sender will modify the LRU state, and the receiver is able to observe this through a timing measurement. This article presents LRU timing-based channels both when the sender and the receiver have access to shared memory, e.g., shared library, and when they are separate processes without shared memory. In addition, the new LRU timing-based channels are demonstrated on both Intel and AMD processors in scenarios where the sender and the receiver are sharing the cache in both hyper-threaded setting and time-sliced setting. The transmission rates of the LRU channels can be up to 600 Kbps per cache set in the hyper-threaded setting. Different from the majority of existing cache channels which require the sender to trigger cache misses, the new LRU channels work with the sender only having cache hits, making the channel faster and stealthier. This article further discusses the effectiveness of the new LRU channels against a number of secure cache designs. Especially, the LRU channels are demonstrated to work against two representative secure caches, Partition-Locked (PL) cache and Random Fill (RF) cache, in the gem5 simulator, showing possible vulnerabilities in the secure cache designs in which the security of the replacement state is not protected properly.

A Literature Review on Caching Transient Contents in Vehicular Named Data Networking

Vehicular Named Data Networking (VNDN) is a revolutionary information-centric architecture specifically conceived for vehicular networks and characterized by name-based forwarding and in-network caching. So far, a variety of caching schemes have been proposed for VNDN that work in presence of static Data packets, like traditional Internet contents. However, with the advent of Internet of Things (IoT) and Internet of Vehicles (IoV) applications, large sets of vehicular contents are expected to be transient, i.e., they are characterized by a limited lifetime and become invalid after the latter expires. This is the case of information related to road traffic or parking lot availability, which can change after a few minutes—or even after a few seconds—it has been generated at the source. The transiency of contents may highly influence the network performance, including the gain of in-network caching. Therefore, in this paper, we consider the dissemination of transient contents in vehicular networks and its effects on VNDN caching. By providing a detailed review of related work, we identify the main challenges and objectives when caching transient contents, e.g., to avoid cache inconsistency, to minimize the Age of Information (AoI) and the retrieval latency, and the main strategies to fulfill them. We scan the existing caching and replacement policies specifically designed for transient contents in VNDN and, finally, we outline interesting research perspectives.

Real-world emissions of construction mobile machines and comparison to a non-road emission model

This study implemented real-world tests in Nanjing, China for measuring emission factors (EFs) of air pollutants, including Carbon Monoxide (CO), Hydrocarbon (HC), Nitrogen Oxides (NOx), and Particulate Matter (PM) from ten construction machines in three operational modes (idling, moving, and working) with a Portable Emission Measurement System. The idling mode shows the least variation of EFs, and its average CO EFs can be higher than the moving and working modes by 43% and 34%, respectively. The working mode generates the highest emission for all other pollutants with the highest variation. The EFs suggested by the Guide (an official guidebook for developing emission inventory in China) are in general lower than the measured EFs, and the gap becomes larger for older machines. The EFs of CO, NOx, and PM of China Stage II machines are 24%, 120%, and 66% higher than those of the Guide, respectively. The differences go up as high as 126%, 1066%, and 559% for China Stage I machines, indicating the upgrade of engine technology from Stage I to Stage II, as well as the effect of machine deterioration. The result of this study reveals the effectiveness of stringent emission standards in controlling emissions from construction machines. High emissions from older machines emphasize the importance of a more rigorous machine replacement policy and a regulated maintenance strategy. The result also stresses the need to update the Guide with differentiated activity modes, region variations, and machine deterioration effects.

Performance Analysis Methods for List-Based Caches With Non-Uniform Access

List-based caches can offer lower miss rates than single-list caches, but their analysis is challenging due to state space explosion. In this setting, we propose novel methods to analyze performance for a general class of list-based caches with tree structure, non-uniform access to items and lists, and random or first-in first-out replacement policies. Even though the underlying Markov process is shown to admit a product-form solution, this is difficult to exploit for large caches. Thus, we develop novel approximations for cache performance metrics, in particular by means of a singular perturbation method and a refined mean field approximation. We compare the accuracy of these approaches to simulations, finding that our new methods rapidly converge to the equilibrium distribution as the number of items and the cache capacity grow in a fixed ratio. We find that they are much more accurate than fixed point methods similar to prior work, with mean average errors typically below 1.5% even for very small caches. Our models are also generalized to account for synchronous requests, fetch latency, and item sizes, extending the applicability of approximations for list-based caches.

Optimal replacement policy with replacement last under cumulative damage models

−In this study, we discuss a preventive replacement policy under cumulative damage models that include the concept of replacement last. The system is subject to two types of shocks (represented by type 1 shock and type 2 shock) whose probabilities depend on age. Each type 1 shock leads to an amount of additive damage to the system and also causes a minor failure of the system, which can be rectified by a minimal repair. The system will have a catastrophic failure as long as the accumulated damage exceeds a failure level threshold L. Meanwhile, type 2 shock will cause catastrophic failure of the system. The system is replaced preventively at age τ or the n-th type 1 shock or the time instant when the accumulated damage exceeds a pre-specified level k (but less than L), whichever occurs last, and is replaced correctively at the first type 2 shock or the time which the accumulated damage exceeds L, whichever occurs first. The average cost rate is developed and the optimal replacement policy is discussed analytically and computed numerically.

Analysis of two components parallel repairable degenerate system with vacation

<abstract><p>This article studies a parallel repairable degradation system with two similar components and a repairman who can take a single vacation. Suppose that the system consists of two components that cannot be repaired "as good as new" after failures; when the repairman has a single vacation, the fault component of system may not be repaired immediately, namely, if a component fails and the repairman is on vacation, the repair of the component will be delayed, if a component fails and the repairman is on duty, the fault component can be repaired immediately. Under these assumptions, a replacement policy $ N $ based on the failed times of component 1 is studied. The explicit expression of the system average cost rate $ C(N) $ and the optimal replacement policy $ N^{\ast} $ by minimizing the $ C(N) $ are obtained, which means the two components of the system will be replaced at the same time if the failures of component 1 reach $ N^{\ast} $. To show the advantage of a parallel system, a replacement policy $ N $ of the cold standby system consisting of the two similar components is also considered. The numerical results of both systems are given by the numerical analysis. The optimal replacement policy $ N^* $ for both systems are obtained. Finally, the comparison of numerical results shows the advantages of the parallel system.</p></abstract>

CEMP-IR: a novel location aware cache invalidation and replacement policy

Earlier mobile client cache invalidation-replacement policies used in the location-based information system are not appropriate if the path for the client movement is changing rapidly. Further, pre...

DAM: Deadblock Aware Migration Techniques for STT-RAM-Based Hybrid Caches

Last Level Caches (LLCs) play a critical role in reducing the number of costly off-chip memory accesses. Hence, there is a demand to make the LLCs larger to meet the requirements of growing dataset size of emerging data-intensive applications. Non-volatile STT-RAM-based caches with high memory density are a promising alternative to satisfy such a demand. However, STT-RAM-based caches have high write-latency and write energy. Therefore, researchers proposed a unified cache consisting of both SRAM and STT-RAM portions to handle expensive writes in these large hybrid LLCs. However, these large LRU-managed LLCs still remain underutilized due to the presence of a significant fraction of deadblocks (zero-reuse blocks) in them. By choosing the deadblock as an eviction candidate, we show a significant reduction in the LLC misses. Our work considers the entire set of the hybrid cache to select the deadblock as an eviction candidate. Therefore, we propose Deadblock-based Victim Selection (DVS), a deadblock-aware replacement policy. We observe that in up to 40 percent of cases, evicting a deadblock on an LLC miss requires migration of a cache block within the cache set. To incorporate this opportunity into DVS, we augment it with a cache block migration strategy and propose Deadblock-based Migration (DM) policy. The detailed evaluation on the SPEC CPU2006 workloads shows that DVS and DM enhance the performance of the system by up to 13 and 52 percent, respectively. Our results demonstrate that a cache replacement policy that is both deadblock-aware and migration-aware is essential in improving the performance of large hybrid LLCs.