Page Replacement Research Articles

Critical Scrutiny of Page Replacement Algorithms: FIFO, Optimal and LRU

Virtual memory plays an important role in memory management of an operating system. A process or a set of processes may have a requirement of memory space that may exceed the capacity of main memory. This situation is addressed by virtual memory where a certain memory space in secondary memory is treated as primary memory, i.e., main memory is virtually extended to secondary memory. When a process requires a page, it first scans in primary memory. If it is found then, process continues to execute, otherwise a situation arises, called page fault, which is addressed by page replacement algorithms. This algorithms swaps out a page from main memory to secondary memory and replaced it with another page from secondary memory in addition to the fact that it should have minimum page faults so that considerable amount of I/O operations, required for swapping in/out of pages, can be reduced. Several algorithms for page replacement have been formulated to increase the efficiency of page replacement technique. In this paper, mainly three page replacement algorithms: FIFO, Optimal and LRU are discussed, their behavioural pattern is analysed with systematic approach and a comparative analysis of these algorithms is recorded with proper diagram.

GCRFP - PAGE REPLACEMENT FOR SOLID STATE DRIVE USING GHOST-CACHE

State Drive (SSD) is an alternative to data storage that is popular today, widely used as a media cache to speed up data access to the hard disk (HDD). This paper proposes page replacement technique on SSD cache that used frequency and recency parameter, alternately. The algorithm is selected adaptively based on trace input. This method helps to overcome changes in access patterns while minimizing the number of write processes to SSD. The proposed algorithm can choose a replacement technique that suits the user access pattern so that it can bring a better hit rate. The proposed algorithm is also integrated with the ghost-cache mechanism so that the reduction in the number of writing processes to SSD is significant. The experiment runs using a real dataset, describing trace of data read, and data write taken from real usage. The trial shows that the proposed algorithm can give good results compared to other similar algorithms.

PRO: A periodical reset optimized page migration scheme for hybrid memory system

Due to its attractive characteristics, phase change memory (PCM) has emerged as a promising candidate to be used in main memory of embedded systems in the future. However, the write endurance problem has restricted its application in practical. Discussions regarding on hybrid memory page replacement mechanism have dominated research in recent years. Most existing schemes lack the detection for the locality regulations of memory access and do not take migration efficiency into consideration. In this paper, we rethink data access features and conduct further research on inter-reference distance to exploit the locality regulations of workloads in embedded systems. Then, propose a novel page migration scheme, Periodical Reset Optimized Page Migration Scheme (PRO), which is a hardware-software coordination algorithm. PRO largely reduces the number of write operations in PCM with limited swap operations. Meanwhile, it reduces the write operations by an average of 88.75% and decreases the average access time by an average 11.47% compared with the typical migration schemes.

Hybrid Page Replacement Algorithm in real time Operating System

Programming codes are of variable length. When the size of codes becomes greater than that of primary memory, the concept of virtual memory comes into play. As the name suggests, virtual memory allows to outstretch the use of primary memory by using storage devices such as disks. The implementation of virtual memory can be done by using the paging approach. Allocation of memory frames to each and every program is done by the operating system while loading them into the memory. Each program is segregated into pages as per the size of frames. Equal size of pages and frames enhance the usability of memory. As, the process or program which is being executed is provided with a certain amount of memory frames; therefore, swap out technique is necessary for the execution of each and every page. This swap out technique is termed as Page Replacement. There are many algorithms proposed to decide which page needs to be replaced from the frames when new pages come. In this paper, we have proposed a new page replacement technique. This new technique is based on the approach of reading and counting of the pages from secondary storage. Whenever the page fault is detected, the needed page is fetched from the secondary storage. This process of accessing the disc is slow as compared to the process in which the required page is retrieved from the primary storage. In the proposed technique, the pages having least occurrence will be replaced by the new page and the pages having same count will be replaced on the basis of LRU page replacement algorithm. In this method, the paged are retrieved from the secondary storage hence, possibility of page hit will be increased and as a result, the execution time of the processes will be decreased as the possibility of page miss will be decreased.

Architecture of a distributed storage that combines file system, memory and computation in a single layer

Storage and memory systems for modern data analytics are heavily layered, managing shared persistent data, cached data, and non-shared execution data in separate systems such as a distributed file system like HDFS, an in-memory file system like Alluxio, and a computation framework like Spark. Such layering introduces significant performance and management costs. In this paper, we propose a single system called Pangea that can manage all data—both intermediate and long-lived data, and their buffer/caching, page replacement, data placement optimization, and failure recovery—all in one monolithic distributed storage system, without any layering. We present a detailed performance evaluation of Pangea and show that its performance compares favorably with several widely used layered systems such as Spark.

A buffer based page replacement algorithm to reduce page fault

In the memory management system, the page replacement algorithm is an inevitable concept. When the Kernel creates a process, the pages are required to be in the main memory. If the pages are not found in the main memory [4], then it is called page fault. When a page fault occurs, the process needs to bring back the pages in disk. If there is a space in main memory it will be put in this area, otherwise a page replacement with the algorithm is implemented. A number of page replacing algorithms have been implemented. The main aim of this paper is to reduce the page fault, and this paper proposes a new idea for implementing a page replacement, so that the page fault reduces by a minimum of 5%.method: two more inputs read from the reference string, and are to be stored in a buffer for reference before replacing the pages in the frames. This novel algorithm increases the success rate.

Improving of cache memory performance based on a fuzzy clustering based page replacement algorithm by using four features

Internet is one of the most influential new communication technologies has influenced all aspects of human life. Extensive use of the Internet and the rapid growth of network services have increased network traffic and ultimately a slowdown in internet speeds around the world. Such traffic causes reduced network bandwidth, server response latency, and increased access time to web documents. Cache memory is used to improve CPU performance and reduce response time. Due to the cost and limited size of cache compared to other devices that store information, an alternative policy is used to select and extract a page to make space for new pages when the cache is filled. Many algorithms have been introduced which performance depends on a high-speed web cache, but it is not well optimized. The general feature of most of them is that they are developed from the famous LRU and LFU designs and take advantage of both designs. In this research, a page replacement algorithm called FCPRA (Fuzzy Clustering based Page Replacement Algorithm) is presented, which is based on four features. When the cache space can’t respond to a request for a new page, it selects a page of the lowest priority cluster and the largest login order; then, removes it from the cache memory. The results show that FCPRA has a better hit rate with different data sets and can improve the cache memory performance compared to other algorithms.

Research on document digitization processing technology

The digitalization of document information is the development direction of the digitalization of document information management, which involves various technologies such as digitalization technology, picture and text editing, storage format, etc. Through the PDF document loading display, change the page replacement storage, the technical page jump to achieve the PDF document programming control.

A page replacement algorithm based on a fuzzy approach to improve cache memory performance

The memory management in the operating system includes a part called the page replacement algorithms. Replacement algorithms in environments that require high-performance computing are considered as an important issue. For example, these algorithms are very important in cache management in microprocessors, web caching, replication strategies in distributed information systems and so on. Due to the important role of replacement algorithms in overcoming the problem of performance caused by the difference in processor speeds and memory, many algorithms were proposed. Most of them are the developed schemes of the least frequently used (LFU) and least recently used (LRU). Although most proposed designs can solve the LRU and LFU defects, they are implemented in a difficult way. The most important advantage of LRU and LFU is their simple implementation. This research proposes a page replacement algorithm that is simple to implement. The algorithm, which uses three parameters to cluster cache pages, is called the fuzzy page replacement algorithm. Whenever a miss occurs, it selects a page of the cluster with the lowest priority which has the smallest Euclidean distance with its center and then exits the cache. The most significant advantage of the algorithm is using the FCM (fuzzy c-means) algorithm to cluster pages, resulting in better replacement and hence higher memory performance.

Randomized Memoryless Algorithms for the Weighted and the Generalized k -server Problems

The weighted k -server problem is a generalization of the k -server problem wherein the cost of moving a server of weight β i through a distance d is β i ⋅ d . On uniform metric spaces, this models caching with caches having different page replacement costs. A memoryless algorithm is an online algorithm whose behavior is independent of the history given the positions of its k servers. In this article, we develop a framework to analyze the competitiveness of randomized memoryless algorithms. The key technical contribution is a method for working with potential functions defined implicitly as the solution of a linear system. Using this, we establish tight bounds on the competitive ratio achievable by randomized memoryless algorithms for the weighted k -server problem on uniform metrics. We first prove that there is an α k -competitive memoryless algorithm for this problem, where α k =α k − 1 2 + 3α k − 1 +1; α 1 = 1. We complement this result by proving that no randomized memoryless algorithm can have a competitive ratio less than α k . Finally, we prove that the above bounds also hold for the generalized k -server problem on weighted uniform metrics.

Kiiling Media Piracy by using Artificial

Now a day’s Artificial intelligence is very important. To eradicate the media piracy on the internet we are going to implement the technique called the page replacement algorithm by using the artificial intelligence. Detecting and stopping by manually it is not possible to remove manually. The page replacement algorithm will help to detect the media piracy on the internet. Internet means that any of the social media platforms like gmail ,youtube,drives etc. By using this page replacement algorithm we are going to achieve. This algorithm will helps to detect it will divide into the number of frames each page has the several frames .Each frame in the page get scanned by the page replacement algorithm . Based on this technique replaces the page that used for the long period of time. This page replacement algorithm has to work very fastlly and consumes the less memory. This technology has controlled by the any government companies. The government has specified companies to detect such piracy. The LRU technique maintains the backward of the page. This LRU helps within seconds to detect the piracy on the internet.

An Energy Aware Strategy for Distributed Cache Discovery with Stale Page Reduction

With the immense growth in the field of mobile communication, a good number of complex applications are now available for the mobile devices. The complex applications are made available to comply with the client demand for the higher performing and higher capable applications, which can be accessible from any locations and any devices. Thus, the application developers have attempted to make highly scaled applications to be deployed on mobile communication devices. The larger applications have higher demand for memory and processing capabilities. Thus, making the similar infrastructure available on the mobile computing environments was always a challenge. Nonetheless, with the availability of distributed computing architecture, the bottleneck for the computing capabilities for these complex applications can be handled. Nonetheless, the memory capabilities for the applications must be addressed more sophisticated manner using distribution of the memory and sharing of the data. Henceforth, distributed caching came under existence.A conveyed cache is an augmentation of the customary idea of cache utilized in a solitary district. A conveyed cache may traverse various servers with the goal that it can develop in size and in value-based limit. It is for the most part used to store application information living in database and web session information.One of the most popular technique for making the cache available is to perform cache discovery operations in the network. A number of parallel research attempts are made to identify the accurate place in the network to create or build the distributed cache network.However, the most of the parallel research attempts are criticised for considering single dimensions for cache discovery as few of the work focuses on distance, few of the work focuses on density and some of the works focuses on page replacement policies applicable on mobile computing environments as MANETs or WSN. Henceforth, the demand of the research is to consider multiple parameters for cache discovery and build a framework to automatically define the cache distribution. Hence, this work proposes a novel architecture or framework to detect the cache distribution based on distance, stale page reduction mechanism and finally the energy optimization. The outcome of the research is to automate the recommendation of cache discovery and increase the network life time by 90% compared to the existing methods for cache discovery. In order to handle the complex processing of the proposed algorithms, this work deploys machine learning methods to reduce the time complexity.

VAIL: A Victim-Aware Cache Policy to improve NVM Lifetime for hybrid memory system

Nowadays emerging Non-Volatile Memory (NVM) is introduced to remedy the shortages of current DRAM-based main memory, but limited write en-durance of NVM would severely restrict memory system. Many techniques are proposed to extend NVM lifetime based on DRAM and NVM hybrid memory. However, most of them cannot obtain satisfactory NVM lifetime and performance at the same time for various workloads, because they fail to deal well with the conict between reducing writebacks to NVM and improving DRAM access hit ratio. In order to solve this problem, we propose a Victim-Aware Cache Policy named VAIL for DRAM and NVM hybrid memory system. VAIL uti-lizes the property of victim pages to estimate and predict the impact of clean and dirty page replacement on writebacks to NVM and DRAM access hit ratio. Then, pick the page which has the minimal negative impact for replacement. By doing so, VAIL can reduce writebacks to NVM and achieve high DRAM access hit ratio simultaneously. It outperforms the state-of-the-art by 1.29x higher performance and leads to 11.7% less NVM wear-out, according to our evaluation with HPC, graph computing, and machine learning workloads.

Subject Review: Comparing and Analyzing Page Fault Schemes According to Estimated Time

Active page replacement approaches are required for the virtual memory for the purpose of resolving what data pages are going to be driven out from the memory when a page fault occurs. For years, a lot of algorithms have been developed to avoid page fault, all these algorithms have the efforts of decreasing the proportion related to the reduce error in the same time as incurring minimal overhead. Since up-to-date patterns of memory access have been studied, the study has the aim of creating novel methods for page replacement that can be adaptive to the varying workloads. The presented review aims of comparing the assessed replacement time for the main methods of page replacement. Some conventional methods like CLOCK and LRU will be examined, as well as some new methods like 2-DPR, CLOCK-Pro, LIRS, and CAR.

Probabilistic Page Replacement Policy in Buffer Cache Management for Flash-Based Cloud Databases

In the fast evolution of storage systems, the newly emerged flash memory-based Solid State Drives (SSDs) are becoming an important part of the computer storage hierarchy. Amongst the several advantages of flash-based SSDs, high read performance, and low power consumption are of primary importance. Amongst its few disadvantages, its asymmetric I/O latencies for read, write and erase operations are the most crucial for overall performance. In this paper, we proposed two novel probabilistic adaptive algorithms that compute the future probability of reference based on recency, frequency, and periodicity of past page references. The page replacement is performed by considering the probability of reference of cached pages as well as asymmetric read-write-erase properties of flash devices. The experimental results show that our proposed method is successful in minimizing the performance overheads of flash-based systems as well as in maintaining the good hit ratio. The results also justify the utility of a genetic algorithm in maximizing the overall performance gains.

Survey Inter-Reference Recency Based Page Replacement Policies to Cope with Weak Locality Workloads

Least recently used (LRU) makes bold assumption on recency factor only which made LRU miss behave with weak locality workloads. If the “frequency”, of each page reference is taken into consideration, it will perform better in the case where workload has weak locality. Frequency count leads to serious problem after a long duration of reference stream because it cannot cope with change in locality. Reuse distance or inter reference recency (IRR) of a block is equal to number of distinct pages accessed between recent consecutive or correlated access of that particular block. Many recent variations of LRU use IRR rather than recency such that LRU can be made friendly with weak locality workloads. This papers surveys LRU variants that use IRR to make page replacement decision.

The MT Stack: Paging Algorithm and Performance in a Distributed Virtual Memory System


 
 
 Advances in parallel computation are of central importance to Artificial Intelligence due to the significant amount of time and space their pro- grams require. Functional languages have been identified as providing a clear and concise way of programming parallel machines for artificial intelligence tasks. The problems of exporting, creating, and manipulating processes have been thoroughly studied in relation to the paralleliza- tion of functional languages, but none of the necessary support structures needed for the ab- straction, like a distributed memory, have been properly designed. In order to design and im- plement parallel functional languages efficiently, we propose the development of an all-software based distributed virtual memory system de- signed specifically for the memory demands of a functional language. In this paper, we review the MT architecture and briefly survey the related literature that lead to its development. We then present empirical results obtained from observ- ing the paging behavior of the MT stack. Our empirical results suggest that LRU is superior to FIFO as a page replacement policy for MT stack pages. We present a proof that LRU is an opti- ?Partially supported by the Seton Hall University Re- search Council. †Partially supported by NSF grant CDA-9114481. ‡Partially supported by NSF grant HRD-9703600. mal page replacement policy. Based on this proof the MT stack page replacement policy was de- veloped and implemented. We outline the paging algorithm and present an argument of partial cor- rectness. The MT stack page replacement policy is superior to LRU, because it does not incur the expensive time penalties associated with imple- menting LRU in software.
 
 

An Improved Page Replacement Algorithm Using Block Retrieval of Pages

The computer programmer write programming codes of any length without keeping in mind the available primary memory. This is possible if we use the concept of virtual memory. As the name suggests, virtual memory is a concept of executing a programming code of any size even having a primary memory of smaller size than the size of program to be executed. The virtual memory can be implemented using the concept of paging. The operating system allocates a number of memory frames to each program while loading into the memory. The programming code is equally divided into pages of same size as frame size. The size of pages and memory frames are retained equal for the better utilization of the memory. During the execution of program, every process is allocated limited number of memory frames; hence there is a need of page replacements. To overcome this limitation, a number of page replacement techniques had suggested by the researchers. In this paper, we have proposed an modified page replacement technique, which is based on the concept of block reading of pages from the secondary storage. The disc access is very slow as compared to the access from primary memory. Whenever there is a page fault, the required page is retrived from the secondary storage. The numerous page faults increase the execution time of process. In the proposed methodology, a number of pages, which is equal to the allotted memory frames, are read every time when there is a page fault instead of reading a single page at a time. If a block of pages has fetched from secondary storage, it will definitely increases the possibilities of page hit and as a result, it will improve the hit ratio for the processes.

M-CLOCK

Phase Change Memory (PCM) has drawn great attention as a main memory due to its attractive characteristics such as non-volatility, byte-addressability, and in-place update. However, since the capacity of PCM is not fully mature yet, hybrid memory architecture that consists of DRAM and PCM has been suggested as a main memory. In addition, page replacement algorithm based on hybrid memory architecture is actively being studied, because existing page replacement algorithms cannot be used on hybrid memory architecture in that they do not consider the two weaknesses of PCM: high write latency and low endurance. In this article, to mitigate the above hardware limitations of PCM, we revisit the page cache layer for the hybrid memory architecture and propose a novel page replacement algorithm, called M-CLOCK, to improve the performance of hybrid memory architecture and the lifespan of PCM. In particular, M-CLOCK aims to reduce the number of PCM writes that negatively affect the performance of hybrid memory architecture . Experimental results clearly show that M-CLOCK outperforms the state-of-the-art page replacement algorithms in terms of the number of PCM writes and effective memory access time by up to 98% and 9.4 times, respectively.

Energy-aware page replacement and consistency guarantee for hybrid NVM–DRAM memory systems

Abstract Non-Volatile Memory (NVM) has been widely used in hybrid memory architecture due to the promising advantages like high density and low power consumption. Most of existing page replacement methods focused on prolonging the life time of NVM memory systems, which either consider the energy cost or deal with consistency errors caused by system failures. This paper proposes a page replacement method based on NVM–DRAM hybrid main memory systems for low power and consistency guarantee, called Energy-Aware Page Replacement (EAPR). The energy consumption of page access in DRAM and NVM is modelled considering the memory access like reading, writing and idle. EAPR utilizes page grouping policy to improve the migration efficiency between NVM and DRAM. Page groups are chosen to migrate according to their energy-related substitution degrees. To guarantee the consistency during page migration, this paper designs two consistency guarantee schemes in page replacement phase and transaction committing phase. Instead of deleting logs directly, our approach guarantees the consistency of hybrid memory systems by modifying the data structures of logs after the transactions of applications are submitted. Based on existing benchmarks, we conduct extensive experiments to evaluate the proposed method. Experimental results show that EAPR can reduce the energy consumption up to 40.19% compared with the existing page replacement algorithms, and also guarantee the consistency of transactions in NVM–DRAM hybrid memory systems.