Small Files Research Articles

Analisis Perbandingan Teknik Video Codec H.264/AVC, H.265/HEVC, VP9 dan AV1

Video applications consume more energy on the Internet and can be accessed by electronic devices, due to an increase in the consumption of high-resolution and high-quality video content, presenting serious issues to delivery infrastructure that needs higher video compression technologies. The focus of this paper is to evaluate the quality of the most current codec, AV1, to its predecessor codec. The comparison was made experimentally at two video resolutions (1080p and 720p) by sampling video frames with various CRF/CQP values and testing several parameters analyses such as encoding duration, compression ratio, bit rate, Mean Square Error (MSE), and Peak Signal to Noise Ratio (PSNR). The AV1 codec is very great in terms of quality and file size, even though it is slower in terms of compression speed. The H.265/HEVC codec, on the other side, beats the other codec in terms of compression ratio. In conclusion, the H.265/HEVC codec is suggested as a material for obtaining a well compressed video with small file size and a short time.

Implementation of Distributed Operation and Maintenance of Cross-Border e-Commerce Platform Based on Cloud Native Architecture

The traditional architecture of e-commerce data management needs to adapt to the new and more complex environment, which needs to provide massive data management, compatibility of different types of data, and better user experience. Cloud computing technology is a synthesis of parallel, distributed, and grid computing and is one of the future directions of information technology development. In this paper, we use cloud computing data management technology to study the data management of e-commerce. It is hoped that the current e-commerce data management can be improved with the help of cloud computing technology. This paper starts from analyzing the current e-commerce representatives Taobao.com and Jingdong Mall to find out the data characteristics of these two enterprises, analyze the existing data problems, and find the aspects that can be improved. Using this open-source cloud computing implementation solution, we solve the storage problem of large files and unstructured small files in the e-commerce system.

A NFT verification method for distributed AI system

This paper proposes a method invention, namely an efficient NFT data inspection method with minimum granularity and probability comparison. The invention establishes a fast comparison method of AI model and data, that is, the direct comparison of small files priority and the maximum-minimum interval comparison. The invention takes the substantial identity inside the NFT data and the processing method of NFT data coincidence into account, so that the data content outside the token of the NFT publicly shared by the AI distributed system can also be unique on the Internet. Therefore, it can avoid the problem of incremental packaging and repeated packaging, and can successfully balance the efficiency and security of the comparison process. portions given in this document

Distributed Storage Strategy and Visual Analysis for Economic Big Data

With the increasing popularity of a large number of Internet-based services and a large number of services hosted on cloud platforms, a more powerful back-end storage system is needed to support these services. At present, it is very difficult or impossible to implement a distributed storage to meet all the above assumptions. Therefore, the focus of research is to limit different characteristics to design different distributed storage solutions to meet different usage scenarios. Economic big data should have the basic requirements of high storage efficiency and fast retrieval speed. The large number of small files and the diversity of file types make the storage and retrieval of economic big data face severe challenges. This paper is oriented to the application requirements of cross-modal analysis of economic big data. According to the source and characteristics of economic big data, the data types are analyzed and the database storage architecture and data storage structure of economic big data are designed. Taking into account the spatial, temporal, and semantic characteristics of economic big data, this paper proposes a unified coding method based on the spatiotemporal data multilevel division strategy combined with Geohash and Hilbert and spatiotemporal semantic constraints. A prototype system was constructed based on Mongo DB, and the performance of the multilevel partition algorithm proposed in this paper was verified by the prototype system based on the realization of data storage management functions. The Wiener distributed memory based on the principle of Wiener filter is used to store the workload of each workload distributed storage window in a distributed manner. For distributed storage workloads, this article adopts specific types of workloads. According to its periodicity, the workload is divided into distributed storage windows of specific duration. At the beginning of each distributed storage window, distributed storage is distributed to the next distributed storage window. Experiments and tests have verified the distributed storage strategy proposed in this article, which proves that the Wiener distributed storage solution can save platform resources and configuration costs while ensuring Service Level Agreement (SLA).

‘Goldilocks anatomy’ – data-conserving anatomy video tutorials during emergency remote teaching

Namibia’s State of Emergency was announced on 27 March 2020. Institutional attempts to introduce blended learning and formal online learning during the COVID-19 pandemic prior to the students leaving campus came too late. We subsequently did not have the luxury of time to plan and prepare formal online material. Emergency remote teaching (ERT) was started whilst our students were on recess with many stuck at home in rural off-grid settings. They were subsequently faced with erratic internet connectivity and limited data. This limitation necessitated a small file size alternative that addressed the educational needs of our students whilst permitting constructive alignment with the intended learning objectives. Furthermore, it was also found that students prefer communication through WhatsApp. Here the authors report on a novel and content-specific approach to ERT through to-the-point anatomy video tutorials that are data friendly – i.e., Goldilocks Anatomy.

Distributed Storage Allocations for Optimal Service Rates

Distributed systems operate under storage access and download service uncertainty. We consider two access models. In one, a user can access each storage node with a fixed probability, and in the other, a user can access any fixed-size subset of nodes. We consider two download service models. In the first (small file) model, the time to transmit file data is negligible compared to the overall average download time. In the second (large file) model, the download time scales with the amount of downloaded data. The performance metric is the system’s service rate. For a fixed redundancy level, the systems’ service rate depends on the allocation of coded chunks over the storage nodes. Since finding the general optimal allocation is prohibitively hard, we consider quasi-uniform allocations, where coded content is equally spread among a subset of nodes. The question we address asks what the size of this subset (spreading) should be. We show that concentrating the coded content to a minimum-size subset is universally optimal for the small file model. However, for the large file model, the optimal spreading depends on the system parameters. These conclusions hold for both access models.

Repair Delay Analysis of Mobile Storage Systems Using Erasure Codes and Relay Cooperation

Mobile storage systems (MSSs) which store popular content in mobile devices can reduce the heavy traffic burden on the base station (BS). To deal with data loss caused by the mobility of devices, erasure codes are widely used in practice to improve system reliability. The duration to repair all lost data is defined the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">repair delay</i> . However, the repair delay via device-to-device communications is usually large due to intermittent contacts among devices within a given communication range, which causes files to be irreparable and permanently lost. This paper focuses on analyzing the repair delay of the MSSs through D2D communications. We adopt a coded repair process running periodically and derive analytical expressions of the average repair delay by taking into account factors, i.e., limited communication range, device mobility, and coded repair scheme. Moreover, considering that devices need multipath contacts to repair lost data for large files, we propose a relay cooperation repair scheme, in which some mobile devices can act as relay nodes to transmit data cooperatively. Furthermore, we design a heuristic algorithm to optimize the number of relay devices and the amount of data allocated to each path, with the objective of minimizing the average repair delay. We find that maximum distance separable codes can yield smaller average repair delays for small files, and the average repair delay can be reduced by selecting faster moving devices to participate. With the file size increasing, the relay cooperation repair scheme can significantly improve repair efficiency in MSSs using the proposed heuristic algorithm.

Data Pattern Aware Reliability Enhancement Scheme for 3D Solid-State Drives

3D charge-trap (CT) NAND flash-based SSD has been used widely for its large capacity, low cost per bit, and high endurance. One-shot program (OSP) scheme, as a variation of incremental step pulse programming (ISPP) scheme, has been employed to program data for CT flash, whose program unit is the Word-Line (WL) instead of the page. The existing program optimization schemes either make trade-offs among program latency and reliability by adjusting the program step voltage on demand; or remap the most error-prone cell states to others by re-encoding programmed data. However, the data pattern, which represents the ratio of 1s in data values, has not been thoroughly studied. In this paper, we observe that most small files do not contain uniform 1s and 0s among these common file types (i.e., image, audio, text, executable file), leading to programming WL cells in different states unevenly. Some cell states dominate over the WL, while others are not. Based on this observation, we propose a flexible reliability enhancement scheme based on the OSP scheme. This scheme programs the cells into different states with varied , i.e., these cells in one state, whose number is the largest in one WL, are programmed with a fine-grained (namely slow write). In contrast, the minority are programmed with a coarse-grained (namely fast write). So the reliability is improved due to averaging the major enhanced cells with the minor degraded cells without program latency overhead. A series of experiments have been conducted, and the results indicate that the proposed scheme achieves 34% read performance improvement and 16% lifetime elongation on average.

Performance Study on Indexing and Accessing of Small File in Hadoop Distributed File System

Hadoop Distributed File System (HDFS) is developed to efficiently store and handle the vast quantity of files in a distributed environment over a cluster of computers. Various commodity hardware forms the Hadoop cluster, which is inexpensive and easily available. The large number of small files stored in HDFS consumed more memory which lags the performance because small files consumed heavy load on NameNode. Thus, the efficiency of indexing and accessing the small files on HDFS is improved by several techniques, such as archive files, New Hadoop Archive (New HAR), CombineFileInputFormat (CFIF), and Sequence file generation. The archive file combines the small files into single blocks. The new HAR file combines the smaller files into a single large file. The CFIF module merges the multiple files into a single split using NameNode, and the sequence file combines all the small files into a single sequence. The indexing and accessing of a small file in HDFS are evaluated using performance metrics, such as processing time and memory usage. The experiment shows that the sequence file generation approach is efficient when compared to other approaches concerning file access time is 1.5[Formula: see text]s, memory usage is 20 KB in multi-node, and the processing time is 0.1[Formula: see text]s.

The Role of Vertical Elastic Namenode in Handling Big Data in Small Files

The Role of Vertical Elastic Namenode in Handling Big Data in Small Files

Comparative Analysis of Distributed File Systems

It has been observed that there has been a great interest in computing experiments which has been useful on shared nothing computers and commodity machines. We need multiple systems running in parallel working closely together towards the same goal. Frequently it has been experienced and observed that the distributed execution engine named MapReduce handles the primary input-output workload for such clusters. There are numerous distributed file systems around viz. NTFS,ReFS,FAT,FAT32 in windows and linux, we studied them and implemented a few distributed file systems. It has been studied that distributed file systems (DFS) work very well on many small files but some do not generate expected output on large files. We implemented benchmark testing algorithms in each distributed files systems for small and large files, and the analysis is been put forward in this paper. Even we came across the various implementation issues of various DFS, they have also been mentioned in this paper.

Iatrogenic complications arising from cleaning and shaping

Endodontic treatments tend to have very high successful rates in spite of the fact that they are quite an invasive, difficult procedure, especially in complex anatomies. As a consequence, retreatment has become a well-defined field of knowledge and expertise in endodontics, since most complications can be solved with proper surgical or nonsurgical retreatments. Failure to grasp the rationale behind cleaning and shaping concepts can increase the occurrence of needless complications, such as ledges. Extension of the access cavity to provide unobstructed access to the root canals, precurving and not forcing instruments, using NiTi files, using passive step-back and balanced force techniques, and instrumenting the canal to its full length will all help to prevent ledge formation. Initial negotiation and bypassing the ledge can be achieved using a small file with a distinct curve at the tip, whereas a slight rotation motion of the file combined with a picking motion can often help advance the instrument. Blockage, laceration, and foraminal damage are the most common results. Each alters the reliability of the procedure and must be prevented if one is to obtain the best possible prognosis for the patient.

Application of GUI Matlab in physics: Planetary motion (Kepler’s Law)

This study aimed to create a teaching material using an application with a Graphical User Interface (GUI) provided on MATLAB. This teaching material is intended for Physics subject. Creating a GUI with MATLAB was made using the guide facility provided in MATLAB. The MATLAB GUI has a relatively small file size so that it can speed up the running program commands. This research aimed to create an application that is easy and effective to be used by users without having to understand the complexity of computing MATLAB. The application consists of a main menu, a GUI that can be run according to the materials needed by the users, as well as a menu to close the application. The physical matter contained in it is planetary motion (Kepler’s law). Physics learning materials that can be used as a reference in running the GUI program, e-modules containing procedures for creating the GUI by using MATLAB for learning, as well as the MATLAB source code used in every programming. For further research, the author expects the development of this study by using the e-module contained in the application as a material for creating GUI MATLAB.

Blockchain periodic storage space recovery method based on blockchain consensus algorithm

Decentralized encryption digital cash has been proved to be a successful application mode, and the users of the application can also be the maintainers of this application. To solve the problem of fast growth of blockchain data on Ethereum platform, this paper proposes a method to recycle the periodic storage space of blockchain deployed on blockchain based on blockchain consensus algorithm. On the principle of decentralization, the problem of mutual trust between nodes is solved. And that stability value of the update storage node is recorded, and the high-stability node is selecte to store the newly generated data copy, so that the stability of data storage is improved. Finally, some bytecode fragments are replaced by a suitable algorithm. Tests show that the massive small file system supporting file deletion has no obvious decline in file reading and writing performance compared with the original one, and the storage space of smart contracts can be saved by nearly 46%.

Automated Assignment of Proteoform Classification Levels.

Proteoform identification is required to fully understand the biological diversity present in a sample. However, these identifications are often ambiguous because of the challenges in analyzing full length proteins by mass spectrometry. A five-level proteoform classification system was recently developed to delineate the ambiguity of proteoform identifications and to allow for comparisons across software platforms and acquisition methods. Widespread adoption of this system requires software tools to provide classification of the proteoform identifications. We describe here an implementation of the five-level classification system in the software program MetaMorpheus, which provides both bottom-up and top-down identifications. Additionally, we developed a stand-alone program called ProteoformClassifier that allows users to classify proteoform results from any search program, provided that the program writes output that includes the information necessary to evaluate proteoform ambiguity. This stand-alone program includes a small test file and database to evaluate if a given program provides sufficient information to evaluate ambiguity. If the program does not, then ProteoformClassifier provides meaningful feedback to assist developers with implementing the classification system. We tested currently available top-down software programs and found that none of them (other than MetaMorpheus) provided sufficient information regarding identification ambiguity to permit classification.

Hadoop Perfect File: A fast and memory-efficient metadata access archive file to face small files problem in HDFS

HDFS faces several issues when it comes to handling a large number of small files. These issues are well addressed by archive systems, which combine small files into larger ones. They use index files to hold relevant information for retrieving a small file content from the big archive file. However, existing archive-based solutions require significant overheads when retrieving a file content since additional processing and I/Os are needed to acquire the retrieval information before accessing the actual file content, therefore, deteriorating the access efficiency. This paper presents a new archive file named Hadoop Perfect File (HPF). HPF minimizes access overheads by directly accessing metadata from the part of the index file containing the information. It consequently reduces the additional processing and I/Os needed and improves the access efficiency from archive files. Our index system uses two hash functions. Metadata records are distributed across index files using a dynamic hash function. We further build an order-preserving perfect hash function that memorizes the position of a small file's metadata record within the index file.

Influence of maintaining apical patency in post-endodontic pain

BackgroundThe concept of instrumentation beyond the apical foramen by small flexible file to prevent apical blockage is apical patency. However, this procedure might endow postoperative pain, thus to maintain apical patency or not is the matter of dilemma. Hence, the primary objective of this study was to compare postoperative pain between apical patency and non-patency groups and secondary objective was to evaluate the influence of number of visits, vitality of teeth, group of teeth and preoperative pain on post-operative pain.MethodsPreselected (n = 178) patients based on group of teeth and status of pulp were randomly divided into 2 groups, apical patency and non-patency which was further treated in either single or multiple visits. After exclusion, 160 patients were included. Each group (n = 80) was subdivided in single visit (n = 40) and multiple visits (n = 40), including vital (n = 20) and non-vital teeth (n = 20) and single-rooted (n = 10) and multiple-rooted teeth (n = 10). Apical patency was maintained with a size 10 K-file during conventional hand filing step-back shaping procedure. Intensity of pain was recorded before treatment and on days 1, 2, and 7 after treatment using Numerical Rating Scale (NRS-11). Statistical analysis was done using Mann–Whitney U test, Spearman correlation and Multiple linear regression analysis.ResultsThe primary outcome of this study showed statistically significant difference (p < 0.05) in postoperative pain scores between patency and non-patency groups with higher pain scores in patency group on 1st, 2nd and 7th day follow up. The secondary outcome showed postoperative pain in patency-maintained group was influenced by status of the pulp and preoperative pain only. Vital teeth of patency-maintained group treated in multiple visits showed statistically significant (p = 0.02) post-operative pain in day 1 follow up. Pre-operative pain showed positive correlation with postoperative pain with statistically significant difference.ConclusionsOur study concluded that maintenance of apical patency increased postoperative pain. Evaluation of influence of number of visits, status of pulp, group of tooth and preoperative pain revealed status of pulp and preoperative pain as influencing factors for postoperative pain in patency group.

QoE-Driven Edge Caching in Vehicle Networks Based on Deep Reinforcement Learning

The Internet of vehicles (IoV) is a large information interaction network that collects information on vehicles, roads and pedestrians. One of the important uses of vehicle networks is to meet the entertainment needs of driving users through communication between vehicles and roadside units (RSUs). Due to the limited storage space of RSUs, determining the content cached in each RSU is a key challenge. With the development of 5G and video editing technology, short video systems have become increasingly popular. Current widely used cache update methods, such as partial file precaching and content popularity- and user interest-based determination, are inefficient for such systems. To solve this problem, this paper proposes a QoE-driven edge caching method for the IoV based on deep reinforcement learning. First, a class-based user interest model is established. Compared with the traditional file popularity- and user interest distribution-based cache update methods, the proposed method is more suitable for systems with a large number of small files. Second, a quality of experience (QoE)-driven RSU cache model is established based on the proposed class-based user interest model. Third, a deep reinforcement learning method is designed to address the QoE-driven RSU cache update issue effectively. The experimental results verify the effectiveness of the proposed algorithm.

An Efficient Approach for Merging Small Files in HDFS Storage and Accessing Small Files by Using Name Node Method in Big Data

Big Data is one of the most requested techniques in the modern world of software development. In Big Data, the treatment of distributed files is performed by the open-source software framework called Hadoop on the product hardware cluster. For the storage of Big Data, the Framework is considered the most powerful. The HDFS Name Node component is used to store all sorts of files, folders, and blocks or metadata. The HDFS is specially designed to handle large files, but this framework will not properly handle a large number of small files. Proposed systems introduce that how the Name Node memory overheads the data storage reduces the storage of the huge number of small-size files in the HDFS. This approach will be very helpful in understanding the memory consumption and workload in the Name Node reduces the distributed file system called Hadoop.

Remote attestation and integrity measurements with Intel SGX for virtual machines

With response to the emerging virtualization trend, we focus on a Virtual Machine (VM) remote attestation process assuming that it is running in an uncontrolled and untrusted cloud infrastructure.We present a solution that is able to establish a chain of trust in a cloud environment. Our solution is based on a set of CPU instructions and it does not need any additional components to track host modifications. Our solution enables integrity verification of a filesystem. Additionally, it ensures trust level assessment for remote VMs during their startup or while triggered manually at any point in time afterwards.We identify security properties for our solution and show how it meets them. The security analysis shows that with necessary countermeasures, the proposed model can ensure the required level of security. Additionally, We evaluate the performance impact of the prototype and virtualization overhead for a real-life scenario. Here, we assume that small configuration files, binaries, and executables are most critical. The results show that important filesystem components can be verified with a minimum impact on a startup time. This way, the whole proposal allows for making VM a part of a trusted compute resource pool.