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3D NAND Flash is the preferred storage medium for dense mass storage applications, including Solid State Drives and multimedia cards. Improving the latency of these systems is a mandatory task to narrow the gap between computing elements, such as CPUs and GPUs, and the storage environment. To this extent, relatively time-consuming operations in the storage media, such as data programming and data erasing, need to be prioritized and be potentially suspendable by shorter operations, like data reading, in order to improve the overall system quality of service. However, such benefits are strongly dependent on the storage characteristics and on the timing of the single operations. In this work, we investigate, through an extensive characterization, the impacts of suspending the data programming operation in a 3D NAND Flash device. System-level simulations proved that such operations must be carefully characterized before exercising them on Solid State Drives to eventually understand the performance benefits introduced and to disclose all the potential shortcomings.

Data randomization has been a widely adopted Flash Signal Processing technique for reducing or suppressing errors since the inception of mass storage platforms based on planar NAND Flash technology. However, the paradigm change represented by the 3D memory integration concept has complicated the randomization task due to the increased dimensions of the memory array, especially along the bitlines. In this work, we propose an easy to implement, cost effective, and fully scalable with memory dimensions, randomization scheme that guarantees optimal randomization along the wordline and the bitline dimensions. At the same time, we guarantee an upper bound on the maximum length of consecutive ones and zeros along the bitline to improve the memory reliability. Our method has been validated on commercial off-the-shelf TLC 3D NAND Flash memory with respect to the Raw Bit Error Rate metric extracted in different memory working conditions.

With the emergence of ferroelectric HfO 2 - and ZrO 2 -based thin films, the topic of ferroelectric memories has been experiencing a renaissance. These novel ferroelectric materials promise to overcome fundamental scaling and integration roadblocks of the three basic types of ferroelectric memory concepts, FRAM, FeFET and FTJs. While the understanding of the formation of ferro- and antiferroelectric properties in HfO 2 - and ZrO 2 has matured in recent years, also new memory concepts have been suggested. Some represent an advancement of the three basic ferroelectric memories other enhance the performance of existing mainstream memories by incorporating (anti-)ferroelectric layers. The present work gives an overview of these different concepts. The CMOS compatibility allows for a large variety of device architectures, which can address the entire spectrum from mass storage to chache memory. There is a serious industry drive with demonstrators up to array level and most concepts are remarkably close to commercial state-of-the-art memories. Therefore, it seems that ferroelectric memory is finally poised to make inroads into mass markets.

Heterogeneous doping through nanostructuring has been demonstrated to greatly enhance the transport and mass storage properties of halides and Li-ion conductors by decoupling of charge-compensating species. In this study, we explore the potential of heterogeneous doping of ionically conducting oxides through first-principles and thermodynamic calculations of a model system consisting of acceptor-doped SrTiO3 and BaZrO3. We show that the two dominating defects, vO•• and OHO•, are thermodynamically favored in BaZrO3 compared to SrTiO3 by 0.64 and 0.56 eV, respectively, in turn leading to an electrostatic potential barrier as large as 0.64 V (relative to BaZrO3) at 800 K. vO••, OHO• and electron holes as such accumulate on the BaZrO3 side of the interface, leading to a charge-depletion layer in SrTiO3 which thus acts as a heterogeneous acceptor for BaZrO3. These interface effects may drastically enhance the charge-carrier concentration of weakly doped ionic systems, which in turn may lead to novel nanostructured composite materials with enhanced transport properties or, for instance, kinetics for oxygen reduction or water splitting.

One way to increase storage density is using a shingled magnetic recording (SMR) disk. We propose a novel use of SMR disks with RAID (redundant array of independent disks) arrays, specifically building upon and compared with a basic RAID 4 arrangement. The proposed scheme (called RAID 4SMR) has the potential to improve the performance of a traditional RAID 4 array with SMR disks. Our evaluation shows that compared with the standard RAID 4, when using update in-place in RAID arrays, RAID 4SMR with garbage collection not just can allow the adoption of SMR disks with a reduced performance penalty, but offers a performance improvement of up to 56%.

Non-prescriptive design within fire engineering is becoming more prevalent as buildings get taller and more complex. This necessitates the increased use of reliable deterministic predictions; typically computational fluid dynamics-based models. Driven by time constraints, modellers are required to limit the domain to reduce wall time. This ignores the two-way coupling of a fire and a total building system. A neglection which could embody risk to life. One way to address this risk is the use of coupled hybrid modelling to expand the domain; explicitly quantifying risk-related quantities in the far field whilst maintaining practicable wall times. Fire Dynamics Simulator (FDS) version 5.5 opened the door to coupled hybrid modelling within FDS and introduced the HVAC network submodel. Until FDS version 6.5.3 the submodel did not account for transient transport or mass storage. In this work a new transient transport and mass storage subroutine has been introduced into HVAC which is available in FDS version 6.5.3 onwards. The relevant conservation equations and numerical solution are described. Successful verification cases are presented for various arrangements to test the implementation of the solution scheme. To demonstrate the benefits of the new method, a fire engineering test case is presented. The test case illustrates the potential risks contained within the pre-existing coupled hybrid modelling method. These risks include unrealistic predictions of hot layer height and head height temperatures and visibility. The test case demonstrates that the new coupled hybrid modelling method address these shortcomings and could form part of a most robust fire safety engineering solution. Based on experimental benchmarking exercises, recommended model bias factors are put forward.The new model implementation can be used by designers to quantitatively examine the fire hazard embodied within the two-way coupling of a fire and a total building system.

Missions, both near Earth and deep space, are under consideration that will require data recorder capacities doubled at a rate of approximately every three years. This challenge for ever-increasing mass storage also exists in other applications, such as unmanned aerial vehicle (UAV) and echo recording for phased array radar (PAR). All these scenarios call for storage devices with larger capacity, higher I/O bandwidth, lower latency and smaller size. In this paper, we combine Field Programmable Gate Array (FPGA)-based efficient cores of the emerging Non-Volatile Memory express (NVMe) protocol with Flash storage to improve the I/O bandwidth and latency from the operating system (OS) storage I/O software stack. We provide an alternating operation scheme to guarantee consistency of I/O bandwidth. The device has two independent optical fiber channels to ensure the reliability of interconnections and four NVMe flash storage recording data respectively at the same time, which increase its integration and scalability. The prototype has a capacity of 8TB and a volume of only 990 cubic centimeter, weighing only 2.2 pounds. Experimental results demonstrate that the continuous I/O bandwidth of each channel is above 1GBps with variance no more than 7% for its total capacity, and NVMe host logic core achieves up to 88% lower latency against the OS-based system.

Big data-based acquisition and storage system (ASS) plays an important role in the design of industrial data platform. Many big data frameworks have been integrated compression and serialization method. These methods cannot meet the needs of industrial production information management for requiring time-consuming and mass storage. Based on the existing big data frameworks, we propose an enhanced industrial big data platform in order to reduce the data processing time while requiring fewer data storage space. Specifically, this paper focuses on evaluating the impact of multiple compression and serialization methods on big data platform performance and tries to choose optimal compression and serialization methods for the industrial data platform. Compared to the methods integrated in Hadoop and Spark, the experimental results showed the data compression time of the platform has been reduced by 73.9% with a less than 96% the size of data compressed, furthermore, the data serialization time has been reduced by 80.8%. With the increasing amount of data, it takes less time to compare with benchmark methods.

Aim. MRO2 system is a data management platform. It has the ability to manage and store all kinds of data in the product's lifecycle, that is both the mass storage capacity and the scalability are required. For the existing big-data stores for MRO2 systemeither only focus on the storage problem, or only do the scalability issue. In this paper, a two-layer data management model is proposed, in which the top layer uses the memory storage for scalability and the bottom layer uses the distributed key-value storage for mass storage. By adding a middle layer of the key group between the application and the KV storage system, the keys for real-time processing are combined to cache in a node. It satisfies the characteristics of the real-time application and improves the dynamic scalability. The present protocol of the dynamic key groups for real-time distributed computation for MRO2 system is explained in detail. And then the protocol for creating and deleting key groups is introduced. The third topic is an implement of a big-data store for supporting MRO2 system. In this topic, the delay times for creating and deleting the dynamic transaction groups to estimation are used. Finally, the experiments to appraise the present method are done. The response time of the present method is quite efficient in comparison with the other methods to be used inbig data storage systems.

Electrical probe memory has received considerable attention during the last decade due to its prospective potential for the future mass storage device. However, the electrical probe device with conventional diamond-like carbon capping and bottom layers encounters with large interfacial contact resistance and difficulty to match the experimentally measured properties, while its analog with titanium nitride capping and bottom layers also faces serious heat dissipation through either probe and silicon substrate. Therefore, the feasibility of using indium tin oxide (ITO) media for the capping and bottom layers of the electrical probe device is investigated by tailoring the thickness and electrothermal properties of the ITO capping and bottom layers within experimentally established range and subsequently calculating the resultant temperature at several predefined points based on a previously developed three-dimensional model. To meet the required temperature and to fit the experimentally reported values, the thickness, electrical conductivity, and thermal conductivity of the ITO capping and bottom layers are found to be 5 nm, 103 Ω−1 m−1, 0.84 W m−1 K−1, and 200 nm, 1.25 × 106 Ω−1 m−1, 0.84 W m−1 K−1, respectively. The practicality of using this optimized device to achieve ultrahigh density, ultralow energy consumption, ultrafast switching speed, low interfacial contact resistance, and high thermal reliability has also been demonstrated., Graphical Abstract

In order to solve the problems of multi-source heterogeneous, mass storage, and information sharing of traditional railway signal multi-information location data, based on the analysis of railway big data environment, the architecture of the cloud physics-based information physical fusion system (CPS) was proposed. The service division and hierarchical combination of the architecture were analyzed. Taking the railway signal multiple information train positioning data as an example, a real-time processing method of railway large data stream based on Storm was proposed. Finally, the cloud storage model designed in this paper was compared with the traditional stand-alone architecture. The results showed that this system had a greater advantage in handling large amounts of data. To sum up, the system has practical application value in the processing of multi-information location data of railway signals.

This study showed that there were some changes in the temperature and humidity parameters of wheat grains during the storage year. The grain moisture content in both the near-wall and central parts of the metal silo largely did not change, remaining at a level of 10-11%. Moisture values were recorded monthly, and grain temperature was recorded in accordance with seasonal changes, thus, the range of temperature changes was from 20 to 32°С at a minimum outdoor temperature of 5°С. The moisture content of the grain in the surface layer increased by 0.4-1.2% and the final moisture content of the grain was 11.6%. Experiments on grain temperature and humidity changes with active ventilation in large-capacity metal silos have shown that the rate of change (decrease) in temperature depends on the specific air flow rate, and the difference in air and grain temperature. Experimental storage showed that a grain with the moisture content up to 13.6% can be stored for up to nine months without deterioration in quality. A longer shelf life is possible for wheat grains with a moisture content of up to 12%. This article pays special attention to the processes occurring in the under-roof space of large-capacity metal silos and suggests methods for solving this problem. Keywords: long-term storage, active ventilation, metal silos, heat and mass transfer processes

Many techniques on holographic mass storage systems have been developed, which scalar and vector optical data are stored in holographic materials. To realize high data transfer rate, binary SLM such as a ferroelectric liquid crystal SLM and a digital micro-mirror device (DMD). Therefore, methods to increase the recording density using binary data pages are proposed. The principles of the method are verified by numerical analysis and experimentsTwo shot recording for 4-level phase multiplexing is performed by a high-speed binary intensity SLM using a ferroelectric liquid crystal (FLC). Experimental results are presented in terms of recording capacity.

The invention of additive manufacturing (AM) has made technology development interdisciplinary by drawing various fields of knowledge from science and engineering into one technology domain to achieve optimum practical results. In the last three decades, the industrial production environment has changed from no tooling, assembly lines, or supply chains into the classic riotous technology of three-dimensional (3D) printing. The real power of 3D printing lies in the ability to derive new opportunities, products, and services that will change the effectiveness of the products developed in a more significant way. AM plays a crucial role in the emerging Industrial Revolution 4.0 (IR 4.0) for development products in the defense, aerospace, marine, automobile, and other essential mechanical engineering industries for advanced multifunctional and multimaterial systems. AM, or 3D printing, can completely revolutionize the modern manufacturing industry with a considerable cost reduction. AM technology can fabricate highly customized 3D objects where both shape and composition can be tailored along with the material. Here, we try to educate readers on AM’s advantages over traditional methods in saving time and cost. Compared to previous IR technologies, advancements in computing functions and less mass storage costs in AM for IR 4.0 have made extensive data processing of many data less complicated and effortless for modern 3D computer-aided design models with comparatively less time frame.

Micro- and nanotechnology, especially represented by thin film technology, are at the very center of modern day industry. In developed countries as well as in all other regions of our planet and beyond, today, an existence without microsystems is unimaginable. Communication, power distribution, traffic control, medical care, autonomous systems, and integrated fabrication cannot function without ultrafast computing and high-capacity mass storage devices. But the “brain” of every system needs to be “fed” with information. Some information is supplied by a human user, but it constitutes only a microscopic fraction of the total. The utmost quantity is gathered by sensors measuring temperature, pressure, strain, radioactivity, humidity, location, distance, acceleration, etc. In ever more complex systems, the focus is directed at these “feelers” connecting the computer brain with the world outside its box. This chapter intends to offer an insight into the upcoming challenges of sensor development, concentrating on electrical insulation between commonly used machining materials like steel and alloys, and the sensors to be applied. It is the strong belief of the authors that only integrated thin film technology offers the means to meet the future challenges.

At present, the explosive growth of data and the mass storage state have brought many problems such as computational complexity and insufficient computational power to clustering research. The distributed computing platform through load balancing dynamically configures a large number of virtual computing resources, effectively breaking through the bottleneck of time and energy consumption, and embodies its unique advantages in massive data mining. This paper studies the parallel k-means extensively. This article first initializes random sampling and second parallelizes the distance calculation process that provides independence between the data objects to perform cluster analysis in parallel. After the parallel processing of the MapReduce, we use many nodes to calculate distance, which speeds up the efficiency of the algorithm. Finally, the clustering of data objects is parallelized. Results show that our method can provide services efficiently and stably and have good convergence.

The year 1969 was the year humans visited the Moon. It was also the year that domestic US oil production peaked. It was not the end of hydrocarbons, though “peak oil” was being discussed in some quarters. However, the advent of integrated circuits changed everything. Integrated circuits led to mass storage, and microprocessors, the personal computer and the “smartphone,” the shift from analog to digital information with more and more of the devices in use connected to the Internet and capable of “talking to each other.” After the years (1970–1971) computer programs, algorithms and “software” began to become more important than hardware. Indeed, 1969 may, in the future, be regarded as the time when early versions of artificial intelligence (AI) began to take over some major functions of the global economy, if not human existence.

Diese Arbeit beschäftigt sich mit Erdhäusern und deren mögliche Unabhängigkeit gegenüber den verschiedenen Klimazonen aufgrund der Wirkung der umliegenden Erdmassen. Erdmassen verhalten sich aufgrund ihrer Masse anders als herkömmliche Bauteile. Aufgrund ihrer Trägheit kommt es bei ausreichender Schichtdicke zu einer Phasenverschiebung der extremen Temperaturen im Boden. Das bedeutet, dass die kälteste Temperatur der Erdschicht erst Monate später nach der niedrigsten Temperatur der Außenluft auftritt. Diese Phasenverschiebung wirkt sich positiv auf die Heiz und Kühlphasen aus. Darüber hinaus treten aufgrund ihrer große Speicherfähigkeit geringere Extremtemperaturen auf, wodurch der Wärmestrom geringer ist. Die Eignung des Erdhaus-Konzepts für die unterschiedlichen Klimazonen basiert auf einer Analyse der lokalen traditionellen Bauweisen und dem anschließenden Vergleich mit der Erdhausbauweise. This thesis deals with earth houses and their possible independence from the different climatic zones due to the effect of the surrounding earth masses. Earth masses behave differently than conventional components due to their mass. Due to their inertia, a phase shift of the extreme temperatures in the soil occurs when the layer is sufficiently thick. This means that the coldest temperature of the earth's layer occurs months later after the lowest temperature of the outside air. This phase shift has a positive effect on the heating and cooling phases. In addition, due to their large storage capacity, lower extreme temperatures occur, which means that the heat flow is lower. The suitability of the earth house concept for the different climatic zones is based on an analysis of the local traditional construction methods and the subsequent comparison with earth house construction.

2021 IFIP/IEEE 29th International Conference on Very Large Scale Integration (VLSI-SoC), Singapour, 4-7 Oct. 2021; International audience; Phase change memory (PCM) device associated with Ovonic Threshold Switch (OTS) selector is a proven solution to fill the gap between DRAM and mass storage. This technology also has the potential to be embedded in a high-end microcontroller. However, programming and reading phases efficiency is directly linked to the selector's leakage current and the sneak-path management. To tackle this challenge, we propose in this paper, a new sense amplifier able to generate an auto-reference taking into account leakage current of unselected cell, including a regulation loop to compensate voltage drop due to reading current sensing. This auto-referenced sense, built on the charge-sharing principle, is designed on a 28nm FDSOI technology and validated through extensive Monte-Carlo and corner cases simulations. From the simulation results, our sense amplifier is demonstrated to be robust for an ultra-large range of sneak-path current and consequently for a large range of memory array size, suitable for embedded memory in high-end microcontroller.

The demand for mass storage devices has become an inevitable consequence of the explosive increase in data volume. The three-dimensional (3D) vertical NAND (V-NAND) and quad-level cell (QLC) technologies rapidly accelerate the capacity increase of flash memory based storage system, such as SSDs (Solid State Drives). Massive capacity SSDs adopt dozens or hundreds of flash memory chips in order to implement large capacity storage. However, employing such a large number of flash chips increases the error rate in SSDs. A RAID-like technique inside an SSD has been used in a variety of commercial products, along with various studies, in order to protect user data. With the advent of new types of massive storage devices, studies on the design of RAID-like protection techniques for such huge capacity SSDs are important and essential. In this paper, we propose a massive SSD-Aware Parity Logging (mSAPL) scheme that protects against n-failures at the same time in a stripe, where n is protection strength that is specified by the user. The proposed technique allows for us to choose the strength of protection for user data. We implemented mSAPL on a trace-based simulator and evaluated it with real-world I/O workload traces. In addition, we quantitatively analyze the error rates of a flash based SSD for different RAID-like configurations with analytic models. We show that mSAPL outperforms the state-of-the-art RAID-like technique in the performance and reliability.

Bare Machine Computing (BMC) is a paradigm used in programming applications to run on a Bare Machine. It consists of a CPU, Memory, and I/O without an Operating System and resident mass storage. It utilizes an Application Development model software that interfaces directly with the hardware. It also has potential as a powerful teaching and research tool in undergraduate STEM programs, notably Computer Engineering and Computer Science. Before the COVID-19 Pandemic, researchers used the University lab environment, and Bare Systems connected via LAN/WAN. The Pandemic restrictions put members of the research team in different locations. Hence, the researchers adopted a Remote Collaboration model of Concurrent Participation, Communication, and Development for Bare Machine to continue this research. This paper discusses the advantages and disadvantages of moving the BMC research entirely online and measures needed to address the Configuration of BMC Development Environment, Communication, Collaboration, and Diverse Skill Set. The paper covers online technical research because most literature concentrates on only online survey research's benefits and drawbacks. This paper also addresses BMC application in presenting STEM subjects to students, mainly undergraduate students. Finally, the paper includes remote research that fulfills the Department of Education (DOE) requirements of student access.

Facing the challenges of global energy resources, environmental pollution and so on, Large-scale development and utilization of clean energy is imperative. Clean energy has a strong intermittent characteristics, The simulation analysis of the faults and the recovery process of this kind of equipment also need to be carried out in large numbers. In order to meet the large-scale asymmetric fault in intermittent power generation equipment recovery curve simulation results of the process data storage requirements, the development of a rapid retrieval simulation curve library a massive data oriented, successfully applied to the simulation results of the process of data storage.This paper studies the data preprocessing, data compression, data indexing technology, efficient memory database technology, the real-time memory database of mass storage data of historical documents in the library data cache to efficient operation, so as to realize the rapid retrieval simulation curve database for massive data.

Advances in microscopy technologies and techniques are driving development of an integrated cyberinfrastructure to manage the vast amounts of image data being generated. To address this need, a team of neuroscientists and cyberinfrastructure engineers has integrated mass storage, networking, and high-performance computing components to create the Brain Image Library (BIL). BIL serves the neuroscience community by providing a persistent repository for the massive amounts of data being generated (multi-petabyte scale) and by offering brain researchers supercomputing-class processing and visualization capabilities for working with high-resolution brain image datasets.

Probe-based storage memories are considered one of the most promising solutions to address the mass storage issues in the near future. However, data size arising from conventional probe memories is usually larger than probe size due to the thermal diffusion effect. To eliminate such thermal interference and make data dimension fully dominated by probe dimension, we proposed a concept of carbon-based resistive probe memory and developed a comprehensive computational model to predict its write, rewrite and readout performances governed by electro-thermal and mass concentration processes. The physical reality of such a theoretical model was demonstrated through the good agreement between the calculated and experimental measured threshold voltages for different layered thickness. The data bit of carbon-based resistive probe memory, considered as the sp2 filament inside sp3 background, is formed completely underneath the tip edge due to the localized electric field induced here. This makes the bit size fully determined by the probe tip dimension and allows for the achievement of ultra-high density using an ultra-small probe tip with low energy consumption. Such a conductive filament can be also rewritten back to its pristine sp3 state at relatively high temperature (~250 °C) and detected by sensing the device reading contrast (~1). The designed carbon-based resistive probe memory can retain its bit completeness even if we reduce the bit pitch to 28 nm for a probe size of 25 nm, exhibiting a superior immunity to thermal cross-talk effect. It, however, induces strong readout cross-talk, which is revealed from the resistance image of the multiple bit pattern. This adversely reduces the achievable recording density due to the required large bit pitch, which can be alleviated using either a very sharp tip apex or the optical readout scheme.

The continuous and rapid evolution in the field of computing, and in particular in the field of storage devices, has led to the obsolescence of optical discs in favour of mass storage devices. In that sense, a large number of CDs and DVDs become obsolete each day in the world. In trying to create a recovery solution for those pieces, research in which polycarbonate (PC) waste from recycled discs have been used to develop new gypsum coating materials and products has been conducted. In a previous study, the physical and mechanical properties of new gypsum plasters, with PC waste as aggregate, were studied. Following that study, this article aims at creating new gypsum plaster false ceiling plates, using CD and DVD residues in different scenarios: as crushed aggregate in the gypsum matrix, as full reinforcement pieces of the plates and as a combination of both. The mechanical behaviour and the thermal conductivity of the new pieces have been analysed in this paper. The results showed an important improvement in the mechanical and thermal properties of the plates when the PC waste was used in many scenarios.

A file system defines how a computer’s data is stored on and retrieved from a mass storage device. Without a file system, the information on a mass storage device would be an accumulation of unorganized and non-retrievable data. The files in a file system are typically arranged into a set of hierarchically organized directories (a.k.a., folders) and subdirectories (a.k.a., subfolders). Among other things, a file system permits a computer’s operating system to

In recent years, Big Data Analytics is used for the specification of a large amount of data to uncover or extract the information such as the hidden data. This allows the user or developer to utilize the large chunk or data in order to extract the correlations and patterns which may be present inside the large unstructured chunk of data. The term, Big Data was initially coined in the mid-1990s due to the seemingly increased volumes of data which were often stored in hardware devices, up until we obtained a permanent solution to the excess amount of storage space we know today as Cloud Computing. Cloud Computing, known as the phenomenon which involves mass storage of data and information among a certain entity which hosts no hardware, i.e. stored in an imaginary circumstance termed as ‘cloud’, has deemed beneficial to the Technology surrounding us and enabled an immense advantage when it comes to artificial storage. Over the years, there have been various technological improvements and studies surrounding this phenomenon in which this Technology is deemed to be present among almost every hardware component in the near future. In this paper we are going to view some of the advancements and achievements this technology has brought in our rapidly growing technological world.

Memory acquisition is a tool used in advanced forensics and malware analysis. Various methods of memory acquisition exist. Such solutions are ranging from tools based on dedicated hardware to software-only solutions. We proposed a hypervisor based memory acquisition tool. [22]. Our method supports ASLR and Modern operating systems which is an innovation compared to past methods [27, 36]. We extend the hypervisor assisted memory acquisition by adding mass storage device honeypots for the malware to cross and propose hiding the hypervisor using bluepill technology.

With the increasing demand for mass storage, research on exa-scale storage is actively underway. When the scale of storage grows to the exa-scale, the space efficiency becomes very important. To maintain the storage reliability and improve the space efficiency, we have begun to introduce erasure coding instead of replication. However, erasure coding has many I/O performance degradation factors such as Parity Calculation, degraded I/O, Data Distribution cost, etc., whereas the existing research mainly focuses on improving the performance of the Parity Calculation.In this study, we identified the issues and bottlenecks of using erasure coding in real storage. First, we measured the I/O performance of various erasure codes to find the suitable erasure codes for real storage. Next, we analyzed the execution time for each processing step when I/O was performed and the issues when erasure coding was used in storage. Finally, we predicted the cost of EC-based I/O processing in the exa-scale storage and identified the expected problems.

The ability to accurately predict the CO2 storage resource in saline formations is important to make high-level, energy-related government policy and business decisions. CO2-SCREEN (Storage prospeCtive Resource Estimation Excel aNalysis) is a tool developed by the United States Department of Energy − National Energy Technology Laboratory (US-DOE-NETL) to screen saline formations for prospective CO2 storage resources. CO2-SCREEN uses DOE methods and equations to serve as a consistent mechanism for calculating prospective CO2 storage resources. CO2-SCREEN is comprised of two files: an Excel file used for inputs and outputs and a GoldSim Player file used to run Monte Carlo simulations. CO2-SCREEN requires input of physical geologic parameters (i.e. thickness, porosity) as well as efficiency factor ranges (i.e. net-to-gross thickness) to calculate a mass storage estimate. An application of CO2-SCREEN is demonstrated here using well log data from the Oriskany Sandstone portion in Pennsylvania. The Oriskany Sandstone is divided into 20 km x 20 km grid cells in which 151 cells contain well log data. CO2-SCREEN calculates prospective CO2 storage resource for each grid cell based on the well log data and uses lithology and depositional environment information for efficiency factor ranges. The Oriskany Sandstone CO2 storage resource estimate for Pennsylvania, calculated by CO2-SCREEN, ranges from 0.07 to 1.28 gigatons (Gt) with a P50 value of 0.32 Gt. This resource assessment analysis is done to demonstrate the use of CO2-SCREEN and results are comparable to previous studies which encourages the application of CO2-SCREEN to other saline formations and warrants exploring the expansion of this tool to assess the CO2 storage resource in other formations such as shale and depleted oil and gas reservoirs.

A USB mass storage device yields a lot of artifacts when connected to a system. These artifacts are persistent in nature and are retained even after the system has been shut down and the information they contain may assist in carrying out forensic analysis on a suspect system. In this paper, we demonstrate how Windows Event Viewer can be used to find forensic artifacts in a suspect system for investigative purposes. We also discuss the potential that Windows registry holds to identify USB devices&rsquo, information that have been connected to the system, to corroborate our findings from Windows Event Viewer. Finally, we use the Windows 10 file system to extract log details that contain the setup information of a USB device that was connected to the system the very first time, and obtain the necessary identifiers and time stamp details.

Since 2018 several FAIR Phase 0 beamtimes have been operated at GSI, Darmstadt. Here the new challenging technologies for the upcoming FAIR facility shall be tested while various physics experiments are performed with the existing GSI accelerators. One of these challenges concerns the performance, reliability, and scalability of the experiment data storage. A new system for archiving the data from the GSI and FAIR Phase 0 experiments to long-term storage has been developed in the last years and was successfully employed in the 2019 spring beamtime. Raw data as collected by event building software of large scale detector data acquisition has to be safely written to a mass storage system like a magnetic tape library. Besides this long term archive, it is often required to process this data as soon as possible on a high performance compute farm. A full near-online analysis is essential to give a fast feedback on the quality of the data acquired, allowing to improve detector and measurement parameters such as alignment, calibration, high voltage and electronics set-up, etc. The C library LTSM ("Lightweight Tivoli Storage Management") has been developed at GSI IT department based on the IBM TSM software. It provides a file API that allows to write raw listmode data files via TCP/IP sockets directly to an IBM TSM storage server. Moreover, the LTSM library offers Lustre HSM ("Hierarchical Storage Management") capabilities for seamlessly archiving and retrieving data stored on Lustre file system and TSM server. That is, data can be automatically archived to low-cost storage media such as magnetic tapes and seamlessly retrieved when accessing the data on the Lustre file system. In spring 2019 LTSM has been employed at the FAIR Phase 0 beamtimes at GSI. For the HADES experiment LTSM was implemented into the DABC ("Data Acquisition Backbone Core") event building software. During the 4 weeks of Ag+Ag@1.58 AGeV beam, the HADES event builders have transferred about 400 TB data via 8 parallel 10 GbE sockets, both to the TSM archive and to the "GSI green cube" HPC farm. For other FAIR Phase 0 experiments using the vintage MBS ("Multi Branch System") event builders, an LTSM gateway application has been developed to connect the legacy RFIO ("Remote File I/O") protocol of these DAQ systems with the new storage interface. In this contribution the novel LTSM mass storage architecture and its applications for experiment data acquisition will be described. Experiences and storage performance measurements from HADES at FAIR Phase 0 campaign will be deeply discussed. Most recent further developments and an outlook on future enhancements will be presented.

Universal serial bus mass storage is a widely used storage device. In order to protect the user data security in USB storage devices, an effective authentication and data protection scheme is proposed. Using the attribute-based control technology, the security authentication of the USB device user is realized, and the privacy data fine-grained control of the USB device is realized. Security analysis shows that the scheme has strong security, it can resist replay attack, denial of service attack, the online password guessing attack, user impersonation attack, etc. Experimental performance analysis shows that the scheme has high efficiency in user registration, authentication and file decryption.

This article proposes a new phase change memory– (PCM) based memory storage architecture with associated self-adaptive data filtering for various embedded devices to support energy efficiency as well as high computing power. In this approach, PCM-based memory storage can be used as working memory and mass storage layers simultaneously, and a self-adaptive data filtering module composed of small DRAM dual buffers was designed to improve unfavorable PCM features, such as asymmetric read/write access latencies and limited endurance and enhance spatial/temporal localities. In particular, the self-adaptive data filtering algorithm enhances data reusability by screening potentially high reusable data and predicting adequate lifetime of those data depending on current victim time decision value. We also propose the possibility that a small amount of DRAM buffer is embedded into mobile processors, keeping this as small as possible for cost effectiveness and energy efficiency. Experimental results show that by exploiting a small amount of DRAM space for dual buffers and using the self-adaptive filtering algorithm to manage them, the proposed system can reduce execution time by a factor of 1.9 compared to the unified conventional model with same the DRAM capacity and can be considered comparable to 1.5× DRAM capacity.

This article discusses the transient behavior of a supercritical CO2 recuperative Brayton cycle, which, in addition to standard components, includes heat and mass storage systems. The cycle's time dependent behavior is promoted by enforcing a temperature profile on the heat source, which mimics that of a hybrid power plant using an idealized solar radiation flux on top of a baseline energy input. The finite volume code developed allows the spatial and temporal discretization of key components of the cycle. The simulations show that the thermal inertial effects are critical and capable of drastically changing the cycles' power delivery. More specifically, the analysis shows that the overall system might need several days to reach a periodic representative operational pattern, suggesting that the commonly used steady state and quasi-steady state hypotheses must be carefully considered if the cycle is assisted by a heat storage. Also, the results indicate that there is a compromise between the dimensions of the heat storage and its medium's thermophysical properties. Finally, the calculations show that, given a proper control strategy for the heat storage's charging and discharging, its use can significantly extend the cycle's power output delivery, allowing a better fitting to the demand profile.

Racetrack memory (RM) has demonstrated great potential as nonvolatile mass storage in future advanced computer architectures. Domain wall (DW)-based RM first proposed in 2008 by IBM, however, suffers from challenges, such as storage density, scalability, and energy consumption. Recently, magnetic skyrmions, topologically protected particle-like spin textures, have expected to replace DWs as new information carriers in the RM design, owing to their superiorities to DWs in terms of topological stability, smaller size, as well as lower driving current density. Extensive investigations have been performed in skyrmion-based RM (Sky-RM) to date. Furthermore, skyrmions exhibits some unique properties that are inaccessible to DWs, thus enabling Sky-RM to explore some new functions that may be inaccessible to DW-RM. In this paper, a novel Sky-RM, capable of random information update/deletion/insertion, is proposed by exploiting the particle-like behaviors of skyrmions. Micromagnetic studies are performed to validate the function and performance of these novel data operations, which may bring performance benefits in data access operations and enable new applications.

The megatrends and Industry 4.0 in ICT (Information Communication & Technology) are concentrated in IoT (Internet of Things), BigData, CPS (Cyber Physical System), and AI (Artificial Intelligence). These megatrends do not operate independently, and mass storage technology is essential as large computing technology is needed in the background to support them. In order to evaluate the performance of high-capacity storage based on open source Ceph, we carry out the network performance test of Abyss storage with domestic and overseas sites using KOREN (Korea Advanced Research Network). And storage media and network bonding are tested to evaluate the performance of the storage itself. Additionally, the security test is demonstrated by Cuckoo sandbox and Yara malware detection among Abyss storage cluster and oversea sites. Lastly, we have proposed the draft design of Data Lake framework in order to solve garbage dump problem.