Mass Storage System Research Articles

WIRELESS CHARGING OF BATTERY

In reaction to the depletion of natural resources, electric vehicles offer a viable alternative. Practical and dependable methods to charge EV batteries are crucial in order to boost the usage of EVs in daily life, and wireless power transfer (WPT) is being investigated as a solution to charge batteries. In this project, a wireless charger prototype system is built and implemented. The necessity for a cable and plug charger, galvanic separation of the onboard electronics, weight, and cost of this charger, and massive energy storage system (ESS) packs are all present in today's electric vehicles. This paper has designed and developed an antenna system suitable for vehicles using resonant magnetic coupled wireless power transfer technology to an electric vehicle charging system. The use of WPT in EVs provides a clean, convenient and safe operation. At the core of the WPT systems are two coils namely primary and secondary. For the safe and efficient transfer of energy the rated power, both sides have to be tuned by resonant capacitors. The selection of operating frequency is a key criterion for all applications as it affects the size and dimensions of the coils and the selection of the components for the power electronic circuit. Resonant wireless transmission systems for vehicle charging technology are being developed. Keywords— Wireless power transmission(WPT)

Medical Record Encryption Storage System Based on Internet of Things

The Internet of Things takes data as the center, and its core is data storage and management. With the emergence and rapid development of wireless communication technology, with the huge number of terminals in human society, massive data will be generated. Undoubtedly, data storage and management technology will attract much attention. In view of this, this paper proposes a data storage scheme based on the Internet of Things. This paper introduces the Internet of Things technology, designs it from the perspective of the massive data storage system of the Internet of Things, realizes the intelligent processing of data storage, and provides security guarantee for information services. By combing the business process management of doctors, nurses and patients, this paper constructs a medical record encryption management system, makes a comparative analysis before and after the system goes online, and carries out simulation experiments. The simulation results show that (1) the cost of paper is significantly reduced, and the related forms of medical records are more unified and standard, (2) medical record inquiry and reading are more convenient and controllable, and (3) the safety of medical records is well guaranteed. Except that the relevant doctors and nurses of patients can view the relevant medical records, and others have no authority to query and access them. Therefore, the encrypted medical record storage system based on Internet of Things technology can effectively solve the collection, statistics, and integration of patient treatment information, which can be summarized into a unified, shared, and interconnected electronic medical record management system to realize the collection of patient treatment information in the whole process.

Research on data load balancing technology of massive storage systems for wearable devices

Because of the limited memory of the increasing amount of information in current wearable devices, the processing capacity of the servers in the storage system can not keep up with the speed of information growth, resulting in low load balancing, long load balancing time and data processing delay. Therefore, a data load balancing technology is applied to the massive storage systems of wearable devices in this paper. We first analyze the object-oriented load balancing method, and formally describe the dynamic load balancing issues, taking the load balancing as a mapping problem. Then, the task of assigning each data node and the request of the corresponding data node’s actual processing capacity are completed. Different data is allocated to the corresponding data storage node to complete the calculation of the comprehensive weight of the data storage node. According to the load information of each data storage node collected by the scheduler in the storage system, the load weight of the current data storage node is calculated and distributed. The data load balancing of the massive storage system for wearable devices is realized. The experimental results show that the average time of load balancing using this method is 1.75 ​h, which is much lower than the traditional methods. The results show the data load balancing technology of the massive storage system of wearable devices has the advantages of short data load balancing time, high load balancing, strong data processing capability, short processing time and obvious application.

Experimental investigation of demand response potential of buildings: Combined passive thermal mass and active storage

Heating, ventilation, and air conditioning (HVAC) systems, combined with the internal thermal mass of buildings, have been deemed to be promising means of providing demand response (DR) resources, particularly for buildings with active energy storage systems. DR resources, such as peak-load reduction potential, can provide grid-responsive support resulting in a high degree of grid involvement and high flexible electricity demand. In the DR field, the potential of HVAC load flexibility has been considered in buildings. In the future smart buildings, it is important to take advantage of demand-side resources to achieve real-time energy supply–demand balance sustainably. In this context, DR potential and characteristics of buildings play a pivotal role in DR programs. However, few studies have investigated the internal thermal mass’s heat release and DR characteristics of buildings. Thus, a systematic experiment is conducted to study the DR potential and characteristics of internal thermal mass and active storage systems. The DR resources include the passive cooling storage from furniture, building envelope and an active water storage tank. Two DR control strategies, including pre-cooling and temperature resetting, are analyzed in this study. The experimental results show that the strategies are effective for short-term (0.5 h) and intermediate-term (2 h) DR programs. For a long-term DR program, active energy storage technology such as a water storage tank is required to satisfy the occupant's comfort requirements. Hence, we conclude that passive thermal mass and active storage systems should be simultaneously considered in practical DR programs for better DR implementation.

Interleaved Write Scheme for Improving Sequential Write Throughput of Multi-Chip MLC NAND Flash Memory Systems

Mass-storage systems made of multi-level cell (MLC) NAND flash memory are cost effective but suffer from limited sequential write throughput. Although conventional interleaved write scheme helps, the unique characteristic of the MLC that the write time of a least significant bit (LSB) is much shorter than that of a most significant bit (MSB) leaves performance improvement headroom. This article presents an interleaved write scheme for improving the sequential write throughput of the multi-chip MLC NAND flash memory system. It leverages the longer write time of the upper pages to transmit more data by reordering the interleaved write sequence of the MLC chips. The proposed scheme can be directly implemented in the firmware of the flash memory controller without conflicting with existing flash translation layer (FTL) routines. No hardware modification is needed. The design criteria and performance improvements of general MLC NAND flash storage systems are derived for optimizing the system’s performance. Experimental results of an example single-channel 4-chip solid-state drives (SSD) system showed the sequential write throughput was improved by over 11.4%. The proposed interleaved write scheme can be applied to multi-channel storage systems to improve their sequential write throughput as well.

Relieving Grid by Adding PV and BESS for Economical Charging of EV in the Charging Station

Being fueled by electric power, electric vehicles (EVs) are the sustainable alternatives to the conventional vehicles: EVs are likely to alleviate the environmental pollution brought out by excessive use of fossil fuels. To realize electric locomotion, there should be efficient charging facility in our electrical infrastructure to charge the batteries of the EVs. This work proposes an effective topology that focuses to reduce the stress on the grid due to overlapping of EV load profile with the normal Grid-electricity load profile in technically as well as financially feasible way. The EV’s owner can charge his/her vehicle up to desired SOC level from the charging station with sources: PV, BESS and Grid. Here, BESS is a massive energy storage system that can store energy from the grid as well as from the PV system which supplies power to the load during day-time. BESS supplies the load during the peak of the system and helps the grid relieve as well as reduce the Grid-electricity bills during peak hours. Regulation of EV load sharing and prevention of mismatch between circulating currents supplied by power sources is implemented using fixed droop method. The trend of power demand of EVs throughout a day in a charging station is assumed in accordance with the other related works. The economic feasibility of the proposed system is verified in terms of the payback period of the investment made on the PV and BESS. The simulations are successfully implemented to validate the effectiveness of the system and to demonstrate the load management.

Mass storage interface LTSM for FAIR Phase 0 data acquisition

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. 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. The C library LTSM (“Lightweight Tivoli Storage Management”) has been developed at the GSI IT department based on the IBM TSM software. It provides a file API that allows for writing 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. 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 of 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.

On the Complexity and Performance of the Information Dispersal Algorithm

The Information Dispersal Algorithm (IDA) has become a key component in several fault-tolerant massive storage systems. From a theoretical point of view, it is a linear transformation over a finite field on the vectors that make up a given file. Direct transformation adds redundancy, splitting the initial file into a new set of files called dispersals. The inverse transformation recovers the original file from a subset of dispersals. This piece of research demonstrates the impact of input and output (I/O) operations on direct and inverse transformations. Different alternatives to control the exchange of elements between RAM and disk were evaluated, which is the key operation to build a vector in memory and store its entries in a file. First, the impact of the working finite field was tested; second, the impact of the use of a buffer for exchange between the RAM and the hard disk, and finally, several instances of the algorithm with which to evaluate the impact of parallelism were simultaneously deployed. The results demonstrate that the combination of these factors may have an important effect on the speed of both direct and inverse procedures.

La autenticación y verificación de la identidad a través de información biométrica como paradigma del tratamiento de datos personales en México

El rápido progreso de las tecnologías biométricas y su aplicación generalizada en el sistema financiero mexicano, precisan de un estudio pormenorizado desde el punto de vista de la protección de datos personales. Dado que los datos biométricos han sido incluidos de manera incipiente en la normativa mexicana, en el presente artículo, se analiza su régimen jurídico desde el contexto europeo, abordándose además, las ventajas e inconvenientes que puede suponer la implantación de sistemas de almacenamiento masivo de información biométrica, a la luz de los derechos fundamentales de los individuos. Finalmente, apuntaré posibles soluciones que supongan una menor intrusión contra los derechos de los usuarios y clientes de las instituciones financieras.

An Efficient Secret Sharing-based Storage System for Cloud-based Internet of Things

Internet of things (IoTs) is the newfound information architecture based on the internet that develops interactions between objects and services in a secure and reliable environment. As the availability of many smart devices rises, secure and scalable mass storage systems for aggregate data is required in IoTs applications. In this paper, we propose a new method for storing aggregate data in IoTs by the use of -threshold secret sharing scheme in the cloud storage. In this method, original data is divided into ‎ blocks ‎that ‎each ‎block ‎is ‎considered ‎as a ‎share. The edge server does not send these shares (blocks) directly (through the secure channel) to cloud service providers ( s). Rather, the edge server hides the shares (blocks) with XORing two secret values and publishes the result. Indeed, with this method, none of s has an amount of block information.‎This scheme is also verifiable, i.e., in the verification phase, each can verify its quasi-share. Moreover, before data retrieval, the edge server checks the correctness of provided quasi-share from s of an authorized group. Also, the proposed scheme is scalable, since new data can be inserted or part of the original data can be deleted, without changing shares. It is worth noting that the proposed scheme is more efficient compared with the other scheme since heavy and complex computation is not required.

Best Practices in Accessing Tape-Resident Data in HPSS*

Tape is an excellent choice for archival storage because of the capacity, cost per GB and long retention intervals, but its main drawback is the slow access time due to the nature of sequential medium. Modern enterprise tape drives now support Recommended Access Ordering (RAO), which is designed to reduce data recall/retrieval times. BNL SDCC's mass storage system currently holds more than 100 PB of data on tapes, managed by HPSS. Starting with HPSS version 7.5.1, a new feature called “Tape Order Recall (TOR) has been introduced. It supports both RAO and non-RAO drives. The file access performance can be increased by 30% to 60% over the random file access. Prior to HPSS 7.5.1, we have been using an in-house developed scheduling software, aka ERADAT. ERADAT accesses files based on the file logical position order. It has demonstrated a great performance over the past decade long usage in BNL. In this paper we will present a series of test results, compare TOR and ERADAT's performance under different configurations to show how effective TOR (RAO) and ERADAT perform and what is the best solution in data recall from SDCC's tape storage

HSM and backup services at INFN-CNAF

IBM Spectrum Protect (ISP) software, one of the leader solutions in data protection, contributes to the data management infrastructure operated at CNAF, the central computing and storage facility of INFN (Istituto Nazionale di Fisica Nucleare – Italian National Institute for Nuclear Physics). It is used to manage about 55 Petabytes of scientific data produced by LHC (Large Hadron Collider at CERN) and other experiments in which INFN is involved, stored on tape resources as the highest latency storage tier within HSM (Hierarchical Space Management) environment. To accomplish this task, ISP works together with IBM Spectrum Scale (formerly GPFS - General Parallel File System) and GEMSS (Grid Enabled Mass Storage System), an in-house developed software layer that manages migration and recall queues. Moreover, we perform backup/archive operation of main IT services running at CNAF, such as mail servers, configurations, repositories, documents, logs, etc. In this paper we present the current configuration of the HSM infrastructure and the backup and recovery service, with particular attention to issues related to the increasing amount of scientific data to manage, expected for the next years.

Workload Scheduling for Massive Storage Systems with Arbitrary Renewable Supply

As datacenters grow in scale, increasing energy costs and carbon emissions have led data centers to seek renewable energy, such as wind and solar energy. However, tackling the challenges associated with the intermittency and variability of renewable energy is difficult. This paper proposes a scheme called GreenMatch, which deploys an SSD cache to match green energy supplies with a time-shifting workload schedule while maintaining low latency for online data-intensive services. With the SSD cache, the process for a latency-sensitive request to access a disk is divided into two stages: a low-energy/low-latency online stage and a high-energy/high-latency off-line stage. As the process in the latter stage is off-line, it offers opportunities for time-shifting workload scheduling in response to variations of green energy supplies. We also allocate an HDD cache to guarantee data availability when renewable energy is inadequate. Furthermore, we design a novel replacement policy called Inactive P-disk First for the HDD cache to avoid inactive disk accesses. The experimental results show that GreenMatch can make full use of renewable energy while minimizing the negative impacts of intermittency and variability on performance and availability.

Solar Redox Flow Batteries: Mechanism, Design, and Measurement

AbstractThe increasing public awareness of the energy crisis since the 1970s has promoted the ongoing development of energy conversion and storage systems. As a supplement to photovoltaics, photoelectrochemical cells (PECs) are among the promising solar electricity generation systems. However, the intrinsic intermittence of sunlight can never guarantee continuous electricity supply. Therefore, PECs are being developed to convert solar energy to chemical energy in the forms of fuels such as H2 and other organic chemicals. However, this technology requires massive storage systems for the solar fuels/chemicals, and complementary conversion systems for electricity generation from the solar fuels. Redox flow batteries (RFBs) are capable of large‐scale real‐time electricity storage and conversion. Both PECs and RFBs have been investigated for more than three decades, yet the integration of these two systems has not reached maturity. Hence, this review aims to give a critical overview of the state‐of‐the‐art progress in solar redox flow batteries, from the aspects of the working mechanism, device engineering, and performance evaluation.

Transient analysis and optimization of a recuperative sCO2 Brayton cycle assisted by heat and mass storage systems

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.

The Management Strategy of Metadata in Large-scale Network Storage System

The wan Internet storage system based on Distributed Hash Table uses fully distributed data and metadata management, and constructs an extensible and efficient mass storage system for the application based on Internet. However, such systems work in highly dynamic environments, and the frequent entry and exit of nodes will lead to huge communication costs. Therefore, this paper proposes a new hierarchical metadata routing management mechanism based on DHT, which makes full use of the node stabilization point to reduce the maintenance overhead of the overlay. Analysis shows that the algorithm can effectively improve efficiency and enhance stability.

Introduction to the Special Issue on Massive Storage Systems and Technology 2017

Introduction to the Special Issue on Massive Storage Systems and Technology 2017

A Modeling Language for MapReduce Programing in a Storage System Perspective

MapReduce is a powerful distributed data analysis programming model. It runs on big data storage systems and processes data in a parallel way. An appropriate way to ensure the correctness of MapReduce programs is formal method analysis, which requires firstly a formal model of MapReduce. In this paper we propose a modeling language to establish the formal model of the MapReduce framework. Unlike other approaches, our language describes the processing of data in the MapReduce programs from a perspective of underlying files and blocks, so that the details of data processing can be clearly demonstrated. The language is based on our previous work, a language describing the management of massive data storage systems, with extensions from two aspects: block content data refinement and concurrency support. Based on our language, the features of the MapReduce programming model can be discussed.

Efficient Access to Massive Amounts of Tape-Resident Data

Randomly restoring files from tapes degrades the read performance primarily due to frequent tape mounts. The high latency and time-consuming tape mount and dismount is a major issue when accessing massive amounts of data from tape storage. BNL’s mass storage system currently holds more than 80 PB of data on tapes, managed by HPSS. To restore files from HPSS, we make use of a scheduler software, called ERADAT. This scheduler system was originally based on code from Oak Ridge National Lab, developed in the early 2000s. After some major modifications and enhancements, ERADAT now provides advanced HPSS resource management, priority queuing, resource sharing, web-browser visibility of real-time staging activities and advanced real-time statistics and graphs. ERADAT is also integrated with ACSLS and HPSS for near real-time mount statistics and resource control in HPSS. ERADAT is also the interface between HPSS and other applications such as the locally developed Data Carousel, providing fair resource-sharing policies and related capabilities. ERADAT has demonstrated great performance at BNL.

Design and evaluation of a hybrid storage system in HEP environment

Nowadays, the High Energy Physics experiments produce a large amount of data. These data are stored in mass storage systems which need to balance the cost, performance and manageability. In this paper, a hybrid storage system including SSDs (Solid-state Drive) and HDDs (Hard Disk Drive) is designed to accelerate data analysis and maintain a low cost. The performance of accessing files is a decisive factor for the HEP computing system. A new deployment model of Hybrid Storage System in High Energy Physics is proposed which is proved to have higher I/O performance. The detailed evaluation methods and the evaluations about SSD/HDD ratio, and the size of the logic block are also given. In all evaluations, sequential-read, sequential-write, random-read and random-write are all tested to get the comprehensive results. The results show the Hybrid Storage System has good performance in some fields such as accessing big files in HEP.