FPGA-Based inline encryption bridge using AES-XTS for storage systems

Airflow simulation and inlet pressure profile optimization of a grain storage bin aeration system

Incentive programs and ongoing reduction in costs are driving joint installation of solar PV panels and storage systems in residential households. There is a need for optimal investment decisions to reduce the electricity consumption costs of the households further. In this paper, we first develop analytical expression of storage investment decision and then of solar investment decision for a household which is under net metering billing mechanism with time of use pricing condition. Using real data of a residential household in Austin, TX, USA, we study how the investment decisions would provide benefit for a period of one year. Results show significant profit when using storage devices and solar panels optimally for the system. It is important to note that though our approach can help significantly to take investment decisions, the solution will still be sub-optimal for somebody who needs optimal investment jointly on both storage and solar systems.

Currently the QoS requirements for storage systems are usually presented in the form of service-level agreement (SLA) to bound I/O measures such as latency and throughput of I/O requests. However, SLA is not an effective performance interface for users to specify their required I/O service quality for two major reasons. First, for users it is difficult to determine appropriate latency and throughput bounds to ensure their required application performance without resource over-provisioning. Second, for storage system administrators it is a challenge to estimate a user’s real resource demand because the specified SLA measures are not consistently correlated with the user’s resource demand. This makes resource provisioning and scheduling less informative and can greatly reduce system efficiency. We propose the concept of reference storage system (RSS), which can be a storage system chosen by users and whose performance can be measured offline and mimicked online, as a performance interface between applications and storage servers. By designating an RSS to represent I/O performance requirement, a user can expect the performance received from a shared storage server servicing his I/O workload is not worse than the performance received from the RSS servicing the same workload. The storage system is responsible for implementing the RSS interface. The key enabling techniques are a machine learning model that derives request-specific performance requirements and an RSS-centric scheduling that efficiently allocates resource among requests from different users. The proposed scheme, named as YouChoose , supports the user-chosen performance interface through efficiently implementing and migrating virtual storage devices in a host storage system. Our evaluation based on trace-driven simulations shows that YouChoose can precisely implement the RSS performance interface, achieve a strong performance assurance and isolation, and improve the efficiency of a consolidated storage system consisting of different types of storage devices.

Overheating of Li-ion cells and battery packs is an ongoing technological challenge for electrochemical energy conversion and storage, including in electric vehicles. Immersion cooling is a promising thermal management technique to address these challenges. This work presents experimental and theoretical analysis of the thermal and electrochemical impact of immersion cooling of a small module of Li-ion cells. Significant reduction in both surface and core temperature due to immersion cooling is observed, consistent with theoretical and simulation models developed here. However, immersion cooling is also found to result in a small but non-negligible increase in capacity fade of the cells. A number of hypotheses are formed and systematically tested through a comparison of experimental measurements with theoretical modeling and simulations. Electrochemical Impedance Spectroscopy measurements indicate that the accelerated cell aging due to immersion cooling is likely to be due to enhanced lithium plating. Therefore, careful consideration of the impact of immersion cooling on long-term performance may be necessary. The results presented in this work quantify both thermal and electrochemical impacts of a promising thermal management technique for Li-ion cells. These results may be of relevance for design and optimization of electrochemical energy conversion and storage systems.

Economic prospects for the application of new electric energy storage devices

—rigid or hard magnetic disks; —parallel disk arrays; —optical disks, which have several variants: read-only [such as CD-ROM and digital video disk (DVD)], write-once (WORM), and rewritable (magnetooptical or phase change); —magnetic tape, such as 4mm (DAT), 8mm, and digital linear tape (DLT); —autochangers, which combine storage devices with racks of tape cartridges or optical disk platters that can be moved to and from the drives by robotics. —Complete storage systems also include software to manage and orchestrate the storage components. Such software includes management and configuration utilities for storage devices, logical volume managers that tie multiple physical devices together as one, and file systems to arrange layout of data on storage devices. —Storage systems are a vital and growing market. Their primary components are magnetic and optical disk drives, magnetic tapes, and largecapacity robotic assemblies of drives and cartridges. Storage hardware sales in 1995 topped $40 billion, including more than 60,000 terabytes of hard disk storage. In recent years, the amount of storage sold has been almost doubling each year; in the near future it is expected to sustain an annual growth of about 60%. This enormous growth rate has been accompanied by a 50% per year decrease in the cost per byte of storage. These growth trends exceed those of the personal computer market. —The focus of this article is on secondary storage systems and primarily on magnetic disk drives, since these are

An algorithmic mapping of storage locations brings high storage efficiency to the storage system, but the loss of efficient scheduling makes systems prone to crashing at low usage. This paper uses the Ceph storage system as a research sample to analyze these issues and proposes a grading mapping adaptive storage resource collaborative optimization mechanism. This approach grading both the storage device and the storage content, and introduced random factors and influence factors as two-factors to quantify the grading mapping relationship between the two of them. This relation coordinates the storage systems’ performance and reliability. In addition, a collaborative storage algorithm is proposed to realize balanced storage efficiency and control data migration. The experimental results show that in comparison with the inherent mechanism in the traditional Ceph system, the proposed cooperative storage adaptation mechanism for data balancing has increased the average system usage by 17% and reduces data migration by 50% compared to the traditional research approach.

The performance gap between processor and storage device has continuously increased during the past few decades. The gap is further exacerbated recently because applications are becoming more data-intensive in both industry and academia. Traditional storage devices, such as hard disk drives (HDD), fail to keep up with the paces of this growth. A known solution is to use solid state drives (SSD) as fast storage. Due to high cost of SSD, data and supercomputing centers usually adopt a hybrid storage system, which consists of a combination of HDD and SSD I/O servers. However, hybrid I/O and storage systems have increased the complexity, making SSD often underutilized. The configuration and utilization of HDD/SSD hybrid systems is a lasting phenomenon. In this study, we propose a high performance hybrid parallel I/O and storage simulator, HPIS3. As a co-design tool, HPIS3 is capable of simulating a variety of parallel storage systems, especially under hybrid scenarios. The experimental results show that the lowest error rate is 2%, and the average is 11.98%.

Storage systems are the next frontier for providing protection against intrusion. Since storage systems see changes to persistent data, several types of intrusions can be detected by storage systems. Intrusion detection (ID) techniques can be deployed in various storage systems. In this paper, we study how intrusions can be detected at the block storage level and in SAN environments. We propose novel approaches for storage-based intrusion detection and discuss how features of state-of-the-art block storage systems can be used for intrusion detection and recovery of compromised data. In particular we present two prototype systems. First we present a real time intrusion detection system (IDS), which has been integrated within a storage management and virtualization system. In this system incoming requests for storage blocks are examined for signs of intrusions in real time. We then discuss how intrusion detection schemes can be deployed as an appliance loosely coupled with a SAN storage system. The major advantage of this approach is that it does not require any modification and enhancement to the storage system software. In this approach, we use the space and time efficient point-in-time copy operation provided by SAN storage devices. We also present performance results showing that the impact of ID on the overall storage system performance is negligible. Recovering data in compromised systems is also discussed.

This paper proposes a design procedure that exploits storage devices with different cost/bandwidth and cost/capacity ratios to build a hierarchical storage system for video-on- demand with minimum cost. The storage system is assumed to have two levels of hierarchy. The level-1 storage devices feature a low cost/bandwidth ratio and a high cost/capacity ratio. On the other hand, the level-2 storage devices feature a high cost/bandwidth ratio and a low cost/capacity ratio. The proposed procedure determines, with respect to overall system cost, which level of the hierarchy each program should be placed into. Based on the decisions, the designer then can figure out the appropriate configuration of the hierarchical storage system. The optimization target is to minimize the overall cost of the storage system.

Solar‐responsive energy storage system (SRESS) that integrates solar‐energy conversion and electrochemical‐energy storage, is highly promising to advance renewable energy application due to its capability to directly and effectively store solar‐energy into rechargeable batteries. The last decade has evidenced intensive progress on the integration of photoelectric conversion devices and secondary batteries, from an initially photo‐driven system that simply connects state‐of‐the‐art solar cells with storage devices, to a currently photo‐assisted battery with photo‐active electrodes utilizing solar energy to enhance redox kinetics in electrochemical batteries. Noting that integration methodology is of paramount importance to influence performance and applications of SRESS, systematically analyzing working mechanisms, device architectures, and performance metrics according to integration modes in SRESS is necessary, while there is currently a lack of review with such an intention. Therefore, the present work highlights the critical role of integration strategies in determining the energy conversion efficiency of SRESSs, by providing a comprehensive overview of development history, working principles, as well as the comparison of similarities and differences of these systems. The uncertain performance evaluation indicators are also classified to provide basic criteria for the evaluation of SRESSs. Finally, a forward‐looking perspective and challenges, including but not limited to safety, efficiency, and stability of SRESSs by different integration approaches, are offered.

Enterprises usually store data in internal storage and install firewalls to protect against intruders to access the data. They also standardize data access procedures to prevent insiders to disclose the information without permission. In cloud computing, the data will be stored in storage provided by service providers. Service providers must have a viable way to protect their clients' data, especially to prevent the data from disclosure by unauthorized insiders. Storing the data in encrypted form is a common method of information privacy protection. If a cloud system is responsible for both tasks on storage and encryption/decryption of data, the system administrators may simultaneously obtain encrypted data and decryption keys. This allows them to access information without authorization and thus poses a risk to information privacy. This study proposes a business model for cloud computing based on the concept of separating the encryption and decryption service from the storage service. Furthermore, the party responsible for the data storage system must not store data in plaintext, and the party responsible for data encryption and decryption must delete all data upon the computation on encryption or decryption is complete. A CRM (Customer Relationship Management) service is described in this paper as an example to illustrate the proposed business model. The exemplary service utilizes three cloud systems, including an encryption and decryption system, a storage system, and a CRM application system. One service provider operates the encryption and decryption system while other providers operate the storage and application systems, according to the core concept of the proposed business model. This paper further includes suggestions for a multi-party Service- Level Agreement (SLA) suitable for use in the proposed business model.

Market clearing price-based energy management of grid-connected renewable energy hubs including flexible sources according to thermal, hydrogen, and compressed air storage systems

We have proposed a distributed storage system which aims to utilize storage fragments distributed in network nodes without administrators' maintenance cost. Even the performance of storage devices are not uniform, autonomously data block migration helps to achieve enhancing the whole I/O performance of the storage system. However, we have considered all the storage devices to be reliable equally. On this assumption, migration of an important data block to unstable storage might cause degradation of the availability of the data block. In this paper, we propose a scheme to choose the destination of data block migration by evaluating the nodes' reliability along with the performance of storage devices. This scheme aims to improve system stability by preventing to locate a critical data onto an unstable storage device. The storage nodes which lack stability are also utilized for storing a data block which can be easily regenerated or duplicated. The results of the preliminary investigation show that a large number of warning logs from Machine Check Architecture may suggest a sign of unexpected system shutdown.

Simultaneous co-integration of multiple electrical storage applications in a consumer setting