Distributed Storage Applications Research Articles

Distributed Ledger as a Service: A Web 3.0-Oriented Architecture

This paper proposes a general and interoperable Web of Things (WoT)-oriented architecture to support a distributed storage application. In particular, the focus is on a distributed ledger service dedicated to machine-to-machine (M2M) transactions occurring in an intelligent ecosystem. For this purpose, the basic functional modules have been characterized and integrated into a comprehensive framework relying on an IOTA approach. Furthermore, a general protocol that is built upon an underlying publish-and-subscribe framework is proposed to support all the application phases. The proposed approach has been validated by a simulation campaign targeting the achievable latency and throughput and, further, by a qualitative analysis of high-level metrics, both pointing out several advantages in terms of interoperability, scalability, and mobility support, together with addressing some constraints affecting service availability and security.

Simulation and analysis of a peak regulation gas power plant with advanced energy storage and cryogenic CO2 capture

Flexible gas power plants are subject to energy storage, peak regulations, and greenhouse gas emissions. This study proposes an integrated power generation system that combines liquid air energy storage (LAES), liquefied natural gas (LNG) cold energy utilization, gas power systems, and CO2 capture and storage (CCS) technologies, named the LAES-LNG-CCS system. The off-peak electricity can be stored in liquid air. During the peak period, air and gas turbines generate supplementary electricity. Both LNG chemical energy and cold energy were considered: the former was used for gas power plants, and the latter was used for LAES regasification and CCS processes. Based on the thermodynamic analysis, we evaluated the effects of the recovery pressure, CCS pressure, and combustion temperature on the system power consumption and efficiency. The results demonstrated that the system recovery pressure, CCS pressure, and combustion temperature had the greatest effects on system power generation. Round-trip efficiency (RTE) was significantly affected by combustion temperature. The largest exergy loss occurred in the gas power plant. The optimal system operating ranges of the system recovery pressure, CCS pressure, and combustion temperature were 6−10 MPa, 0.53−0.8 MPa, and 1,503−1,773 K, where the RTEs and ηEx,RS reached 55%−58.98% and 74.6%−76%, respectively. The proposed system can simultaneously achieve the synergistic functions of large-scale energy storage, multilevel energy utilization, peak regulation, and carbon emission reduction. It can also be widely used in advanced distributed energy storage applications in the future.

Update on Nexceris’ Solid Oxide Fuel Cell Stack Technology

Over the past several years Nexceris has advanced its solid oxide fuel cell (SOFC) stack technology through innovations in materials, design, and operation. Sustainable fuel cell operation of Nexceris’ lightweight stack at high current density (0.5 – 0.7 A/cm²) and fuel utilization (70 – 80%) yields both high gravimetric power density and electrical efficiency. Stack robustness against thermal gradients, thermal cycling, and one-off events has been achieved through a combination of design modifications, sealing advancements, and operational protocols. Meanwhile, Nexceris’ stack technology maintains the key advantages of its patented FlexCell planar cell design, internal reforming capability, and tolerance to sulfur impurities in military logistic fuels.Recent and ongoing work at Nexceris includes stack demonstrations in breadboard systems and at customer sites, scale-up of stack manufacturing capabilities, and the development of a 10-kW stack module, opening the door to large-scale distributed generation and energy storage applications. This presentation will provide an update on the status and capabilities of Nexceris’ SOFC stacks and cost-saving approaches to stack fabrication.

Sparse and Balanced Reed–Solomon and Tamo–Barg Codes

We study the problem of constructing balanced generator matrices for Reed–Solomon and Tamo–Barg codes. More specifically, we are interested in realizing generator matrices, for the full-length cyclic versions of these codes, where all rows have the same weight and the difference in weight between any columns is at most one. The results presented in this paper translate to computationally balanced encoding schemes, which can be appealing in distributed storage applications. Indeed, the balancedness of these generator matrices guarantees that the computation effort exerted by any storage node is essentially the same. In general, the framework presented can accommodate various values for the required row weight. We emphasize the possibility of constructing sparsest and balanced generator matrices for Reed–Solomon codes, i.e., each row is a minimum distance codeword. The number of storage nodes contacted once a message symbol is updated decreases with the row weight, so sparse constructions are appealing in that context. Results of similar flavor are presented for cyclic Tamo–Barg codes. In particular, we show that for a code with minimum distance $d$ and locality $r$ , a construction in which every row is of weight $d + r - 1$ is possible. The constructions presented are deterministic and operate over the codes’ original underlying finite field. As a result, efficient decoding from both errors and erasures is possible thanks to the plethora of efficient decoders available for the codes considered.

Repairing Reed-Solomon Codes With Multiple Erasures

Despite their exceptional error-correcting properties, Reed-Solomon codes have been overlooked in distributed storage applications due to the common belief that they have poor repair bandwidth: A naive repair approach would require the whole file to be reconstructed in order to recover a single erased codeword symbol. In a recent work, Guruswami and Wootters (STOC'16) proposed a single-erasure repair method for Reed-Solomon codes that achieves the optimal repair bandwidth amongst all linear encoding schemes. Their key idea is to recover the erased symbol by collecting a sufficiently large number of its traces, each of which can be constructed from a number of traces of other symbols. We extend the trace collection technique to cope with two and three erasures.

Energy-aware RAID scheduling methods in distributed storage applications

A dynamic power management (DPM) method makes power-mode-related decisions based on the information available at runtime (online) or before (offline). This paper proposes energy-aware RAID scheduling methods to reduce energy consumption for distributed storage applications using both online and offline DPM strategies. The proposed energy-aware redundant array of inexpensive disk (RAID) scheduling method differs from the existing RAIDs method in that it separately strips data and parity blocks and switches the power mode from active to idle or standby while storage applications are not performing any physical I/O operations. Traditional DPM schedulers are applied for a single logical I/O operation or multiple of the logical I/O operations (workload), whereas the proposed DPM scheduler is applied for physical I/O operations. Experimental results show that the proposed storage application reduces average energy consumption by 26–36% compared to existing storage applications.

Oblivious Network RAM and Leveraging Parallelism to Achieve Obliviousness

Oblivious RAM (ORAM) is a cryptographic primitive that allows a trusted CPU to securely access untrusted memory, such that the access patterns reveal nothing about sensitive data. ORAM is known to have broad applications in secure processor design and secure multiparty computation for big data. Unfortunately, due to a logarithmic lower bound by Goldreich and Ostrovsky (J ACM 43(3):431–473, 1996), ORAM is bound to incur a moderate cost in practice. In particular, with the latest developments in ORAM constructions, we are quickly approaching this limit, and the room for performance improvement is small. In this paper, we consider new models of computation in which the cost of obliviousness can be fundamentally reduced in comparison with the standard ORAM model. We propose the oblivious network RAM model of computation, where a CPU communicates with multiple memory banks, such that the adversary observes only which bank the CPU is communicating with, but not the address offset within each memory bank. In other words, obliviousness within each bank comes for free—either because the architecture prevents a malicious party from observing the address accessed within a bank, or because another solution is used to obfuscate memory accesses within each bank—and hence we only need to obfuscate communication patterns between the CPU and the memory banks. We present new constructions for obliviously simulating general or parallel programs in the network RAM model. We describe applications of our new model in distributed storage applications with a network adversary.

MaxMinSum Steiner Systems for Access Balancing in Distributed Storage

Many code families such as low-density parity-check codes, fractional repetition codes, batch codes and private information retrieval codes with low storage overhead rely on the use of combinatorial block designs or derivatives thereof. In the context of distributed storage applications, one is often faced with system design issues that impose additional constraints on the coding schemes, and therefore on the underlying block designs. Here, we address one such problem, pertaining to server access frequency balancing, by introducing a new form of Steiner systems, termed MaxMinSum Steiner systems. MaxMinSum Steiner systems are characterized by the property that the minimum value of the sum of points (elements) within a block is maximized, or that the minimum sum of block indices containing some fixed point is maximized. We show that proper relabelings of points in the Bose and Skolem constructions for Steiner triple systems lead to optimal MaxMin values for the sums of interest; for the duals of the designs, we exhibit block labelings that are within a 3/4 multiplicative factor from the optimum.

A High-Performance Sintered Iron Electrode for Rechargeable Alkaline Batteries to Enable Large-Scale Energy Storage

Iron-based alkaline rechargeable batteries such as iron-air and nickel-iron batteries are particularly attractive for large-scale energy storage because these batteries can be relatively inexpensive, environment- friendly, and also safe. Therefore, our study has focused on achieving the essential electrical performance and cycling properties needed for the widespread use of iron-based alkaline batteries in stationary and distributed energy storage applications. We have demonstrated for the first time, an advanced sintered iron electrode capable of 3500 cycles of repeated charge and discharge at the 1-hour rate and 100% depth of discharge in each cycle, and an average Coulombic efficiency of over 97%. Such a robust and efficient rechargeable iron electrode is also capable of continuous discharge at rates as high as 3C with no noticeable loss in utilization. We have shown that the porosity, pore size and thickness of the sintered electrode can be selected rationally to optimize specific capacity, rate capability and robustness. These advances in the electrical performance and durability of the iron electrode enables iron-based alkaline batteries to be a viable technology solution for meeting the dire need for large-scale electrical energy storage.

Locality and Availability in Distributed Storage

This paper studies the problem of information symbol availability in codes: we refer to a systematic code as code with $(r, t)$ -availability if every information (systematic) symbol can be reconstructed from $t$ disjoint groups of other code symbols, each of the sizes at most $r$ . This paper shows that it is possible to construct codes that can support a scaling number of parallel reads while keeping the rate to be an arbitrarily high constant. It further shows that this is possible with the minimum Hamming distance arbitrarily close to the Singleton bound. This paper also presents a bound demonstrating a tradeoff between rate, minimum Hamming distance, and availability parameters. Our codes match the aforementioned bound, and their constructions rely on certain combinatorial structures. Resolvable designs provide one way to realize these required combinatorial structures. The two constructions presented in this paper require field sizes, which are linear and exponential in the code length, respectively. From a practical standpoint, our codes are relevant for distributed storage applications involving hot data, i.e., the information, which is frequently accessed by multiple processes in parallel.

Update-Efficiency and Local Repairability Limits for Capacity Approaching Codes

Motivated by distributed storage applications, we investigate the degree to which capacity achieving codes can be efficiently updated when a single information symbol changes, and the degree to which such codes can be efficiently repaired when a single encoded symbol is lost. Specifically, we first develop conditions under which optimum error-correction and update-efficiency are possible. We establish that the number of encoded bits that should change in response to a change in a single information bit must scale logarithmically in the block-length of the code, if we are to achieve any nontrivial rate with vanishing probability of error over the binary erasure or binary symmetric channels. Moreover, we show that there exist capacity-achieving codes with this scaling. With respect to local repairability, we develop tight upper and lower bounds on the number of remaining encoded bits that are needed to recover a single lost encoded bit. In particular, we show that when the rate of an optimal code is ε below capacity, the maximum number of codeword symbols required to recover one lost symbol must scale as log1/ε. Several variations on-and extensions of-these results are also developed, including to the problem of rate-distortion coding.

Whole-Systems Assessment of the Value of Energy Storage in Low-Carbon Electricity Systems

Energy storage represents one of the key enabling technologies to facilitate an efficient system integration of intermittent renewable generation and electrified transport and heating demand. This paper presents a novel whole-systems approach to valuing the contribution of grid-scale electricity storage. This approach simultaneously optimizes investment into new generation, network and storage capacity, while minimising system operation cost, and also considering reserve and security requirements. Case studies on the system of Great Britain (GB) with high share of renewable generation demonstrate that energy storage can simultaneously bring benefits to several sectors, including generation, transmission and distribution, while supporting real-time system balancing. The analysis distinguishes between bulk and distributed storage applications, while also considering the competition against other technologies, such as flexible generation, interconnection and demand-side response.

The Rank of Random Binary Matrices and Distributed Storage Applications

Random binary matrices appear in a variety of signal processing and encoding problems. They play an important role in rateless codes and in distributed storage applications. This paper focuses on block angular matrices, a class of random rectangular binary matrices that are particularly suited to distributed storage applications. We address one of the key issues regarding binary random matrices in general, and block angular matrices in particular: the probability of obtaining a full rank matrix, when drawing uniformly at random from the set of binary matrices with compatible structure. This paper gives a closed-form expression for this probability, as well as some bounds and approximations.

Research on a Distributed Storage Application with HBase

This paper describes research in the use of HBase to develop storage applications.. This paper introduces the structure of HBase library and describes the implementation of algorithms in our library. HBase is a NoSQL database., A Bigtable is a sparse, distributed, persistent multi-dimensional sorted map. The map is indexed by a row key, column key, and a timestamp; each value in the map is an uninterpreted array of bytes.

Collusion in peer-to-peer systems

P2P systems are used to provide distributed storage, file sharing, video streaming, distributed gaming, and other applications based on the collaboration of participating peers and on the observation that sharing resources used sporadically leads to huge savings. The operation of a P2P system, as well as its sheer survival, however, is open to many kinds of attacks, which are tough to fight due to both the decentralized nature of P2P applications, and the lack, in some of them, of a central authority, or of a well-defined structure, or both. Particularly, as P2P systems require the active collaboration of the participants beyond their selfish interest, many systems include methods designed to lure the most resourceful users into broader participation, to provide an overall better service. The methods devised to attract the contribution of users are unfortunately vulnerable to a particular class of attacks: collusion. Collusion is broadly defined as any malicious coordinated behavior of a group of users aimed at gaining undeserved benefits, or at damaging (some) well behaved users. In this paper, we survey the literature on P2P systems security with specific attention to collusion, to find out how they resist to such attacks and what solutions can be used, e.g., game theory, to further counter this problem and give P2P systems the possibility of developing into full fledged services of the future Internet.

Experiences with a FPGA-based Reed/Solomon-encoding coprocessor

In this paper we present an implementation of a Reed/Solomon (R/S)-coprocessor to be used on a hybrid computing system, which combines general purpose CPUs with FPGAs. The coprocessor accelerates the encoding of user data to be stored block-wise on a distributed, failure-tolerant storage system. We document design constraints and their impact on the resulting architecture. Measurements are presented to characterize the performance of the coprocessor in terms of computational bandwidth, latency, and the hardware–software interaction. For comparison, software-based R/S-encoding implementations are presented and evaluated as well. The two variants of the FPGA-based coprocessors are compared to each other with respect to their fitting to a distributed storage application.

WDM optical network testbed and distributed storage application

In this article we present the details of a generalized multiprotocol label switching controlled wavelength-division multiplexing (WDM) optical network developed under the Optical Network Focused Interest Group (ONFIG) program in Singapore. The WDM network is controlled through a GMPLS control plane that consists of CR-LDP, LMP, and OSPF-TE. We conducted various field trials on the GMPLS-capable WDM optical network testbed with the main focus on distributed storage service application. We developed and evaluated a distributed storage services application on the WDM optical network testbed and demonstrated that incorporating a lightweight data transport protocol with optical network control could be an efficient approach for data-intensive storage applications by exploiting the dynamic connection establishment and backup protection features.

The basics of reliable distributed storage networks

Because of storage protocols that operate over extended distances, various distributed storage applications that improve the efficiency and reliability of data storage are now possible. Distributed storage applications improve efficiency by allowing any network server to transparently consolidate and access data stored in multiple physical locations. Remote backup and mirroring improve the system's reliability by copying critical data. These processes improve efficiency by eliminating backup downtime and manual backup operations. Business continuity and disaster recovery capabilities enable enterprises to recover quickly and transparently from system failure or data loss. Storage protocols and gateway devices enable rapid and transparent data transfer between mainframe applications and open-systems applications. NAS applications provide shared file access for clients using standard LAN-based technology, and can integrate with SAN architectures to provide truly distributed network capabilities. All these distributed storage network applications enable IT managers to improve data availability and reliability while minimizing management overhead and costs.