Distributed Storage Research Articles

Control techniques for microgrids networks with energy storage systems: An overview

Microgrids (MG) are localized, self-sufficient energy networks which utilize distributed energy sources to improve dependability, resiliency and long-term viability in decentralized energy production. Network Energy Storage Systems (ESS) have been recognized as critical facilitators within the transitioning from the conventional centralized power system into a sophisticated, self-sustaining, as well as decentralized systems based on renewable energies. Controlling distributed energy storage entails coordinating the administration of several lesser energy storages, which are generally integrated in MGAs consequence, there have been an increase in fascination with regulating elements of sharing power balance and sustainable development, boosting the system's resilience including dependability, along with maintaining a distribution State of charge (SoC). The present research provides a detailed overview of decentralized, centralized, multiagent, and intelligent controlling techniques for managing and regulating distributed energy storages. It also illustrates a possible range of functions which the storages might supply, as well as the controlling challenges and recommended solutions. This research major purpose is to represent current breakthroughs in digitalization by focusing on controlling techniques that depend on multiagent communications.

Region-based compressive distributed storage in Mobile CrowdSensing

Compressive Sensing-based distributed data storage for Mobile CrowdSensing (MCS) primarily addresses the problem that data needs to be stored temporarily on mobile devices when the central server cannot work as expected. In the crowdsensing-aware platform, the emerging distributed storage scheme mainly recovers the data fields of the entire area. However, when only local area information is required, it is still necessary to recover the entire area, creating unnecessary waste. Based on this observation, this paper proposes a Region-based Distributed Data Storage with global Denoising (R-DDS-D) algorithm. Region-based distributed data storage strategy is individually coded in regional blocks, allowing users to reconstruct the regional information they need selectively. Simultaneously, global denoising can be achieved through the correlation between small regions, which can further improve the accuracy of reconstructed data. In addition, not all local region information is equally significant, an extended algorithm for sampling allocation is proposed considering the importance of different regions to further improve accuracy. Theoretical analysis demonstrates that R-DDS-D can recover the signal with high probability, and the sampling allocation method can more reasonably allocate sampling resources. Experimentally, the R-DDS-D scheme offers greater flexibility, recruiting cost savings, and smoother reconstruction performance for recovering local regions, and the sampling allocation method further enhances the reconstruction quality in the case of uneven data distribution.

Blockchain-based cooperative game bilateral matching architecture for shared storage

The development of IPFS (InterPlanetary File System) and blockchain-based distributed storage projects has brought new possibilities to the field of storage. This paper proposes a blockchain-based cooperative game bilateral matching architecture as a novel approach for shared storage networks. In traditional competitive (non-cooperative) game models, the allocation of storage resources is centered around pricing, leading to a scenario where node providers often engage in price competition to obtain greater rewards, resulting in an imbalance in resource allocation for both buyers and sellers. In contrast, a distributed storage model based on cooperative game theory can better facilitate cooperation and resource sharing among node providers. This paper designs a storage resource allocation algorithm based on the stable marriage matching algorithm, demonstrating the stability of this algorithm as a matching solution. The paper also analyzes the differences between cooperative and non-cooperative game models in the market, and explores an equilibrium pricing mechanism guided by supply and demand. Furthermore, the paper introduces a trading mechanism for storage resources, including publication standards and matching schemes, ensuring efficient and trustworthy interaction between storage suppliers and demanders in a decentralized network centered around storage resources, thus enabling the circulation of the value of storage resources. A prototype of a blockchain-based shared storage trading system is implemented in this paper, utilizing bilateral matching for tradings. System evaluation and experimental testing are conducted, with results showing that the average utility value of the matching trading mechanism proposed in this paper outperforms the Double Auction-based matching model under any Poisson distribution (λ = 0.1, 0.2, 0.3, …, 0.9) conditions set in the experiments. Additionally, compared to the traditional approach of directly storing complete data content on the chain, the design proposed in this paper effectively reduces on-chain storage consumption by approximately 27.06%.

Investigation on the heat transfer and charge/discharge performance of phase change material capsule emulsion based on nanoparticles enhanced thermal conductivity

Both internal encapsulation and external added nanoparticles have been employed in this study to enhance thermal conductivity and explore the corresponding heat transfer characteristics. Specifically, the correlation between thermal conductivity and capsule, nanoparticle content, as well as the enhanced heat transfer/thermal energy storage performance facilitated by internal encapsulation are demonstrated through numerical and experimental study. Furthermore, it compares key parameters like heat transfer and pressure drop, providing quantifiable evidence that the addition of nanoparticles, whether internally or externally, leads to an increase of thermal conductivity by 6.63 %/2.75 % (5 wt%) and 5.92 %/4.26 % (10 wt%), respectively. Internal encapsulation was observed to yield a more substantial enhancement in heat transfer. Moreover, higher capsule concentrations tend to induce an inverted concentration profile near the heat exchange wall, particularly at higher flow rates. Furthermore, encapsulating nanoparticles within these capsules enhances heat transfer performance, with the level of enhancement scaling with the nanoparticle quantity. Increasing the flow rate of emulsion from 0.4 m·s−1 to 0.6 m·s−1 in a horizontal tube resulted in a 26.67 % increase in heat transfer and a 41.55 % increase in pressure drop. As a result of the disturbed heating, thermal fluctuations of external addition showed more pronounced thermal fluctuations due to disrupted heating, while a internal encapsulation exhibited a more stable temperature distribution and superior heat storage performance.

Smart landscaping design for sustainable net-zero energy smart cities: Modeling energy hub in digital twin

In our study, we introduce an innovative energy management system optimized for energy hubs in net-zero energy smart cities, emphasizing sustainability as a core objective. Our approach intricately integrates distributed generation systems and storage facilities within a digital twin framework, incorporating landscape considerations to promote environmental harmony. By prioritizing sustainability, our strategy aims to minimize operational costs while maximizing energy efficiency and reducing carbon emissions. We employ specialized energy flow algorithms for each grid, designing energy hubs that leverage renewable resources and mobile storage to enhance sustainability. To address complexity, our model utilizes a non-convex mixed-integer nonlinear programming structure and robust adaptive optimization techniques, combining the Gray Wolf and Krill Herd algorithms. Through simulations, we demonstrate significant improvements in power system efficiency, including notable reductions in power loss, peak voltage fluctuations, and temperature variations. Our research underscores the critical role of smart landscaping in advancing sustainable energy management for net-zero energy smart cities, facilitating seamless integration of energy hubs with the surrounding landscape within a digital twin paradigm.

Heat transfer performance of copper foam/paraffin composite phase change material under different centrifugal forces-A visual experimental study

Copper foam is used to enhance the heat transfer of phase change material (PCM) due to its high thermal conductivity. However, its porous structure can restrict the convection of PCM. The natural convection of PCM embedded in copper foam under external force remains unclear. A visual experimental system was established to investigate the effect of copper foam on the heat transfer process of PCM under external force. The phase interface, temperature distribution, and heat storage rate of composite PCM (CPCM) were conducted under centrifugal forces from -5 g to 5 g. Results indicate that there is a significant difference in the melting rate and temperature distribution of PCM under different forces. Under forward force, the convection of PCM is inhibited, and the isotherm is parallel to the end-state isobars line, increasing the total melting time of CPCM and creating a large temperature gradient near the heat source. Conversely, under the backward force, the melting rate of CPCM is increased due to the enhanced natural convection of liquid PCM. The development of isotherms is influenced by buoyancy, which results in a more uniform temperature distribution of CPCM. However, the enhancement effect of the backward force is limited when it exceeds -3 g. In general, CPCM exhibits more apparent improvement in heat transfer performance under the backward force. This article provides references for the optimization design of thermal management systems.

Development of the AI Pipeline for Corneal Opacity Detection.

Ophthalmological services face global inadequacies, especially in low- and middle-income countries, which are marked by a shortage of practitioners and equipment. This study employed a portable slit lamp microscope with video capabilities and cloud storage for more equitable global diagnostic resource distribution. To enhance accessibility and quality of care, this study targets corneal opacity, which is a global cause of blindness. This study has two purposes. The first is to detect corneal opacity from videos in which the anterior segment of the eye is captured. The other is to develop an AI pipeline to detect corneal opacities. First, we extracted image frames from videos and processed them using a convolutional neural network (CNN) model. Second, we manually annotated the images to extract only the corneal margins, adjusted the contrast with CLAHE, and processed them using the CNN model. Finally, we performed semantic segmentation of the cornea using annotated data. The results showed an accuracy of 0.8 for image frames and 0.96 for corneal margins. Dice and IoU achieved a score of 0.94 for semantic segmentation of the corneal margins. Although corneal opacity detection from video frames seemed challenging in the early stages of this study, manual annotation, corneal extraction, and CLAHE contrast adjustment significantly improved accuracy. The incorporation of manual annotation into the AI pipeline, through semantic segmentation, facilitated high accuracy in detecting corneal opacity.

Analyzing flexibility options for microgrid management from economical operational and environmental perspectives

Power grids have undergone a massive transformation due to increasing number of renewable/non renewable distributed generators, storage technologies and electrical vehicles. This paper focuses on the flexible energy management of grid connected microgrid (MG) in order to analyze the effects of the flexibility options such as electric vehicle with demand response (EV-DR), battery storage system (BSS), hydrogen storage system (HSS) and dynamic line rating (DLR) in presence of renewable sources. In addition, microturbine (MT), fuel cell (FC), biomass (BIO), geothermal (GEO), and diesel engine (DIE) whose output is controllable are also considered as flexible sources. In this paper, optimum operation of grid-connected MG is modeled as a mixed-integer linear programming problem considering uncertainties of wind turbine (WT) and photovoltaic (PV) sources. A day-ahead forecasting of irradiance and wind speed are performed with Decision Tree Regression (DTR) and Long Short Term Memory (LSTM) algorithms for sensitive calculation of PV and WT output. The cost function merges operating costs including fuel, operation & maintains (O&M), depletion costs with emission cost of CO2, SO2, and NOx. Obtained numerical results show that total cost of the MG is reduced by 9.40% and emission cost is diminished by 5.59% with inclusion of all considered flexibility options. Further, load factor is improved from 0.7932 to 0.8236 with 100% flexibility condition for MG.

Optimal configuration and power scheduling algorithm of distributed power system with large range power flow transfer

The distributed power system is composed of multiple distributed energy sources, loads and energy storage devices, which have the characteristics of decentralization and complexity. Therefore, a distributed power system optimal allocation and power dispatching algorithm considering large-scale power flow transfer is proposed. Calculate the power flow values of different nodes, and construct an optimization model according to the results to complete power flow transmission. In the inner loop, the current dispatching is set as the objective, and in the outer loop, the voltage dispatching is set as the objective. Distributed power system scheduling is completed by double closed-loop vectors. The experimental results show that the power oscillation amplitude of this method is small and the duration is short.

Storage systems for the transition towards active and smart distribution systems

The paper presents the criteria adopted for designing a storage system to be used in a distribution grid where several distributed resources exist. The purpose of introducing storage in distribution is to enable the operators to manage the grid as a really active system. A droop based control system has been designed and tested through simulations. The results are currently being used to specify and build a prototype device to be installed in a test facility where Enel will develop a “smart grid”.

Improved static membrane-free zinc‑bromine batteries by an efficient bromine complexing agent

Zinc‑bromine batteries (ZBBs) are very promising in distributed and household energy storage due to their high energy density and long lifetime. However, the disadvantages of existing zinc‑bromine flow batteries, including complicated structure, high cost for manufacturing and maintenance, limited their large-scale applications seriously. Additionally, polybromide anions during the charging process of ZBBs will result in the problem of self-discharge. Here, a static membrane-free ZBB (SMF-ZBB) structure has been proposed, in which the phenyl trimethyl ammonium bromide (PTMAB) works as a bromine complexing agent (BCA). Because PTMAB has a feature of strong polarity, it can be combined well with polybromide anions to reduce the self-discharge effectively. Furthermore, it can also reduce the internal resistance of electrolytes and improve the energy density of SMF-ZBB. Compared with the blank electrolyte, the coulombic efficiency (CE) of the battery with PTMAB addition was increased by 10 % at 20 mA/cm2. The CE with a value of 93.1 % can be well maintained even after >5000 cycles at 10 mA/cm2. The results show that the introduction of PTMAB into the electrolytes can improve the CE and energy efficiency (EE) effectively.

A novel node selection method for wireless distributed edge storage based on SDN and a maldistributed decision model

A novel node selection method for wireless distributed edge storage based on SDN and a maldistributed decision model

Numerical simulation of indoor air distribution and wall heat storage under accident conditiohs in a main control room

The main control room serves as a refuge for staff in a nuclear power plant in the event of an accident. To determine whether the control room can meet habitability requirements under accident conditions, this study utilized CFD methods to establish a habitability model of the main control room under such conditions. The changing trends of temperature and velocity near personnel were analyzed. The numerical results indicate that the building envelope significantly contributes to reducing the indoor temperature. The average wall temperature measured at 72 hours was 27?C, with an average temperature increase of 4?C. The highest average ambient temperature in the main control room occurred at 24 hours. At this time, the indoor ambient temperature reached approximately 34.62?C, with a temperature increase of 11.62?C, while the wind speed near the personnel remained below 0.2 m/s, meeting habitability requirements for personnel under extreme conditions.

Методика оценки эффективности механизации коневодства в условиях экстремально низких температур

The article briefly characterizes the state of horse breeding in the Republic of Sakha (Yakutia). There are special features in breeding of the Yakutian horses. The Yakutian horses stay outdoors all year round and feed mainly on fodder. At present, villagers have started to maximize the number of horses due to the unpretentiousness of their feeding. However, another problem has arisen – due to the sharp increase in horse number there is not enough fodder. To solve this problem, it is proposed to organize mechanical distribution of additional feeding in the form of hay in decentralized areas. When calculating additional feeding norm, the following are taken into account: the required mass of hay, which is determined by the herd and the normative amount of hay per horse; the distance between hay distribution place and storage place, fuel consumption and pasture area. The aim of the study is to develop a methodology for forecasting the level of efficiency of herd horse breeding at the mechanized method of hay delivery and distribution by applying a mathematical dependence. It can help in choosing the location and distance for the organization of horse breeding bases in decentralized areas in the conditions of Yakutia. The calculations for preliminary assessment of proposed mathematical dependence efficiency were carried out. The initial data were taken for the existing horse breeding farm – LLC "Horse Farm Berte". The obtained results of forecast calculations have shown that the efficiency of production increases significantly, on average by 56.5% at mechanization of delivery and distribution of additional feeding in decentralized horse-breeding bases. At the farthest horse farm, located 60 km away from the central farmstead, it is possible to increase the number of animals from 145 to 227.

Hybrid fault tolerance in distributed in-memory storage systems

An in-memory storage system provides submillisecond latency and improves the concurrency of user applications by caching data into memory from external storage. Fault tolerance of in-memory storage systems is essential, as the loss of cached data requires access to data from external storage, which evidently increases the response latency. Typically, replication and erasure code (EC) are two fault-tolerant schemes that pose different trade-offs between access performance and storage usage. To help make the best performance and space trade-off, we design ElasticMem, a hybrid fault-tolerant distributed in-memory storage system that supports elastic redundancy transition to dynamically change the fault-tolerant scheme. ElasticMem exploits a novel EC-oriented replication (EOR) that carefully designs the data placement of replication according to the future data layout of EC to enhance the I/O efficiency of redundancy transition. ElasticMem solves the consistency problem caused by concurrent data accesses via a lightweight table-based scheme combined with data bypassing. It detects corelated read and write requests and serves subsequent read requests with local data. We implement a prototype that realizes ElasticMem based on Memcached. Experiments show that ElasticMem remarkably reduces the time of redundancy transition, the overall latency of corelated concurrent data accesses, and the latency of single data access among them.

Design and application of airport data storage under an information security optimization system

Abstract With the advancement of technology, the “partial construction” model is no longer able to meet the current information requirements of the aviation industry. Therefore, it is necessary to establish a complete “global informatization”, that is, an airport data center, which comprehensively includes multiple production management systems within the airport group, achieves information sharing, data analysis, and intelligent decision-making, thereby enabling the airport to achieve more accurate and reliable comprehensive economic and socially sustainable development. The current network storage technology often generates massive amounts of data when processing it, which leads to an increase in storage cycles and a decrease in storage performance. On this basis, the FPGA interface in FLASH chips was studied and analyzed in detail. On this basis, the FPGA receiving module is used to accurately receive and filter the massive data obtained, and convert it into high-quality FLASH format for daily use and maintenance. By analyzing the three-layer architecture, a large-scale network data storage solution based on the three-layer architecture is proposed. Finally, an implementation scheme for a new distributed storage system based on this model is presented, and simulation results are provided.

Assessing baby leaf kale (Brassica oleracea) waste production mitigation in the transition to sustainable packaging with the application of silicon through an integrative model of quality

This research builds a mathematical modelling to assess food waste production when designing sustainable packaging solutions integrated with an agricultural intervention in kale production. The model utilizes experimental data obtained from simulated retail and distribution storage conditions to assess the probability of the product to be found out of technical specification and becoming waste. The packaging design was made using a system of differential equations describing the gas exchanges inside the packaging. The waste was estimated fitting linear mixed effect models to the postharvest experimental data, accounting for the variability between and within groups. A field experiment with kale treated with silicon during growth as a bio stimulant was used with the aim to make the product more resilient to packaging conditions. The Kale was then packaged in polylactic acid and oriented polypropylene for postharvest testing. Technological thresholds that indicate out-of-specification product were used to estimate the percentage of product that would likely end up as food waste. In total 7.2% of the product was found to be out of specification with the PLA film after 7 days. Silicon treatment was able to reduce this value to negligible, demonstrating the ability of agricultural interventions to facilitate sustainable packaging and reducing food waste in horticultural products.

Blockchain-Based Secure Distributed File Storage for Community Cloud Computing

Cloud storage is the most used option for storing and sharing files. However, cloud storage has issues like lack of transparency, privacy, security, and trust. On the other hand, local file storage is always faster and more secure than public cloud storage. Besides, a community cloud is more economical and scalable than private storage. However, due to the ad-hoc nature of community users, developing such a community cloud storage has always been a challenge due to data privacy, security, and availability concerns. Recent developments in blockchain technology and computer security are promising to resolve most of these challenges. Thus, in this research, we are presenting blockchain-based, distributed file storage for community cloud computing. This research, which focuses on local communities, allows them to securely share the excessive storage with the locals to earn something while gaining access to faster, more reliable large-scale local storage. By replacing the central authority of third-party storage vendors and migrating to distributed file storage, local communities will achieve greater security, reliability, and control over their data while reducing the risks of data failures and interruptions. Due to symmetric encryption, data privacy would be 100% assured even though they are stored in other peoples' computers. Moreover, this system uses Reed Solomon. Using the Reed Solomon algorithm, the system can retrieve files even when users holding 33.33% of the files are not present. Besides, it allows local communities to make effective use of their idle and unallocated computer resources transparently.

Developing a predictive model of salted kimchi cabbage shelf-life using the general stability index

Salted kimchi cabbage (SKC) is a ready-to-use product used to manufacture kimchi. However, during distribution and storage, deterioration in quality parameters, such as pH, total titratable acidity, aerobic plate count, and color, lowers the product value. To ensure sufficient distribution and consumer storage, SKC should be vacuum-packed and cold-stored. Therefore, in this study, changes in SKC quality parameters were monitored at different cold storages (≤10 °C), and a predictive model of SKC shelf life was established using the general stability index (GSI) method. The established GSI method is an adequate tool for predicting the shelf life of SKC. The model with the highest R2 value was obtained by fitting the data with a second-order equation and integrating it with 0–10 °C using the Arrhenius equation. This study provides important insights into the quality assessment and shelf-life prediction of SKC during cold storage, contributing toward quality management systems. In addition, chromaticity values, which previously lacked reproducible measurement methods for SKC, were obtained after segmenting complex-shaped parts using a novel image analysis technique. This technique can be applied to a variety of vegetables to determine chromaticity of individual parts for assessing quality based on symptoms like browning.

OJUMP: Optimization for joint unicast‐multicast panoramic VR live streaming system

AbstractVirtual reality (VR) videos have garnered increasing attention due to their ability to deliver immersive multimedia experiences to users. Nonetheless, the demanding requirements of high bandwidth and low latency for VR services present significant challenges, especially in the context of network infrastructure. In this article, we introduce a novel system called OJUMP, aimed at Optimizing the transmission and distribution of Joint Unicast‐Multicast Panoramic video field of view live streaming using Bit Index Explicit Replication (BIER). The proposed system encompasses a BIER‐based network transmission approach that enhances video transmission efficiency and facilitates large‐scale service deployment. Furthermore, OJUMP includes a dynamic disk‐state‐based tile slice distribution storage algorithm and a prefetch method designed for edge nodes to enhance the distribution efficiency of live streaming services. Experimental results illustrate that the proposed system offers distinct advantages over the baseline system in terms of bandwidth, latency, disk utilization, and central processing unit utilization.