High Storage Utilization Research Articles

Long-term thermal performance analysis of a large-scale water pit thermal energy storage

Large-scale water pit thermal energy storage (PTES) promotes solar district heating (SDH) system as one of the most potential renewable applications for carbon neutrality. PTES needs vast investment and operates in a complicated system with numerous components, highlighting the need for a suitable simulation tool for tech-economic and feasibility investigations. This paper experimentally and theoretically investigated the long-term thermal performance of a 60,000 m3 PTES in Dronninglund, Denmark. Five years measurements were analyzed to investigate the development of temperatures, heat flows, and thermal stratification in heat storage. A modified 2D model was proposed to calculate the thermal performance of the large-scale PTES based on the XST model in TRNSYS. The results showed that the developed model predicts well the storage temperatures and the heat flows. For one-year validation, the deviations of annual charged/discharged energy, internal energy content, and annual thermal loss between the model and the measurements were 2.0%/1.8%, 2.8% and 1.3%, respectively. The Dronninglund PTES showed 90.1% storage efficiency in the five-year investigation due to its high storage utilization cycle of 2.16. Even without any insulation on the sidewall and the bottom of the PTES, the average thermal loss from the two parts only accounted for 32.3% of total heat loss. Meanwhile, the soil region needed four years to stabilize. Approx. 24.4% of the heat loss in summer from the sidewall and the bottom is regained by the PTES in winter, when there is a low temperature in the heat storage. The findings of the paper serve as a good reference for designers and practitioners of water pit heat storage.

ER-Store: A Hybrid Storage Mechanism with Erasure Coding and Replication in Distributed Database Systems

In distributed database systems, as cluster scales grow, efficiency and availability become critical considerations. In a cluster, a common approach to high availability is using replication, but this is inefficient due to its low storage utilization. Erasure coding can provide data reliability while ensuring high storage utilization. However, due to the large number of coding and decoding operations required by the CPU, it is not suitable for some frequently updated data. In order to optimize the storage efficiency of the data in the distributed system without affecting the availability of the data, this paper proposes a data temperature recognition algorithm that can distinguish data tablets and divides data tablets into three types, cold, warm, and hot, according to the frequency of access. Combining three replicas and erasure coding technology, ER-store is proposed, a hybrid storage mechanism for different data types. At the same time, we combined the read-write separation architecture of the distributed database system to design the data temperature conversion cycle, which reduces the computational overhead caused by frequent updates of erasure coding technology. We have implemented this design on the CBase database system based on the read-write separation architecture, and the experimental results show that it can save 14.6%–18.3% of the storage space while meeting the efficient access performance of the system.

Considering the influence of queue length on performance improvement for a new compact robotic automated parking system

With the development of the BI (Business intelligence) applications, robots and robot-based technology appear in various fields. Compact robotic automated parking system will facilitate the informatization and modernization of urban development and environmental protection. Compact robotic automated parking (CRAP) system is a new system with higher storage utilization and rapid response to store and handle cars. This system has double storage rings, instead of one storage ring in old compact automated parking (CAP) system for storing cars in each tier, and each tier is equipped with inner rotating ring and tier-captive automated guided vehicle for horizontal transport. The CRAP system has one elevator with vertical automated guided vehicle in the outer ring instead of the center part in the old CAP system for vertical transport. We first estimate the system performance using queuing network models. Second, we validate the analytical models through simulation and a real case. The simulation results show that we make an accurate estimation. Third, we optimize system configurations by minimizing the car retrieval time. Finally, given the same storage capacity, we compare the car retrieval time based on a real application and footprint area of CRAP system with CAP system. The results show that the car retrieval time can be reduced by at least 29.7% when the system capacity C is 400, and the space utilization can be improved by at least 32.0%.

Effects of aboveground herbivory on plants with long-term belowground biomass storage

Plant tolerance to herbivory is contingent on multiple traits and adaptive mechanisms, which makes it a complex response with ecological implications. In plants with long-term belowground storage, allocation of biomass to inaccessible parts belowground in response to folivory is a well-recognized tolerance mechanism. In temperate regions, spring growth from buried rootstock is common among winter deciduous plants and is often followed by regrowth after defoliation, both of which draws resources from the stored reserves. We developed a mathematical model to analyze this tolerance response in a winter deciduous plant with long-term belowground biomass when it is defoliated by a specialist insect folivore. The model explores how three closely associated traits—(1) belowground biomass allocation to roots, (2) spring utilization of stored reserves, and (3) post-defoliation regrowth capacity—modulate the persistence and dynamics of the plant and herbivore populations. Model results show that allocation to belowground storage is not only a critical component of tolerance but also influences the herbivore population dynamics in ways that depend on how and when plant biomass is allocated and used. Low belowground biomass allocation and high storage utilization combined with poor photosynthetic growth caused extirpation of the plant population by the defoliating insects. Stable coexistence of the plant at low biomass along with its specialist insect required a moderate amount of post-herbivory belowground allocation. High values of belowground biomass allocation, storage utilization, and photosynthetic growth resulted in sustained cycles of the herbivore and plant populations. Interestingly, utilization of stored reserves had conflicting influence on above and belowground biomass, and strongly affected herbivore population dynamics. Our model thus highlights the complexity of tolerance response when it involves multiple traits and mechanisms as evinced by winter deciduous plants. We close by discussing the implications of our findings for the contributions of defoliating insects to biocontrol programs.

Implementation of Monitoring Algorithms for the Battery Pack Optimal Design and Control in an Electric Vehicle

Battery monitoring algorithms and exclusively state of charge (SOC) estimation is the key function for successful operation of the battery management system (BMS). Enabling high storage utilization, safe operation environment for the battery pack and individual cells, cost reduction by avoiding over engineering, fault detection and lifetime enhancement are among all other benefits provided by monitoring algorithms. In this work, up-scaled dynamic voltage simulation and SOC estimator are described for the high power lithium ion cell (63Ah) used in parallel-series connection (2X108) to form the battery pack used in concept electric vehicle (EV) taxi ‘‘EVA‘‘ developed at TUM CREATE Singapore. Models are developed in offline platform with matlab/Simulink based on the aging experiments. Models are evaluated in realtime hardware in the loop (HIL) system and the interaction between HIL and experimental set up are described. Verified models are implemented on target microcontroller for small scale evaluation and BMS of the EV for large scale implementation in the final stage. Each individual cell affects the overall performance of the pack, to deal with this, single cell SOC estimation within the battery pack is considered critical feature of the BMS. Battery pack is the most expensive component of the EV and conducting aging experiments on the pack is very expensive and requires specific laboratory equipment, hence extensive experimental tests are performed on the cells level at various controlled ambient temperature to simulate different conditions for the cells which they will go through in real application. These experimental tests are also used to create reliable reference data under controlled laboratory conditions, cell parameterization, diagnostics and aging studies on the cells among all. Not all the cells in the battery pack are identical; external/internal influences lead to cell to cell discrepancies. These influences can be from slight manufacturing process differences, hot spots due to cell locations inside the pack, sudden failures among other influences causes different behavior between cells. Weakest cell in the pack dictates the charging and discharging limits and safety level of the battery pack. This is due to the fact that the weak cell charges faster among other cells and reaches it critical voltage/temperature values before other cells being charged and discharges faster due to less capacity compared to other cell. This work demonstrates the simulation method to estimate the SOC for individual cell among the battery pack and the overall battery pack SOC considering the cell to cell variations, surface temperature differences and aging influences of the cell. This method leads to battery utilization of the high storage system and safe and reliable operation of the cells and is beneficial as well in cell balancing applications as it will be shown that these variations can be as high as 5-10% capacity difference between two cells in the battery pack. Figure 1

A data-centric storage scheme for high storage utilization in wireless sensor networks

In wireless sensor networks, a data-centric storage (DCS) scheme is one of representative researches to store sensor readings and to process a query efficiently. The DCS scheme assigns distributed data regions to sensor nodes and stores sensor readings to the sensor node which is responsible for the data region to process the query efficiently. However, the existing DCS schemes have some drawbacks that the sensor nodes have the fixed ranges to store sensor readings. Because the ranges of the sensor readings change periodically in real world applications, the existing DCS schemes have problems that they use storage space unevenly in entire sensors and their network lifetimes are reduced. To overcome this problem, we propose a novel DCS scheme for high storage utilization in wireless sensor networks. The proposed scheme stores the sensed data equally in the entire sensor network to improve the storage utilization. To show the superiority of our proposed scheme, we compare it with the existing DCS schemes. Our experimental results show that our proposed scheme improves about 498 % storage utilization and about 377.7 % network lifetime over the existing schemes on average.

Courier: Multi-dimensional QoS guarantees for the consolidated storage system

The increasing cost and complexity of data management is driving data centers to consolidate resource and provide storage service for multiplex applications. Therefore, storage systems must be able to guarantee multi-dimensional Quality of Service (QoS) for various applications. However, satisfying performance targets for each workload is challenging, because that the I/O characteristics of workloads usually varies widely and capability of storage system changes significantly. In this paper, we design and implement a novel QoS scheduler, Courier, to maintain satisfactory performance for applications even in this highly-volatile scenario. Courier dynamically alternates between a feedback-based latency controller and reward budget-based scheduling to achieve per-application performance requirement. The feedback-based controller is employed to estimate request service times and adjust scheduling strategy dynamically. Based on the estimation, it can identify time-critical requests from throughput-sensitive requests and schedule applications with time-critical requests preferentially to avoid latency violations. In addition, Courier rewards well-behavior application with more budget to maintain high storage utilization while providing performance guarantees. We evaluate the effectiveness of our approach using synthetic and real workloads, and the results show that Courier has good ability to achieve per-application performance targets.

Application of Improved B+-Trees Algorithm in Embedded Database

B+-trees algorithm is a high efficient and common-used data organization algorithm in database system. But B+-trees algorithm has a disadvantage of low storage utilization. This disadvantage has a bad effect especially on embedded database systems, which have limit storage. To overcome this drawback, this paper presents an improved B+-trees algorithm, and applies it to an embedded database-Berkeley DB. Experimental results show that the improved B+-trees algorithm can attain higher storage utilization at the expense of more execution time than the conventional B+-trees algorithm.

SEF: A Secure, Efficient, and Flexible Range Query Scheme in Two-Tiered Sensor Networks

Large-scale wireless sensor networks follow the two-tiered architecture, where master nodes take charge of storing data and processing queries. However, if a master node is compromised, the information stored in it may be exposed, and query results can be juggled. This paper presents a novel scheme called SEF for secure range queries. To preserve privacy, SEF employs the order-preserving symmetric encryption which not only supports efficient range queries, but also maintains a strong security standard. To preserve authenticity and integrity of query results, we propose a novel data structure called Authenticity & Integrity tree. Moreover, SEF is flexible since it allows users to include or exclude the authenticity and integrity guarantee. To the best of our knowledge, this paper is the first to use the characteristic of NAND flash to achieve high storage utilization and query processing efficiency. The efficiency of the proposed scheme is demonstrated by experiments on real sensor platforms.

A new indexing method with high storage utilization and retrieval efficiency for large spatial databases

Storing and querying high-dimensional data are important problems in designing an information retrieval system. Two crucial issues, time and space efficiencies, must be considered when evaluating the performance of such a system. The KDB-tree and its variants have been reported to have good performance by using them as the index structure for retrieving multidimensional data. However, they all suffer from low storage utilization problem caused by imperfect “splitting policies.” Unnecessary splits increase the size of the index structure and deteriorate the performance of the system. In this paper, a new data insertion algorithm with a better splitting policy was proposed, which arranges data entries in the leaf nodes as many as possible. Our new index scheme can increase the storage utilization up to nearly 100% and reduce the index size to a smaller scale. As a result, both time and space efficiencies are significantly improved. Analytical and experimental results show that our indexing method outperforms the traditional KDB-tree and its variants.

Fast indexing and visualization of metric data sets using slim-trees

Many recent database applications need to deal with similarity queries. For such applications, it is important to measure the similarity between two objects using the distance between them. Focusing on this problem, this paper proposes the slim-tree, a new dynamic tree for organizing metric data sets in pages of fixed size. The slim-tree uses the triangle inequality to prune the distance calculations that are needed to answer similarity queries over objects in metric spaces. The proposed insertion algorithm uses new policies to select the nodes where incoming objects are stored. When a node overflows, the slim-tree uses a minimal spanning tree to help with the splitting. The new insertion algorithm leads to a tree with high storage utilization and improved query performance. The slim-tree is a metric access method that tackles the problem of overlaps between nodes in metric spaces and that allows one to minimize the overlap. The proposed is a way to quantify whether a given tree can be improved and also to compare two trees. We show how to use the fat-factor to achieve accurate estimates of the search performance and also how to improve the performance of a metric tree through the proposed algorithm. This paper also presents a new tool in the slim-tree's arsenal of resources, aimed at visualizing it. Visualization is a powerful tool for interactive data mining and for the visual tracking of the behavior of a tree under updates. Finally, we present a formula to estimate the number of disk accesses in range queries. Results from experiments with real and synthetic data sets show that the new slim-tree algorithms lead to performance improvements. These results show that the slim-tree outperforms the M-tree by up to 200% for range queries. For insertion and splitting, the minimal-spanning-tree-based algorithm achieves up to 40 times faster insertions. We observed improvements of up to 40% in range queries after applying the slim-down algorithm.

A New Indexing Scheme for Content-Based Image Retrieval

We propose a new efficient indexing scheme, called the HG-tree, to support content-based retrieval in image databases. Image content is represented by a point in a multidimensional feature space. The types of queries considered are the range query and the nearest-neighbor query, both in a multidimensional space. Our goals are twofold: increasing the storage utilization and decreasing the area covered by the directory regions of the index tree. The high storage utilization and the small directory area reduce the number of nodes that have to be touched during the query processing. The first goal is achieved by suppressing node splitting if possible, and when splitting is necessary, converting two nodes into three. This is done by proposing a good ordering on the directory nodes. The second goal is achieved by maintaining the area occupied by the directory region as small as possible. This is done by introducing the smallest interval that encloses all regions of the lower nodes. We note that there is a trade-off between the two design goals, but the HG-tree is so flexible that it can control the trade-off to some extent. We present the design of our indexing scheme and associated algorithms. In addition, we report the results of a series of tests, comparing the proposed index tree with the buddy-tree, which is one of the most successful point indexing schemes for a multidimensional space. The results show the superiority of our method.