Journal articles: 'Edge storage'

1

Cui, Huanqing, Yifan Wu, and Silin Lv. "Property Graph Partition Algorithm Based on Improved Barnacle Mating Optimization." Journal of Physics: Conference Series 2832, no. 1 (2024): 012005. http://dx.doi.org/10.1088/1742-6596/2832/1/012005.

Full text

Abstract:

Abstract Distributed graph processing systems have been used more frequently in various fields, and graph partitioning is the basis of these systems. Graph partitioning algorithms generally aim to minimize the communication cost while the number of vertices or edges reach the load balance. But the vertices and/or edges of property graphs require some storage volume, so the traditional graph partition algorithms will lead to an unbalanced storage volume load. This paper proposes an edge-cut graph partitioning algorithm to generate partitions with equal size and storage volume as well as low cut-edge ratio. Initially, it partitions the graph into k partitions with equal size and storage volume. It then migrates vertices based on the improved Barnacles mating optimizer. The experiments on real-world graphs show that the proposed algorithm can achieve the partition size of volume balance, and the cut-edge ratio is also very low.

APA, Harvard, Vancouver, ISO, and other styles

2

Yang, Yejin, Miao Ye, Qiuxiang Jiang, and Peng Wen. "A novel node selection method for wireless distributed edge storage based on SDN and a maldistributed decision model." Electronic Research Archive 32, no. 2 (2024): 1160–90. http://dx.doi.org/10.3934/era.2024056.

Full text

Abstract:

<abstract> In distributed edge storage, data storage data is allocated to network edge devices to achieve low latency, high security, and flexibility. However, traditional systems for distributed edge storage only consider individual factors, such as node capacity, while overlooking the network status and the load states of the storage nodes, thereby impacting the system's read and write performance. Moreover, these systems exhibit inadequate scalability in widely adopted wireless terminal application scenarios. To overcome these challenges, this paper introduces a software-defined edge storage model and a distributed edge storage architecture grounded in software-defined networking (SDN) and the Server Message Block (SMB) protocol. A data storage node selection and distribution algorithm is formulated based on a maldistributed decision model that comprehensively considers the network and storage node load states. A system prototype is implemented in combination with 5G wireless communication technology. The experimental results demonstrate that, in comparison to conventional distributed edge storage systems, the proposed wireless distributed edge storage system exhibits significantly enhanced performance under high load conditions, demonstrating superior scalability and adaptability. This approach effectively addresses the scalability limitation, rendering it suitable for edge scenarios in mobile applications and reducing hardware deployment costs. </abstract>

APA, Harvard, Vancouver, ISO, and other styles

3

Meng, Belinda Chong Chiew, Dayang Suhaida Awang Damit, and Nor Salwa Damanhuri. "Comparative studies of multiscale edge detection using different edge detectors for MRI thigh." Bulletin of Electrical Engineering and Informatics 10, no. 4 (2021): 1979–86. http://dx.doi.org/10.11591/eei.v10i4.2220.

Full text

Abstract:

Edge detection plays an important role in computer vision to extract object boundary. Multiscale edge detection method provides a variety of image features by different resolution at multiscale of edges. The method extracts coarse and fine structure edges simultaneously in an image. Due to this, the multiscale method enables more reliable edges are detected. Most of the multiscale methods are not translation invariant due to the decimated process. They mostly depend on the corresponding transform coefficients. These methods need more computation and a larger storage space. This study proposes a multiscale method that uses an average filter to smooth image at three different scales. Three different classical edge detectors namely Prewitt, Sobel and Laplacian were used to extract the edges from the smooth images. The edges extracted from the different scales of smooth images were then combined to form the multiscale edge detection. The performances of the multiscale images extracted from the three classical edge detectors were then compared and discussed.

APA, Harvard, Vancouver, ISO, and other styles

4

Belinda, Chong Chiew Meng, Suhaida Awang Damit Dayang, and Salwa Damanhuri Nor. "Comparative studies of multiscale edge detection using different edge detectors for MRI thigh." Bulletin of Electrical Engineering and Informatics 10, no. 4 (2021): 1979~1986. https://doi.org/10.11591/eei.v10i4.2220.

Full text

Abstract:

Edge detection plays an important role in computer vision to extract object boundary. Multiscale edge detection method provides a variety of image features by different resolution at multiscale of edges. The method extracts coarse and fine structure edges simultaneously in an image. Due to this, the multiscale method enables more reliable edges are detected. Most of the multiscale methods are not translation invariant due to the decimated process. They mostly depend on the corresponding transform coefficients. These methods need more computation and a larger storage space. This study proposes a multiscale method that uses an average filter to smooth image at three different scales. Three different classical edge detectors namely Prewitt, Sobel and Laplacian were used to extract the edges from the smooth images. The edges extracted from the different scales of smooth images were then combined to form the multiscale edge detection. The performances of the multiscale images extracted from the three classical edge detectors were then compared and discussed.

APA, Harvard, Vancouver, ISO, and other styles

5

M. Manideepsai, U. Vineeth Goud, CH. Vinay Goud, P. Vignesh Yadav, and D. Saidulu. "An Optimized Data Storage in A Secure Cloud-Edge Collaboration A Fault Tolerance Approach." International Journal of Scientific Research in Science, Engineering and Technology 11, no. 2 (2024): 355–62. http://dx.doi.org/10.32628/ijsrset2411255.

Full text

Abstract:

The rise of edge smart IoT devices has led to the development of edge storage systems (ESS) for efficient access to massive edge data. ESS can reduce the load on cloud centers and improve user experience. However, ESS still faces challenges in improving fault tolerance and efficiency. Thus, there is a need for a secure and efficient fault-tolerant storage scheme. Existing schemes have drawbacks like high edge storage overhead, difficulty in protecting edge data privacy, and low data writing performance. To address these issues, we propose a Hierarchical Cloud-Edge Collaborative Fault-Tolerant Storage (HCEFT) model. This model aims to enhance system robustness, reduce edge storage overhead, and ensure edge data privacy. We also introduce an optimization method for data writing in HCEFT, called ECWSS (Erasure Code data Writing method based on Steiner tree and SDN). This method improves the trade-off between data writing time and traffic consumption. Our scheme improves data robustness, availability, and security. Additionally, the writing optimization method reduces data write time by 13%-67% and network traffic consumption by 20%-62%, enhancing network load balance performance.

APA, Harvard, Vancouver, ISO, and other styles

6

Levenson, Marc D., Robert T. Lynch, and S. M. Tan. "Edge detection for magnetooptical data storage." Applied Optics 30, no. 2 (1991): 232. http://dx.doi.org/10.1364/ao.30.000232.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Du, Sixuan, Bo Zheng, Hangyu Lei, Huifeng Guo, and Xiang Li. "Response of Understory Plant Diversity to Edge Effects in Plantation Forests on the Loess Plateau." Forests 16, no. 1 (2025): 87. https://doi.org/10.3390/f16010087.

Full text

Abstract:

The majority of the world’s forests are located at landscape edges and are highly fragmented; the plantations on the Loess Plateau are no exception, experiencing pronounced edge effects. However, edge effects are often overlooked in assessments of carbon storage and biodiversity, and the extent and impact of these effects on Loess Plateau plantations remain inadequately understood. The objective of this study is to reveal how edge effects influence biodiversity and species composition and to examine their long-term impacts on ecosystem structure and function. Furthermore, it aims to explore the mechanisms underlying edge effects in plantation systems. Examining these effects is essential for guiding forest management practices and formulating effective biodiversity conservation strategies, thereby providing scientific insights to support the ecological restoration and sustainable management of plantations. In this study, we classified 44 sample plots into four groups according to their distances from the plantation edges to compare and analyze species composition. Additionally, we evaluated the intensity and range of edge effects on stand structure, species diversity, and carbon storage. The Shannon index of understory vegetation was used as the dependent variable, with canopy cover, edge distance, and stand density as independent variables. We used multiple linear regression to examine the effects of these factors on the Shannon index of understory vegetation (shrubs, herbs, and trees). The key findings were as follows: (1) Tree height did not exhibit edge effects across any distance range, while the Shannon index, species richness, and carbon storage showed edge effects within 54 m from the edge. Diameter at breast height (DBH), stand density, and canopy cover exhibited edge effects within 0–83 m from the edge. (2) The significance values for edge distance and canopy cover in the linear regression with the Shannon index were 0.99 and 0.51, respectively, showing no significant correlation. In contrast, stand density had a significant positive effect on the Shannon index (p = 0.03). (3) Notable differences in understory species composition were observed between the outermost and innermost groups of the plantation. Climatic conditions on the Loess Plateau exert a dominant influence on understory plants, altering species composition and abundance. High stand density appeared to moderate the microclimate, contributing to a higher understory Shannon index, but reducing carbon storage. Our findings suggest that the edge effects of plantation forests on the Loess Plateau exert varying degrees of influence on different indicators. Management decisions should be guided by the specific silvicultural objectives, whether the manager’s goals are to optimize biomass accumulation, enhance species recovery, or achieve a balance between these two goals.

APA, Harvard, Vancouver, ISO, and other styles

8

Vistro, Daniel Mago. "IoT based Big Data Analytics for Cloud Storage Using Edge Computing." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (2020): 1594–98. http://dx.doi.org/10.5373/jardcs/v12sp7/20202262.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Liu, Zehao. "Performance Comparison and Analysis of RAID-6 Encoding and Scaling in Edge Computing Environments." Highlights in Science, Engineering and Technology 87 (March 26, 2024): 17–22. http://dx.doi.org/10.54097/6hp0x463.

Full text

Abstract:

In today's world where cloud computing is widely used, edge computing is starting to be used as a new type of data computing and management service. This paper first describes the importance of data reliability and storage fault tolerance for edge computing operating in multiple environments, and then focuses on RAID-6 to address the data storage requirements of edge computing. In this paper, the feasibility of RAID-6 for edge computing is discussed and two different RAID-6 coding algorithms are introduced. The better option for edge computing is explored through performance comparison. Among the two RAID-6 coding algorithms, it is considered that Row-Diagonal parity will be more suitable than EVENODD code for edge computing scenarios through comparison. But perhaps there are better coding algorithms with lower complexity that can again improve the performance of edge computing storage systems. An edge computing storage system using RAID-6 architecture would be very beneficial for a wide range of real-world application scenarios.

APA, Harvard, Vancouver, ISO, and other styles

10

Linaje, Marino, Javier Berrocal, and Alfonso Galan-Benitez. "Mist and Edge Storage: Fair Storage Distribution in Sensor Networks." IEEE Access 7 (2019): 123860–76. http://dx.doi.org/10.1109/access.2019.2938443.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Xu, Rongxu, Lei Hang, Wenquan Jin, and Dohyeun Kim. "Distributed Secure Edge Computing Architecture Based on Blockchain for Real-Time Data Integrity in IoT Environments." Actuators 10, no. 8 (2021): 197. http://dx.doi.org/10.3390/act10080197.

Full text

Abstract:

The traditional cloud-based Internet of Things (IoT) architecture places extremely high demands on computers and storage on cloud servers. At the same time, the strong dependence on centralized servers causes major trust problems. Blockchain provides immutability, transparency, and data encryption based on safety to solve these problems of the IoT. In this paper, we present a distributed secure edge computing architecture using multiple data storages and blockchain agents for the real-time context data integrity in the IoT environment. The proposed distributed secure edge computing architecture provides reliable access and an unlimited repository for scalable and secure transactions. The architecture eliminates traditional centralized servers using an edge computing framework that represents cloud computing for computer and security issues. Also, blockchain-based edge computing-compatible IoT design is supported to achieve the level of security and scalability required for data integrity. Furthermore, we present the blockchain agent to provide internetworking between blockchain networks and edge computing. For experimenting with the proposed architecture in the IoT environment, we implement and perform a concrete IoT environment based on the EdgeX framework and Hyperledger Fabric. The evaluation results are collected by measuring the performance of the edge computing and blockchain platform based on service execution time to verify the proposed architecture in the IoT environment.

APA, Harvard, Vancouver, ISO, and other styles

12

Alblehai, Fahad. "A Caching-Based Pipelining Model for Improving the Input/Output Performance of Distributed Data Storage Systems." Journal of Nanoelectronics and Optoelectronics 17, no. 6 (2022): 946–57. http://dx.doi.org/10.1166/jno.2022.3269.

Full text

Abstract:

Distributed data storage requires swift input/output (I/O) processing features to prevent pipelines from balancing requests and responses. Unpredictable data streams and fetching intervals congest the data retrieval from distributed systems. To address this issue, in this article, a Coordinated Pipeline Caching Model (CPCM) is proposed. The proposed model distinguishes request and response pipelines for different intervals of time by reallocating them. The reallocation is performed using storage and service demand analysis; in the analysis, edge-assisted federated learning is utilized. The shared pipelining process is fetched from the connected edge devices to prevent input and output congestion. In pipeline allocation and storage management, the current data state and I/O responses are augmented by distributed edges. This prevents pipeline delays and aids storage optimization through replication mitigation. Therefore, the proposed model reduces the congestion rate (57.60%), replication ratio (59.90%), and waiting time (54.95%) and improves the response ratio (5.16%) and processing rate (74.25%) for different requests.

APA, Harvard, Vancouver, ISO, and other styles

13

Wang, Jiansi, Haopeng Chen, Fuxiao Zhou, Meng Sun, Ziang Huang, and Zhengtong Zhang. "A-DECS: Enhanced collaborative edge–edge data storage service for edge computing with adaptive prediction." Computer Networks 193 (July 2021): 108087. http://dx.doi.org/10.1016/j.comnet.2021.108087.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Dr.Trupti, Kaushiram Wable. "Design and Implementation of Collaborative Cloud-Edge System Using Raspberry Pi for Video Surveillance System with AIoT to Analyse Effective Performance Parameters of Network." Research and Applications: Emerging Technologies 6, no. 2 (2024): 30–35. https://doi.org/10.5281/zenodo.11607879.

Full text

Abstract:

The video surveillance can avoid many crimes as well as it will help to reduce crime rate in society as well we can save many lives. But currently implemented IoT system having various limitations like insufficient storage capacity and inadequate processing of information. Thus we can integrate traditional IoT system with Artificial Intelligence (AI) models to improve storage capacity & processing called as Artificial Intelligence of Things (AIoT). This system mainly focuses on performance parameter of video surveillance system the parameter consist of Response Latency Time, Network Bandwidth & Storage on server. In proposed system divided in two part, First part include Edge node implemented with Raspberry Pi as IoT system which having video input then it perform image processing & store output on edge node, second part include cloud node which is train with AI model as AI system to extract image and analyzed performance of system. So Cloud-Edge Collaborative system refers as Artificial Intelligence of Things (AIoT). In this research I conclude comparative study of traditional Cloud Computing System with Collaborative Cloud-Edge Computing system which shows that, the Response Latency Time improve by 5 times, Network Bandwidth improve by 10 times and storage capacity improve by 5 times of traditional Edge Computing System.

APA, Harvard, Vancouver, ISO, and other styles

15

Makris, Antonios, Ioannis Kontopoulos, Evangelos Psomakelis, Stylianos Nektarios Xyalis, Theodoros Theodoropoulos, and Konstantinos Tserpes. "Performance Analysis of Storage Systems in Edge Computing Infrastructures." Applied Sciences 12, no. 17 (2022): 8923. http://dx.doi.org/10.3390/app12178923.

Full text

Abstract:

Edge computing constitutes a promising paradigm of managing and processing the massive amounts of data generated by Internet of Things (IoT) devices. Data and computation are moved closer to the client, thus enabling latency- and bandwidth-sensitive applications. However, the distributed and heterogeneous nature of the edge as well as its limited resource capabilities pose several challenges in implementing or choosing an efficient edge-enabled storage system. Therefore, it is imperative for the research community to contribute to the clarification of the purposes and highlight the advantages and disadvantages of various edge-enabled storage systems. This work aspires to contribute toward this direction by presenting a performance analysis of three different storage systems, namely MinIO, BigchainDB, and the IPFS. We selected these three systems as they have been proven to be valid candidates for edge computing infrastructures. In addition, as the three evaluated systems belong to different types of storage, we evaluated a wide range of storage systems, increasing the variability of the results. The performance evaluation is performed using a set of resource utilization and Quality of Service (QoS) metrics. Each storage system is deployed and installed on a Raspberry Pi (small single-board computers), which serves as an edge device, able to optimize the overall efficiency with minimum power and minimum cost. The experimental results revealed that MinIO has the best overall performance regarding query response times, RAM consumption, disk IO time, and transaction rate. The results presented in this paper are intended for researchers in the field of edge computing and database systems.

APA, Harvard, Vancouver, ISO, and other styles

16

Boucher, Rod, and Paul Rodzianko. "Advanced pumped storage: The new competitive edge." Electricity Journal 7, no. 6 (1994): 48–53. http://dx.doi.org/10.1016/1040-6190(94)90184-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Bosch, R. A. "Edge radiation in an electron storage ring." Il Nuovo Cimento D 20, no. 4 (1998): 483–93. http://dx.doi.org/10.1007/bf03185543.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Khan, Imran Ahmed, and Mashhood Hasan. "Power Efficient Dual Edge-Triggered Storage Design." International Journal of Engineering and Technology 9, no. 2 (2017): 427–34. http://dx.doi.org/10.21817/ijet/2017/v9i2/170902323.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Beljakov, Igor, Velimir Meded, Franz Symalla, Karin Fink, Sam Shallcross, and Wolfgang Wenzel. "Magnetic anisotropy of graphene quantum dots decorated with a ruthenium adatom." Beilstein Journal of Nanotechnology 4 (July 10, 2013): 441–45. http://dx.doi.org/10.3762/bjnano.4.51.

Full text

Abstract:

The creation of magnetic storage devices by decoration of a graphene sheet by magnetic transition-metal adatoms, utilizing the high in-plane versus out-of-plane magnetic anisotropy energy (MAE), has recently been proposed. This concept is extended in our density-functional-based modeling study by incorporating the influence of the graphene edge on the MAE. We consider triangular graphene flakes with both armchair and zigzag edges in which a single ruthenium adatom is placed at symmetrically inequivalent positions. Depending on the edge-type, the graphene edge was found to influence the MAE in opposite ways: for the armchair flake the MAE increases close to the edge, while the opposite is true for the zigzag edge. Additionally, in-plane pinning of the magnetization direction perpendicular to the edge itself is observed for the first time.

APA, Harvard, Vancouver, ISO, and other styles

20

Rajesh, Ravula, and Ripon Patgiri. "Survey Based on Edge Structured File Systems in Edge Computing." Tehnički glasnik 19, no. 2 (2025): 305–12. https://doi.org/10.31803/tg-20240111081254.

Full text

Abstract:

Edge Structured File systems (ESFs) are distributed file systems designed to provide efficient and reliable storage solutions in edge computing environments. By employing distributed and decentralized designs, these file systems address specific challenges such as limited resources, inconsistent connectivity, and fluctuating network conditions, resulting in quicker access times, reduced latency, and enhanced resilience. ESFs adapt to dynamic edge settings through flexible data placement tactics, network congestion detection and resolution, and seamless integration with cloud-based storage systems. These techniques enable data portability and, when necessary, the outsourcing of computation-intensive operations to the cloud. Overall, edge-computing ecosystems rely on ESFs to deliver optimal performance, resilience, and data availability. The article discusses several studies on edge-structured file systems, highlighting their features and limitations of previous works. Furthermore, it identifies requirements and discusses research challenges in edge computing, laying the groundwork for future advancements in this rapidly evolving field. By providing insights into the state-of-the-art technologies, features, and limitations of ESFs, as well as their broader implications for edge computing, this article aims to offer valuable guidance to researchers, practitioners, and stakeholders interested in harnessing the full potential of edge computing technologies.

APA, Harvard, Vancouver, ISO, and other styles

21

Xue, Cunjin, Chengbin Wu, Jingyi Liu, and Fenzhen Su. "A Novel Process-Oriented Graph Storage for Dynamic Geographic Phenomena." ISPRS International Journal of Geo-Information 8, no. 2 (2019): 100. http://dx.doi.org/10.3390/ijgi8020100.

Full text

Abstract:

There exists a sort of dynamic geographic phenomenon in the real world that has a property which is maintained from production through development to death. Using traditional storage units, e.g., point, line, and polygon, researchers face great challenges in exploring the spatial evolution of dynamic phenomena during their lifespan. Thus, this paper proposes a process-oriented two-tier graph model named PoTGM to store the dynamic geographic phenomena. The core ideas of PoTGM are as follows. 1) A dynamic geographic phenomenon is abstracted into a process with a property that is maintained from production through development to death. A process consists of evolution sequences which include instantaneous states. 2) PoTGM integrates a process graph and a sequence graph using a node–edge structure, in which there are four types of nodes, i.e., a process node, a sequence node, a state node, and a linked node, as well as two types of edges, i.e., an including edge and an evolution edge. 3) A node stores an object, i.e., a process object, a sequence object, or a state object, and an edge stores a relationship, i.e., an including or evolution relationship between two objects. Experiments on simulated datasets are used to demonstrate an at least one order of magnitude advantage of PoTGM in relation to relationship querying and to compare it with the Oracle spatial database. The applications on the sea surface temperature remote sensing products in the Pacific Ocean show that PoTGM can effectively explore marine objects as well as spatial evolution, and these behaviors may provide new references for global change research.

APA, Harvard, Vancouver, ISO, and other styles

22

Zhong, Jiayong, and Xiaofu Xiong. "Data Security Storage Method for Power Distribution Internet of Things in Cyber-Physical Energy Systems." Wireless Communications and Mobile Computing 2021 (January 2, 2021): 1–15. http://dx.doi.org/10.1155/2021/6694729.

Full text

Abstract:

The existing cloud storage methods cannot meet the delay requirements of intelligent devices in the power distribution Internet of Things (IoT), and it is difficult to ensure the data security in the complex network environment. Therefore, a data Security Storage method for the power distribution IoT is proposed. Firstly, based on the “cloud tube edge end” power distribution IoT structure, a cloud edge collaborative centralized distributed joint control mode is proposed, which makes full use of the collaborative advantages of cloud computing and edge computing to meet the real-time requirements. Then, a distributed data storage method based on the Kademlia algorithm is proposed, and the homomorphic encryption and secret sharing algorithm are used to store the data in the cloud as ciphertext and perform data query directly on the ciphertext. Finally, considering the heterogeneity of edge nodes, the security protection model of edge nodes based on noncooperative differential game is established, and the algorithm of optimal defense strategy of edge nodes is designed to ensure the security of edge nodes. The experimental results show that the proposed method obtained excellent query performance, and the ability to resist network attacks is better than other comparison methods. It can reduce the data storage and query delay and ensure the data security of the system.

APA, Harvard, Vancouver, ISO, and other styles

23

Bansal, Malti, and Harshit. "IoT based Edge Computing." December 2020 2, no. 4 (2021): 204–10. http://dx.doi.org/10.36548/jtcsst.2020.4.005.

Full text

Abstract:

Edge computing is a new way of calculating where most computer and storage devices are located on the internet, near mobile devices, sensors, end users, and internet of things devices. This physical approach improves delays, bandwidth, trust and survival.

APA, Harvard, Vancouver, ISO, and other styles

24

Ajayi, Oluwashina Joseph, Joseph Rafferty, Jose Santos, Matias Garcia-Constantino, and Zhan Cui. "BECA: A Blockchain-Based Edge Computing Architecture for Internet of Things Systems." IoT 2, no. 4 (2021): 610–32. http://dx.doi.org/10.3390/iot2040031.

Full text

Abstract:

The scale of Internet of Things (IoT) systems has expanded in recent times and, in tandem with this, IoT solutions have developed symbiotic relationships with technologies, such as edge Computing. IoT has leveraged edge computing capabilities to improve the capabilities of IoT solutions, such as facilitating quick data retrieval, low latency response, and advanced computation, among others. However, in contrast with the benefits offered by edge computing capabilities, there are several detractors, such as centralized data storage, data ownership, privacy, data auditability, and security, which concern the IoT community. This study leveraged blockchain’s inherent capabilities, including distributed storage system, non-repudiation, privacy, security, and immutability, to provide a novel, advanced edge computing architecture for IoT systems. Specifically, this blockchain-based edge computing architecture addressed centralized data storage, data auditability, privacy, data ownership, and security. Following implementation, the performance of this solution was evaluated to quantify performance in terms of response time and resource utilization. The results show the viability of the proposed and implemented architecture, characterized by improved privacy, device data ownership, security, and data auditability while implementing decentralized storage.

APA, Harvard, Vancouver, ISO, and other styles

25

Byun, Siwoo. "Replicated Data Management Using Scaled Segment Chain in Unstable IoT Environments." Webology 19, no. 1 (2022): 4286–98. http://dx.doi.org/10.14704/web/v19i1/web19282.

Full text

Abstract:

IoT edge gateway reduces cloud computing's overload that redirect sensor data to remote servers. For reliable and efficient IoT gateway, column-based flash memory has become a reasonable storage due to its space efficiency and compression performance. This paper introduces recent IoT network and edge computing technology. It proposes efficient replication management called Context-mapped Segment Submirroring to support stable data services for sensor data in the edge-based IoT environment. Sensor context scaling and chained segment submirroring schemes are presented to improve the reliability and performance using IoT edge gateway. In the chained submirroring scheme, the sensor data are kept in the space-efficient storage of IoT edge. Consequently, sensor data transmission and mirroring storage cost can be minimized. The simulation results show that the proposed scheme outperforms the traditional scheme in respect of operation throughput and its response time.

APA, Harvard, Vancouver, ISO, and other styles

26

Wang, Tianyu, Jinyang Guo, Bowen Zhang, Ge Yang, and Dong Li. "Deploying AI on Edge: Advancement and Challenges in Edge Intelligence." Mathematics 13, no. 11 (2025): 1878. https://doi.org/10.3390/math13111878.

Full text

Abstract:

In recent years, artificial intelligence (AI) has achieved significant progress and remarkable advancements across various disciplines, including biology, computer science, and industry. However, the increasing complexity of AI network structures and the vast number of associated parameters impose substantial computational and storage demands, severely limiting the practical deployment of these models on resource-constrained edge devices. Although edge intelligence methods have been proposed to alleviate the computational and storage burdens, they still face multiple persistent challenges, such as large-scale model deployment, poor interpretability, privacy and security vulnerabilities, and energy efficiency constraints. This article systematically reviews the current advancements in edge intelligence technologies, highlights key enabling techniques including model sparsity, quantization, knowledge distillation, neural architecture search, and federated learning, and explores their applications in industrial, automotive, healthcare, and consumer domains. Furthermore, this paper presents a comparative analysis of these techniques, summarizes major trade-offs, and proposes decision frameworks to guide deployment strategies under different scenarios. Finally, it discusses future research directions to address the remaining technical bottlenecks and promote the practical and sustainable development of edge intelligence. Standing at the threshold of an exciting new era, we believe edge intelligence will play an increasingly critical role in transforming industries and enabling ubiquitous intelligent services.

APA, Harvard, Vancouver, ISO, and other styles

27

Wang, Chun Ping. "Study on Content Distribute Mechanism of Cloud Storage." Applied Mechanics and Materials 662 (October 2014): 263–66. http://dx.doi.org/10.4028/www.scientific.net/amm.662.263.

Full text

Abstract:

In this paper, the charging mechanism and content distribution mechanisms of cloud storage for analysis, given reasonable network topology and cost models. Suggestions for improvement heuristic cloud storage static content distribution genetic algorithm is put forward. Full account of the current network bandwidth, edge cloud storage node performance and historical visit value, since the convergence of the proposed probabilistic matching content distribution cloud storage load balancing technology, effectively balancing the load, while reducing the edge server response time.

APA, Harvard, Vancouver, ISO, and other styles

28

Sepulveda, Frank, Joseph Soloman Thangraj, and Jay Pulliam. "The Edge of Exploration: An Edge Storage and Computing Framework for Ambient Noise Seismic Interferometry Using Internet of Things Based Sensor Networks." Sensors 22, no. 10 (2022): 3615. http://dx.doi.org/10.3390/s22103615.

Full text

Abstract:

Recent technological advances have reduced the complexity and cost of developing sensor networks for remote environmental monitoring. However, the challenges of acquiring, transmitting, storing, and processing remote environmental data remain significant. The transmission of large volumes of sensor data to a centralized location (i.e., the cloud) burdens network resources, introduces latency and jitter, and can ultimately impact user experience. Edge computing has emerged as a paradigm in which substantial storage and computing resources are located at the “edge” of the network. In this paper, we present an edge storage and computing framework leveraging commercially available components organized in a tiered architecture and arranged in a hub-and-spoke topology. The framework includes a popular distributed database to support the acquisition, transmission, storage, and processing of Internet-of-Things-based sensor network data in a field setting. We present details regarding the architecture, distributed database, embedded systems, and topology used to implement an edge-based solution. Lastly, a real-world case study (i.e., seismic) is presented that leverages the edge storage and computing framework to acquire, transmit, store, and process millions of samples of data per hour.

APA, Harvard, Vancouver, ISO, and other styles

29

Balan, Harikishore Allu, and Bikash Agarwal. "Container Storage Solutions for Telecommunications Applications on Private Cloud." International Journal of Engineering and Computer Science 14, no. 06 (2025): 27249–58. https://doi.org/10.18535/ijecs.v14i06.5145.

Full text

Abstract:

The telecommunications industry is undergoing a significant transformation fueled by 5G, edge computing, and the adoption of cloud-native technologies. As telco workloads increasingly shift to private cloud environments, the role of storage becomes critical in ensuring performance, scalability, and reliability. From 5G core functions to real-time edge processing, telco applications demand high IOPS, low latency, and continuous availability—requirements that challenge traditional storage systems. This paper explores the capabilities of modern container storage solutions like Red Hat ODF (Ceph), Portworx, and Dell CSM, analyzing how they meet the stringent demands of telco workloads. By examining real-world scenarios, performance benchmarks, and operational behavior under stress, we offer guidance on selecting storage architectures that enable resilient, secure, and agile service delivery across centralized and edge deployments in private cloud infrastructures.

APA, Harvard, Vancouver, ISO, and other styles

30

Sonia, Farjana J., Manoj K. Jangid, Balakrishna Ananthoju, M. Aslam, Priya Johari, and Amartya Mukhopadhyay. "Understanding the Li-storage in few layers graphene with respect to bulk graphite: experimental, analytical and computational study." Journal of Materials Chemistry A 5, no. 18 (2017): 8662–79. http://dx.doi.org/10.1039/c7ta01978e.

Full text

Abstract:

Greater Li-capacity of well-ordered fairly pristine few layers graphene is due to combined contributions of ‘classical’ bulk Li-intercalation (up to LiC6) and surface storage, especially near the exposed ‘stepped’ edges of each graphene layer (but not exactly at the edge sites).

APA, Harvard, Vancouver, ISO, and other styles

31

Chenchen Han, Chenchen Han, Gwang-Jun Kim Chenchen Han, Osama Alfarraj Gwang-Jun Kim, Amr Tolba Osama Alfarraj, and Yongjun Ren Amr Tolba. "ZT-BDS: A Secure Blockchain-based Zero-trust Data Storage Scheme in 6G Edge IoT." 網際網路技術學刊 23, no. 2 (2022): 289–95. http://dx.doi.org/10.53106/160792642022032302009.

Full text

Abstract:

With the rapid development of 6G communication technology, data security of the Internet of Things (IoT) has become a key challenge. This paper first analyzes the security issues and risks of IoT data storage in 6G, and then constructs a blockchain-based zero-trust data storage scheme (ZT-BDS) in 6G edge IoT to ensure data security. Under this framework, an improved scratch-off puzzle based on Proof of Recoverability (PoR) is firstly constructed to realize distributed IoT data storage, which can reduce resource consumption compared with other existing schemes. Secondly, the accumulator is used to replace the Merkle trees to store IoT data in the blockchain. Since the accumulator can provide not only membership proof, but also non-membership proof, the proposed blockchain-based data storage scheme is more secure. Thirdly, PoW is replaced by an improved PoR scheme as the consensus protocol. On the one hand, PoR can verify the integrity of data, which will further enhance the security of IoT data; on the other hand, the proposed PoR is composed of polynomial commitment, which can reduce bandwidth with the aid of the aggregation function of polynomial commitment. Experimental comparisons show that our scheme has better bandwidth and storage capacity. &nbsp;

APA, Harvard, Vancouver, ISO, and other styles

32

Yuan, Liang, Qiang He, Feifei Chen, et al. "CSEdge: Enabling Collaborative Edge Storage for Multi-Access Edge Computing Based on Blockchain." IEEE Transactions on Parallel and Distributed Systems 33, no. 8 (2022): 1873–87. http://dx.doi.org/10.1109/tpds.2021.3131680.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

M. Al-Tuhafi, Ola, and Emad H. Al-Hemiary. "EDGE-TO-CLOUD ADAPTIVE OFFLOADING FOR NEXT-GENERATION SERVICES." Iraqi Journal of Information and Communication Technology 6, no. 2 (2023): 58–67. http://dx.doi.org/10.31987/ijict.6.2.230.

Full text

Abstract:

Due to the continuous growth of user traffic demands, there is a need to cope with the increased processing and storage requirements. The increased number of connected end devices causes a problem with carrying the generated loads efficiently. Edge and cloud computing and storage are real solutions to overcome the limitations of end devices on many prospective including computation capabilities, storage capabilities, and power consumption. Terminal devices offload their overflow tasks to the cloud for processing, analysis, and storage. This paper aims to improve computation offloading from edge nodes to the cloud in Internet of Things networks by making efficient decisions using an adaptive offloading algorithm. Offloading is controlled by a processing time offloading threshold value, which is determined automatically by edge nodes based on their traffic intensity and adaptively increased or decreased in loads. The proposed algorithm had been programmed and simulated; experimental evaluations show that the proposed adaptive offloading algorithm minimizes the edge mean response time by up to 58% and the cloud mean response time by up to 25% compared to the existing fixed, pre-defined offloading threshold value.

APA, Harvard, Vancouver, ISO, and other styles

34

Peng, Chubing, M. Mansuripur, W. M. Kim, and S. G. Kim. "Edge detection in phase-change optical data storage." Applied Physics Letters 71, no. 15 (1997): 2088–90. http://dx.doi.org/10.1063/1.119350.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Smolyakov, N. V., and A. Hiraya. "Study of edge radiation at HiSOR storage ring." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 543, no. 1 (2005): 51–54. http://dx.doi.org/10.1016/j.nima.2005.01.112.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Liang, Lixin, Huan He, Jian Zhao, Chengjian Liu, Qiuming Luo, and Xiaowen Chu. "An Erasure-Coded Storage System for Edge Computing." IEEE Access 8 (2020): 96271–83. http://dx.doi.org/10.1109/access.2020.2995973.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Xie, Zhanyuan, and Wei Chen. "Storage-Efficient Edge Caching With Asynchronous User Requests." IEEE Transactions on Cognitive Communications and Networking 6, no. 1 (2020): 229–41. http://dx.doi.org/10.1109/tccn.2019.2954391.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Hunter, P. "Network attached storage: no longer on the edge." Information Professional 3, no. 5 (2006): 35–38. http://dx.doi.org/10.1049/inp:20060504.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Chubar, O. V., and N. V. Smolyakov. "VUV range edge radiation in electron storage rings." Journal of Optics 24, no. 3 (1993): 117–21. http://dx.doi.org/10.1088/0150-536x/24/3/004.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Jiang, Guangshen, Xiaosa Xu, Haojie Han, et al. "Edge-enriched MoS2 for kinetics-enhanced potassium storage." Nano Research 13, no. 10 (2020): 2763–69. http://dx.doi.org/10.1007/s12274-020-2925-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Stock, A. M., G. Herl, T. Sauer, and J. Hiller. "Edge-preserving compression of CT scans using wavelets." Insight - Non-Destructive Testing and Condition Monitoring 62, no. 6 (2020): 345–51. http://dx.doi.org/10.1784/insi.2020.62.6.345.

Full text

Abstract:

This work addresses the subject of efficient storage of computed tomography (CT) data with an emphasis on the quality of surfaces. Industrial dimensional metrology often requires high measurement accuracy and it is shown that this is retained using wavelet-based compression methods. The applied techniques include a tensor product wavelet transform and soft wavelet shrinkage. In these tests, performed on real objects, dimensional CT measurements of compressed and uncompressed volumes were compared. The necessary storage space was reduced significantly with a negligible loss of accuracy. The storage space required for a multi-sphere phantom was decreased to 4.7% (from 638 MB to 30 MB), with an average deviation below 1 μm from the original volume.

APA, Harvard, Vancouver, ISO, and other styles

42

Wang, Guangming, and Yifeng Wang. "Innovative Marketing Framework for Enterprises Using Edge-Enabled Data Analysis." Mobile Information Systems 2021 (February 6, 2021): 1–8. http://dx.doi.org/10.1155/2021/6699420.

Full text

Abstract:

An effective marketing strategy has become a challenging task with the development of the social economy for the reform and innovation of many domestic and foreign enterprises. The idea of edge computing is also gaining prominence and is broadly recognized. Edge-enabled solutions provide computing, analysis, storage, and control nearer to the edge of the network. The existing literature highlights the concepts of social media marketing and evaluates the advantages of social media for communication between individuals and companies. However, there is a lack of an effective marketing strategy for enterprises. This article proposes an innovative marketing framework for enterprises using data analysis and wireless networks. The proposed framework is composed of two different modules. Initially, a corporate innovation and marketing framework module is established through edge computing to carry out a wireless transmission of relevant data and information at the edges of the network. Later, the enterprise marketing resource optimization module is constructed based on the particle swarm algorithm. The proposed framework performs efficient calculation and storage using a resource optimization module. The feasibility and effectiveness of the proposed framework are verified using the analysis of the actual case test results. This proposed framework can effectively improve the innovation efficiency level of existing enterprises and the optimization of marketing management resources.

APA, Harvard, Vancouver, ISO, and other styles

43

Javed, Muhammad Umar, Mubariz Rehman, Nadeem Javaid, Abdulaziz Aldegheishem, Nabil Alrajeh, and Muhammad Tahir. "Blockchain-Based Secure Data Storage for Distributed Vehicular Networks." Applied Sciences 10, no. 6 (2020): 2011. http://dx.doi.org/10.3390/app10062011.

Full text

Abstract:

In this paper, a blockchain-based secure data sharing mechanism is proposed for Vehicular Networks (VNs). Edge service providers are introduced along with ordinary nodes to efficiently manage service provisioning. The edge service providers are placed in the neighborhood of the ordinary nodes to ensure smooth communication between them. The huge amount of data generated by smart vehicles is stored in a distributed file storage system, known as Interplanetary File System (IPFS). It is used to tackle the issues related to data storage in centralized architectures, such as data tampering, lack of privacy, vulnerability to hackers, etc. Monetary incentives are given to edge vehicle nodes to motivate them for accurate and timely service provisioning to ordinary nodes. In response, ordinary nodes give reviews to the edge nodes against the services provided by them, which are further stored in a blockchain to ensure integrity, security and transparency. Smart contracts are used to automate the system processes without the inclusion of an intermediate party and to check the reviews given to the edge nodes. To optimize gas consumption and to enhance the system performance, a Proof of Authority (PoA) consensus mechanism is used to validate the transactions. Moreover, a caching system is introduced at the edge nodes to store frequently used services. Furthermore, both security and privacy are enhanced in the proposed system by incorporating a symmetric key cryptographic mechanism. A trust management mechanism is also proposed in this work to calculate the nodes’ reputation values based upon their trust values. These values determine the authenticity of the nodes involved in the network. Eventually, it is concluded from the simulation results that the proposed system is efficient for VNs.

APA, Harvard, Vancouver, ISO, and other styles

44

Xu, Rongxu, Wenquan Jin, Yonggeun Hong, and Do-Hyeun Kim. "Intelligent Optimization Mechanism Based on an Objective Function for Efficient Home Appliances Control in an Embedded Edge Platform." Electronics 10, no. 12 (2021): 1460. http://dx.doi.org/10.3390/electronics10121460.

Full text

Abstract:

In recent years the ever-expanding internet of things (IoT) is becoming more empowered to revolutionize our world with the advent of cutting-edge features and intelligence in an IoT ecosystem. Thanks to the development of the IoT, researchers have devoted themselves to technologies that convert a conventional home into an intelligent occupants-aware place to manage electric resources with autonomous devices to deal with excess energy consumption and providing a comfortable living environment. There are studies to supplement the innate shortcomings of the IoT and improve intelligence by using cloud computing and machine learning. However, the machine learning-based autonomous control devices lack flexibility, and cloud computing is challenging with latency and security. In this paper, we propose a rule-based optimization mechanism on an embedded edge platform to provide dynamic home appliance control and advanced intelligence in a smart home. To provide actional control ability, we design and developed a rule-based objective function in the EdgeX edge computing platform to control the temperature states of the smart home. Compared to cloud computing, edge computing can provide faster response and higher quality of services. The edge computing paradigm provides better analysis, processing, and storage abilities to the data generated from the IoT sensors to enhance the capability of IoT devices concerning computing, storage, and network resources. In order to satisfy the paradigm of distributed edge computing, all the services are implemented as microservices. The microservices are connected to each other through REST APIs based on the constrained IoT devices to provide all the functionalities that accomplish a trade-off between energy consumption and occupant-desired environment setting for the smart home appliances. We simulated our proposed system to control the temperature of a smart home; through experimental findings, we investigated the application against the delay time and overall memory consumption by the embedded edge system of EdgeX. The result of this research work suggests that the implemented services operated efficiently in the raspberry pi 3 hardware of IoT devices.

APA, Harvard, Vancouver, ISO, and other styles

45

Odunayo Josephine Akindote, Abimbola Oluwatoyin Adegbite, Samuel Onimisi Dawodu, Adedolapo Omotosho, and Anthony Anyanwu. "INNOVATION IN DATA STORAGE TECHNOLOGIES: FROM CLOUD COMPUTING TO EDGE COMPUTING." Computer Science & IT Research Journal 4, no. 3 (2023): 273–99. http://dx.doi.org/10.51594/csitrj.v4i3.661.

Full text

Abstract:

In an era where data is the new gold, understanding the evolution and future trajectory of data storage technologies is crucial. This paper delves into the transformative journey from traditional storage methods to contemporary paradigms like cloud and edge computing, underpinned by the burgeoning influence of Big Data, IoT, AI, and machine learning. The study's aim is to provide a comprehensive analysis of these technologies, assessing their development, efficacy, and the challenges they face in meeting the escalating demands of data storage. The methodology employed is a meticulous synthesis of literature reviews, case studies, and comparative analyses. This approach facilitates an in-depth exploration of the historical evolution of data storage, the paradigm shifts from cloud to edge computing, and the interplay between technological advancements and user demands. The study also scrutinizes the security concerns inherent in these technologies and identifies strategic directions for future research. Key findings reveal that while cloud computing has revolutionized data storage with its scalability and flexibility, edge computing emerges as a vital solution to latency and bandwidth limitations. The integration of AI and machine learning is identified as a pivotal factor in enhancing the efficiency and intelligence of data storage systems. However, this integration presents unique challenges, necessitating innovative solutions. Conclusively, the study recommends a continued focus on innovation in data storage technologies, emphasizing the development of integrated, secure, and efficient solutions. Future research should particularly explore the potential of AI and machine learning in overcoming current limitations. The paper's scope encompasses a comprehensive overview of the current state and future potential of data storage technologies, making it a valuable resource for researchers, technologists, and policymakers in the field. Keywords: Data Storage Technologies, Cloud Computing, Edge Computing, Big Data, Internet of Things (IoT), Artificial Intelligence (AI).

APA, Harvard, Vancouver, ISO, and other styles

46

MIURA, YOSHIMASA. "Cutting edge of the Information Storage Technologies. Information Storage Technology for IT Era." Journal of the Institute of Electrical Engineers of Japan 122, no. 4 (2002): 216–18. http://dx.doi.org/10.1541/ieejjournal.122.216.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Y., Ameer Hamza, Kranthi Kumar, Ch Rajini, and Mahesh Chandrashekar. "A Concurrent Computing Model for Fog Assisted Edge Network Applications." International Innovative Research Journal of Engineering and Technology 8, no. 3 (2023): 17–24. http://dx.doi.org/10.32595/iirjet.org/v8i3.2023.170.

Full text

Abstract:

The Fog Computing paradigm is designed to improve the feasibility of service provisioning in the local network applications. This paradigm is proficient in granting services, computations, storage, and communication features for heterogeneous devices. By this consideration, this paper discusses a novel proposal of proliferating computing model (PCM) for improving the robustness in storage level processing. The proposed model makes use of deep learning techniques for improving the concurrency in storage level processing for data storage and access. The learning classifies the functions of requesting and responding devices to improve the rate of data handling along with latency-less processing. This helps to improve the rate of processing by reducing the time along with response rate and less overhead.

APA, Harvard, Vancouver, ISO, and other styles

48

Barron, Alfredo, Dante D. Sanchez-Gallegos, Diana Carrizales-Espinoza, J. L. Gonzalez-Compean, and Miguel Morales-Sandoval. "On the Efficient Delivery and Storage of IoT Data in Edge–Fog–Cloud Environments." Sensors 22, no. 18 (2022): 7016. http://dx.doi.org/10.3390/s22187016.

Full text

Abstract:

Cloud storage has become a keystone for organizations to manage large volumes of data produced by sensors at the edge as well as information produced by deep and machine learning applications. Nevertheless, the latency produced by geographic distributed systems deployed on any of the edge, the fog, or the cloud, leads to delays that are observed by end-users in the form of high response times. In this paper, we present an efficient scheme for the management and storage of Internet of Thing (IoT) data in edge–fog–cloud environments. In our proposal, entities called data containers are coupled, in a logical manner, with nano/microservices deployed on any of the edge, the fog, or the cloud. The data containers implement a hierarchical cache file system including storage levels such as in-memory, file system, and cloud services for transparently managing the input/output data operations produced by nano/microservices (e.g., a sensor hub collecting data from sensors at the edge or machine learning applications processing data at the edge). Data containers are interconnected through a secure and efficient content delivery network, which transparently and automatically performs the continuous delivery of data through the edge–fog–cloud. A prototype of our proposed scheme was implemented and evaluated in a case study based on the management of electrocardiogram sensor data. The obtained results reveal the suitability and efficiency of the proposed scheme.

APA, Harvard, Vancouver, ISO, and other styles

49

Badahun Kharumnuid, Steffy Liza Kharmuti, and Lenin Thingbaijam. "The Evolution of Edge Computing in a Data-Driven World." International Research Journal on Advanced Engineering and Management (IRJAEM) 2, no. 10 (2024): 3238–50. http://dx.doi.org/10.47392/irjaem.2024.0477.

Full text

Abstract:

Edge computing is revolutionizing data processing and storage by bringing computational and data storage facilities closer to the data sources. This technique tackles the challenges faced by conventional clouds such as high latency and network congestion by employing the concept of data processed at the edge of the network in real-time. This paper discusses the edge computing paradigm and its evolution by covering the relevant concepts, benefits and trends that are changing within various industries. In particular, we assess the factors that make edge computing beneficial in terms of security, performance and efficiency concerns in smart cities, self-driving cars and internet of things (IoT) industries. This paper also reviews and reflects on the challenges of edge computing in terms of security, interoperability and scalability issues and how it can be overcome by integrating edge computing with fog computing, 5G and artificial intelligence (AI).

APA, Harvard, Vancouver, ISO, and other styles

50

Xiao, Chuqiao, Xueqing Gong, Yefeng Xia, and Qian Zhang. "PB: A Product-Bitmatrix Construction to Reduce the Complexity of XOR Operations of PM-MSR and PM-MBR Codes over GF 2 w." Security and Communication Networks 2021 (January 29, 2021): 1–18. http://dx.doi.org/10.1155/2021/6642121.

Full text

Abstract:

Edge computing, as an emerging computing paradigm, aims to reduce network bandwidth transmission overhead while storing and processing data on edge nodes. However, the storage strategies required for edge nodes are different from those for existing data centers. Erasure code (EC) strategies have been applied in some decentralized storage systems to ensure the privacy and security of data storage. Product-matrix (PM) regenerating codes (RGCs) as a state-of-the-art EC family are designed to minimize the repair bandwidth overhead or minimize the storage overhead. Nevertheless, the high complexity of the PM framework contains more finite-domain multiplication operations than classical ECs, which heavily consumes computational resources at the edge nodes. In this paper, a theoretical derivation of each step of the PM minimum storage regeneration (PM-MSR) and PM minimum bandwidth regeneration (PM-MBR) codes is performed and the XOR complexity over finite fields is analyzed. On this basis, a new construct called product bitmatrix (PB) is designed to reduce the complexity of XOR operations in the PM framework, and two heuristics are used to further reduce the XOR numbers of the PB-MSR and PB-MBR codes, respectively. The evaluation results show that the PB construction significantly reduces the XOR number compared to the PM-MSR, PM-MBR, Reed–Solomon (RS), and Cauchy RS codes while retaining optimal performance and reliability.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Edge storage'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles