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Query optimization-oriented lateral expansion method of distributed geological borehole database

OPEN GEOSCIENCES 2023年第1期15卷

作者： Luo, Qingjia Jiangmen Polytech Sch Informat Engn Jiangmen 529090 Peoples R China

In order to reduce the resource occupancy and retrieval efficiency of geological drilling databases, this study proposes a distributed horizontal expansion method for query optimization of geological drilling databases by constructing a comprehensive geological data subtree, analyzing the characteristics of distributed databases and elements in geological databases, and quickly retrieving data resources based on element attributes. In addition, this study has designed a method to horizontally extend the database designed for drilling holes using a multi-constraint model in order to achieve extension optimization of the distributed geological drilling database. Experiments are conducted to verify the performance and applicability of the proposed method. The experiment shows that when the geological data capacity is 80 GB, the capacity level of the geological database can be extended to 41 x 105TB using the method proposed in this study. The retrieval efficiency is higher than 89% and the resource occupancy rate is lower than 12% after the horizontal expansion of the database. By using this research method, the horizontal expansion of the geological drilling database is more effective, and can effectively reduce the resource occupancy rate and retrieval efficiency of the geological drilling databases. This has value significance for geological drilling with efficiency improvement and development.

关键词： query optimization multiple constraint model geological data subtree distributed database

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Query Optimization of distributed database Based on Parallel Genetic Algorithm and Max-Min Ant System

Query Optimization of Distributed Database Based on Parallel...

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International Symposium on Computational Intelligence and Design

作者： Wenjiao Ban Jiming Lin Jichao Tong Shiwen Li College of Information and Communication Guilin University of Electronic Technology Guilin 541004 China

ISBN: (纸本)9781467395885

Since the era of big data is coming, the first important problem is how to enhance the speed of database query. For the query optimization of distributed database, the speed of query depends on the data transfer and order of join. The cost model minimizing communication cost is the emphasis of research. Parallel Genetic Algorithm-Max-Min Ant System was proposed to seek a best query execution plan, which combines faster convergence of Genetic Algorithm, globally search ability of Max-Min Ant System and parallel property of both them. The experiment results show that the proposed algorithm is effective for query processing of multi-join, and plays important role in improving the performance of distributed database.

关键词： distributed database Genetic Algorithm Max-Min Ant System query execution plan parallel

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Data Storage Management in a distributed database with Deterministic Limited Communications Windows Between Data Storage Nodes

Data Storage Management in a Distributed Database with Deter...

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Conference on Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XIII

作者： Straub, Jeremy Univ N Dakota Dept Comp Sci Grand Forks ND 58202 USA

ISBN: (纸本)9781628410112

An orbital service model allows data to be collected, stored and used on different nodes comprising an ad-hoc system where provider craft supply services to consumer craft. Ad-hoc networks and provider-consumer relationships are commonly used in various applications on Earth. The deterministic movement of spacecraft, however, allows the ad-hoc network and service providing model to operate in a different way than would be typical in most terrestrial ad-hoc networks. While long periods of no direct node-to-node connectivity may exist, the periods of connectivity are pre-known based on orbital parameters. Additionally, paths for indirect connectivity can be identified and evaluated for cost effectiveness. This paper presents a data management approach for an orbital computing ad-hoc system. Algorithms for determining where data should be stored (identification of most useful point of storage, whether multiple copies are justified) and how movement should be affected (transfer scheduling, replication, etc.) are presented and evaluated.

关键词： Orbital services data storage management distributed database orbital environment data storage

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Application on query of distributed database Based on Improved Genetic Algorithm

Application on query of Distributed Database Based on Improv...

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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Chen Fuxing Xie Xusheng Jiangxi Normal Univ Coll Comp Informat Engn Nanchang Peoples R China

ISBN: (纸本)9783038351153

The query cost usually as an important criterion for a distributed database. The genetic algorithm is an adaptive probabilistic search algorithm, but the crossover and mutation probability usually keep a probability in traditional genetic algorithm. If the crossover probability keep a large value, the possibility of damage for genetic algorithm model is greater;In turn, if the crossover probability keep a small value, the search process will transform a slow processing or even stagnating. If the mutation probability keep a small value, a new individual can be reproduced difficultly;In turn, if the mutation probability keep a large value, the genetic algorithm will as a Pure random search algorithm. To solve this problem, proposed a improved genetic algorithm that multiple possibility of crossover and mutation based on k-means clustering algorithm. The experiment results indicate that the algorithm is effective.

关键词： distributed database genetic algorithm distributed query optimization k-means clustering algorithm

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Too-Short-Arc Association and Clustering Method for Space-Based Optical Observations

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2025年第1期48卷 84-97页

作者： Li, Jiasheng Yang, Zhen Luo, Yazhong Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Peoples R China Natl Univ Def Technol Hunan Key Lab Intelligent Planning & Simulat Aeros Changsha 410073 Peoples R China

Space-based optical observation is assuming an increasingly significant role in space surveillance and tracking. However, it often yields tracks that are too short, which are known as too short arcs (TSAs). A single TSA lacks sufficient information for reliable initial orbit determination of a resident space object. Therefore, it is typically necessary to perform tracklet association during catalog building and maintenance. This study presents a novel tracklet association method that improves upon existing techniques by combining admissible regions and nonlinear orbital uncertainty propagation. Proceeding by constructing TSA association matrices and TSA clustering matrices, the bond energy algorithm, traditionally employed in the design of distributed database systems, is applied to cluster TSAs based on the association results between two arbitrary TSAs. Furthermore, the proposed splitting algorithm reduces the computational load associated with clustering multiple tracklets and effectively handles erroneous association results. To assess the effectiveness of this approach, it was tested in a space-based optical-survey scenario, accounting for practical observation uncertainties. The simulation results demonstrate that the method achieves a high level of accuracy in both TSA association and clustering.

关键词： Geosynchronous Earth Orbit Orbit Determination distributed database Space Science and Technology Planets Satellites Specific Angular Momentum Orbital Property RADAR Sun Synchronous Orbit

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A1: A distributed In-Memory Graph database 20

A1: A Distributed In-Memory Graph Database

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ACM SIGMOD International Conference on Management of Data (SIGMOD)

作者： Buragohain, Chiranjeeb Risvik, Knut Magne Brett, Paul Castro, Miguel Cho, Wonhee Cowhig, Joshua Gloy, Nikolas Kalyanaraman, Karthik Khanna, Richendra Pao, John Renzelmann, Matthew Shamis, Alex Tan, Timothy Zheng, Shuheng Microsoft Redmond WA 98052 USA

ISBN: (纸本)9781450367356

A1 is an in-memory distributed database used by the Bing search engine to support complex queries over structured data. The key enablers for A1 are availability of cheap DRAM and high speed RDMA (Remote Direct Memory Access) networking in commodity hardware. A1 uses FaRM [11, 12] as its underlying storage layer and builds the graph abstraction and query engine on top. The combination of in-memory storage and RDMA access requires rethinking how data is allocated, organized and queried in a large distributed system. A single A1 cluster can store tens of billions of vertices and edges and support a throughput of 350+ million of vertex reads per second with end to end query latency in single digit milliseconds. In this paper we describe the A1 data model, RDMA optimized data structures and query execution.

关键词： in-memory database graph database distributed database RDMA graph query processing

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An Improved blockchain-based secure medical record sharing scheme

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2024年第6期27卷 7981-8000页

作者： Bodur, Hueseyin Al Yaseen, Imad Fakhri Taha Duzce Univ Dept Comp Engn TR-81000 Duzce Turkiye

Today, the confidentiality and security of patient medical records is of great importance. This study proposes a scheme that aims to store, access, and share medical data without risking security vulnerabilities and attacks. In the proposed scheme, medical data are divided into sensitive and non-sensitive patient data. Three consensus mechanisms (Proof of Work (PoW), Proof of Stake (PoS), and Proof of Authority (PoA)) are implemented and compared to each other in terms of performance. The performance analysis of the proposed scheme shows that PoW provides approximately 21% and 9% better results than PoA and PoS for non-sensitive data in terms of block size, respectively. It also provides approximately 23% and 32% better results than PoA and PoS for sensitive data in terms of memory usage, respectively. The security analysis demonstrates that it has many security features and is strong against man-in-the-middle, impersonation, and modification attacks.

关键词： Electronic medical records (EMRs) Healthcare Blockchain Consensus mechanisms distributed database Security

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CoralDB: A Collaborative database for Data Sharing Based on Permissioned Blockchain

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2024年第9期23卷 8886-8901页

作者： Li, Weimin Tian, Weihong Yan, Zhengmao Li, Zitong Gao, Jie Wu, Fan Liu, Jianxun Chen, Wenxiong Ren, Ju Hunan Univ Humanities Sci & Technol Sch Informat Loudi 417000 Peoples R China Carleton Univ Sch Informat Technol Ottawa ON K1S 5B6 Canada Cent South Univ Sch Comp Sci & Engn Changsha 410083 Peoples R China Hunan Normal Univ Coll Informat Sci & Engn Changsha 410081 Hunan Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing 10084 Peoples R China

Systems that integrate distributed databases and existing blockchain platforms have recently emerged, which conveniently leverage their respective strengths to build efficient, secure, and usable data sharing and collaboration environments for different organizations. However, the performance of such systems can be limited by the native blockchain platforms due to the high latency of transactions. In this article, we present CoralDB, a bottom-up fully redesigned hybrid system of blockchain and database, aimed at enabling untrusted organizations to collaborate and share data efficiently and securely at the database level. The storage layer of CoralDB ensures data security and system throughput through key modules such as customized block structure, consensus mechanism, and transaction pool. On top of the storage layer, a database layer is introduced, which extends the blockchain of the storage layer by incorporating connection pools, collaborative tables, and query interfaces, to enhance the usability and efficiency of data collaboration and sharing. Extensive experimental results demonstrate that CoralDB provides security assurances at the level of blockchain and enables efficient decentralized data collaboration and sharing.

关键词： Blockchain data collaboration data sharing distributed database efficiency security Blockchain data collaboration data sharing distributed database efficiency security

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Dodo: A scalable optimistic deterministic concurrency control protocol

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2024年 159卷 15-26页

作者： Wang, Xinyuan Peng, Yun Huang, Hejiao Li, Xingchen Harbin Inst Technol Shenzhen Shenzhen 518071 Guangdong Peoples R China Guangzhou Univ Guangzhou 510006 Guangdong Peoples R China

Deterministic concurrency control is able to avoid the expensive two-phase commit in distributed databases and can solve the single -thread bottleneck of transaction processing in blockchain systems. Most existing deterministic concurrency control protocols rely on prior knowledge of the transaction's read-write set, which is impractical in most cases. The state-of-the-art deterministic concurrency control protocols Aria and DOCC break this limitation. However, they do not perform well in multi -node and multi -core scalability. To solve the scalability issues, we propose Dodo, a novel deterministic concurrency control protocol. Dodo processes transactions in multi -batches, and each batch is divided into three phases. In the first phase, transactions are executed as read committed and staged. In the second phase, transactions are validated for the read-write conflict. In the third phase, only the continuous un-conflicted transactions at the head of the batch can be committed. For the aborted transaction that will be rerun in the next batch, we utilize its write set in the previous execution to reduce the read-write conflicts in the next batch. In this way, Dodo has the following benefits. First, Dodo does not rely on the prior knowledge of the read-write set. Second, Dodo commits transactions in pre -determined orders (TIDs) providing high multi -node scalability. Third, Dodo runs transactions in each phase concurrently, and the aborted transactions are re -executed in a conflict -less manner, enabling high multi -core scalability. Besides, we propose two optimism -based improvements, lazy decision and early -write visibility, to reduce aborts and blocking. Our evaluation shows that Dodo outperforms Aria and DOCC by up to 16.5x and 8.0x in a single -node setting and scales well in a multi -node setting.

关键词： Deterministic concurrency control Transaction processing distributed database Scalability

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Aion: Live Migration for In-Memory databases with Zero Downtime and Reduced Redundant Data Transfer

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DATA SCIENCE AND ENGINEERING 2025年 1-18页

作者： Cao, Huijie Huang, Chenfeng Liu, Shengchi Hu, Huiqi Zhao, Minghao Zhou, Xuan Tu, Yaofeng Qian, Weining East China Normal Univ Sch Data Sci & Engn Shanghai Peoples R China ZTE Corp Nanjing Branch Nanjing 210012 Peoples R China East China Normal Univ Sch Data Sci & Engn Engn Res Ctr Blockchain Data Management Minist Educ Shanghai Peoples R China

distributed in-memory databases are widely adopted to achieve low latency and high bandwidth for data-intensive applications. They support scale-out by sharding and distributing data across multiple nodes. To efficiently adapt to various workloads, distributed in-memory databases must be capable of migrating shards across nodes. In this paper, we demonstrate that state-of-the-art approaches experience significant performance degradation during migration due to service downtime and redundant data transfer. Furthermore, our findings indicate that the presence of service downtime constrains the scalability of migration strategies, while the transfer of redundant data during the snapshot transfer phase limits their adaptability to dynamic workloads. To this end, this paper proposes Aion, a live migration strategy designed for distributed in-memory databases. Aion eliminates any potential service downtime by immediately switching transaction routing to the destination node. To ensure data consistency between the source and destination nodes, as well as serializable execution during migration, Aion proposes the mutual validation phase. Moreover, Aion introduces an analysis phase before the snapshot transfer phase to identify dynamically changing hotspots in workloads. The analysis phase identifies and transfers tuples and versions accessed less frequently to the destination node, reducing the amount of data transferred. Aion is implemented on a distributed in-memory database and evaluated using various OLTP workloads. The results demonstrate that Aion can fundamentally eliminate service downtime, adapt effectively to various workloads and exhibit robust scalability. Compared to state-of-the-art approaches, Aion achieves up to 2.25x-6.57x higher throughput during migration and shortens the migration duration by 53.7-68.2%.

关键词： Live migration In-memory database Concurrency control distributed database

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