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6th International Conference on Smart Grid and Electrical Automation (ICSGEA)

作者： Li, Liantian Yangjiang Polytech Yangjiang 529500 Peoples R China

ISBN: (纸本)9781665432634

When clustering efficient distributed database, the conventional algorithm has long time cost and low clustering accuracy. To solve the above problems, an efficient distributed database clustering algorithm for big data processing is designed. Calculating the eigenvalues of the database, and linking the efficient distributed database with similar characteristics. The cross correlation matrix is used to ensure the consistency of cluster label. To improve the performance of K-means algorithm, input the database to be clustered, output k clustering centers, and divide the clustering groups. Mapping database to clustering center, clustering low dimensional big data. Experimental results show that the proposed algorithm can reduce the miming time and mean square error of data clustering, and improve the efficiency and accuracy of clustering.

关键词： distributed database Low-dimensional big data Cluster label database mapping

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Lock Violation for Fault-tolerant distributed database System 37

Lock Violation for Fault-tolerant Distributed Database Syste...

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37th IEEE International Conference on Data Engineering (IEEE ICDE)

作者： Guo, Hua Zhou, Xuan Cai, Le Renmin Univ China Sch Informat Beijing Peoples R China East China Normal Univ Shanghai Engn Res Ctr Big Data Management Shanghai Peoples R China Alibaba Grp San Mateo CA USA

ISBN: (纸本)9781728191843

Modern distributed database systems scale horizontally by partitioning their data across a large number of nodes. Most such systems build their transactional layers on a replication layer, employing a consensus protocol to ensure data consistency to achieve fault tolerance. Synchronization among replicated state machines thus becomes a significant overhead of transaction processing. Without careful design, synchronization could amplify transactions' lock duration and impair the system's scalability. Speculative techniques, such as Controlled Lock Violation (CLV) and Early Lock Release (ELR), prove useful in shortening lock's critical path and boosting transaction processing performance. To use these techniques to optimize geo-replicated distributed databases(GDDB) is an intuitive idea. This paper shows that a naive application of speculation is often unhelpful in a distributed environment. Instead, we introduce distributed Lock Violation (DLV), a specialized speculative technique for geo-replicated distributed databases. DLV can achieve good performance without incurring severe side effects.

关键词： distributed database Transaction Locking High Availability

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distributed database of Cloud Platform for the Lower-limb Exoskeleton Robot 17

Distributed Database of Cloud Platform for the Lower-limb Ex...

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17th International Conference on Ubiquitous Robots (UR)

作者： Wu, Yi Cao, Guang-Zhong Huang, Su-Dan Peng, Yeping Shenzhen Univ Coll Mechatron & Control Engn Shenzhen Key Lab Electromagnet Control Guangdong Key Lab Electromagnet Control & Intelli Shenzhen 518060 Peoples R China

ISBN: (纸本)9781728157153

A distributed database of cloud platform for the lower-limb exoskeleton robot is developed in this paper, which is to solve the problem of large data storage when long-term monitoring of multiple exoskeleton robots. The architecture of the cloud platform is present. In terms of the data information of the robot and human body, a distributed database is built by using MyCat and MySQL. The interface between the database and the front-end web page is developed. The experiment indicates that the database of the cloud platform is able to remotely collect the information such as the joint angles of the robot which is also displayed on the web page.

关键词： Lower-limb exoskeleton robot Cloud platform distributed database

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SardineDB: A distributed database on the Edge of the Network 5th

SardineDB: A Distributed Database on the Edge of the Network

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5th Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) International Joint Conference on Web and Big Data

作者： Dong, Min Zhong, Haozhao Sun, Boyu Bi, Sheng Cai, Yi South China Univ Technol Sch Comp Sci & Engn Guangzhou 510006 Guangdong Peoples R China Minist Educ Key Lab Big Data & Intelligent Robot Guangzhou 510006 Guangdong Peoples R China South China Univ Technol Sch Software Engn Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9783030858995;9783030858988

In the past few years, the number of sensors is rapidly increasing on the edge of the network. IoT(Internet of things) devices play not only data producers but also data consumers. It is valuable to deploy a distributed database on the edge of the network. However, flash memory is the mainstream storage medium on the edge, which is different from cloud environment. Flash memory can wear out through repeated writes while large amount of data are written on the edge per day. Thus, in this paper, SardineDB is presented, which is a decentralized distributed database optimized for edge. The engine of SardineDB is Sardine-Core, which is a flash-optimized key-value separation storage based on LevelDB. SardineCore has low GC (garbage collection) burden, which can be used to low the write amplification and improve the write performance on the edge. From evaluation results, the write performance and random read performance of SardineDB have great advantages compared with existing distributed databases on the edge. As a result, SardineDB is very suitable for edge because it has high write performance, low GC burden and low write amplification.

关键词： IOT Edge computing LevelDB distributed database Sensor Flash memory

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An adaptive strategy for statistics collecting in distributed database

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Frontiers of Computer Science 2020年第5期14卷 199-211页

作者： Jintao Gao Wenjie Liu Zhanhuai Li School of Computer Science Northwestern Polytechnical UniversityXi’an710072China

Collecting statistics is a time-and resource-consuming operation in database *** is even more challenging to efficiently collect statistics without affecting system performance,meanwhile keeping correctness in distributed *** strategies usually consider one dimension during collecting statistics,which is lack of *** this paper,we propose an adaptive strategy for statistics collecting(ASC),which well balances collecting efficiency,correctness of statistics and effect to system *** formally define the procedure of collecting statistics and abstract the relationships among collecting efficiency,correctness of statistics and effect to system performance,and introduce an elastic structure(ESI)storing necessary information generated during proceeding our *** can pick appropriate time to trigger collecting action and filter unnecessary tasks,meanwhile reasonably allocating collecting tasks to appropriate executing locations with right executing models through the information stored at *** implement and evaluate our strategy in a distributed *** show that our solutions generally improve the efficiency and correctness of collecting statistics,moreover,reduce the negative effect to system performance comparing with other strategies.

关键词： statistics collecting distributed database adaptive strategy query optimization

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A general fragments allocation method for join query in distributed database

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INFORMATION SCIENCES 2020年 512卷 1249-1263页

作者： Gao, Jintao Liu, Wenjie Li, Zhanhuai Zhang, Jian Shen, Li Northwestern Polytech Univ Xian 710072 Peoples R China PingCAP Ltd Beijing 100096 Peoples R China

The quality of fragments allocation is key for improving performance of join query in distributed database. Current strategies concentrate on using heuristic rules to allocate fragments to corresponding locations, such as picking the location with maximum required data or with greedy algorithm. Notwithstanding their benefits, under distributed environment, facing various query plans, different data distributions and expensive network cost, their scene-sensitive character may easily generate low quality allocation plan due to lack of generalization ability. In this paper, for breaking this limitation, we propose a general strategy for allocating fragments(AlCo, Allocate fragments based on Cost). AICo evaluates multiple candidate allocation plans based on cost, which is realized by a modified genetic algorithm employed from PostgreSQL. Our fitness function (cost model) synthetically considers various changeable factors to support generalization ability. For reducing the risks caused by randomization of genetic algorithm, AICo provides an upper bound computed through current heuristic methods to improve the robustness of our genetic algorithm. We implement AICo in a distributed database system, and the experiments show that, on TPC-H benchmark, AICo is up to 2x-4x better on performance than existing strategies and performs well in robustness and scalability. (C) 2019 Elsevier Inc. All rights reserved.

关键词： distributed database Genetic algorithm Query optimization Fragments allocation Robustness

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Development of Island tourism resources based on distributed database and embedded system

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MICROPROCESSORS AND MICROSYSTEMS 2021年 81卷 103752-103752页

作者： Wang, Yong Hou, Guobin East China Univ Polit Sci & Law ECUPL Sch Int Law Shanghai 200042 Peoples R China

This article describes the sustainable production system made islands. distributed data resources used to produce goods for consumption and disposal. Production activities are supported by global non-critical resources, such as capital, technology and expertise in embedded systems, patents and data: analysis and business plan. Provide a case study to explain this arrangement. Understand the potential of the Island?s manufacturing sector to add value to the debate on sustainable manufacturing. This study aims to develop an embedded system as a model recognized as a highly developed modern development model, and tourism destination as a system bound essentially regional representatives with a specific development framework. Find similarities with the indispensable support of the overall product at your destination for a distributed database server. By this analogy, find a long-term development model suitable for local commercial embedded systems tourist destinations. A reasonable solution is the concept of sustainable development;the basic principle is coherent. Tourism destination management principles function.

关键词： distributed database Embedded system Tourist destination Sustainable Development Competitiveness

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Enhanced Schemes for Data Fragmentation, Allocation, and Replication in distributed database Systems

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COMPUTER SYSTEMS SCIENCE AND ENGINEERING 2020年第2期35卷 99-112页

作者： Torshiz, Masood Niazi Esfaji, Azadeh Salehi Amintoosi, Haleh Islamic Azad Univ Mashhad Branch Dept Comp Engn Mashhad Razavi Khorasan Iran Ferdowsi Univ Mashhad Fac Engn Comp Engn Dept Mashhad Razavi Khorasan Iran

With the growth of information technology and computer networks, there is a vital need for optimal design of distributed databases with the aim of performance improvement in terms of minimizing the round-trip response time and query transmission and processing costs. To address this issue, new fragmentation, data allocation, and replication techniques are required. In this paper, we propose enhanced vertical fragmentation, allocation, and replication schemes to improve the performance of distributed database systems. The proposed fragmentation scheme clusters highly-bonded attributes (i.e., normally accessed together) into a single fragment in order to minimize the query processing cost. The allocation scheme is proposed to find an optimized allocation to minimize the round-trip response time. The replication scheme partially replicates the fragments to increase the local execution of queries in a way that minimizes the cost of transmitting replicas to the sites. Experimental results show that, on average, the proposed schemes reduce the round-trip response time of queries by 23% and query processing cost by 15%, as compared to the related work.

关键词： distributed database Big Data Vertical Fragmentation Allocation Replication

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Research Load Balancing Technology of distributed database Based on Consistent Hash 19

Research Load Balancing Technology of Distributed Database B...

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3rd International Conference on High Performance Compilation, Computing and Communications (HP3C)

作者： Gong, Wenbo Guilin Univ Elect Technol Sch Comp & Informat Secur Guilin Guangxi Peoples R China

ISBN: (纸本)9781450366380

Consistent hash algorithm is applied to build a distributed database load balancing model, but this model should deal with thousands of user requests, handle 10 billion data information, along with low-latency response scenarios, all of this is a grim challenge. When load balancing control mechanism is built by the consistency hash, some nodes in the database cluster are overloaded, but some are idle. These load imbalances can seriously do great damage to the overall performance of distributed database system. This paper proposes a detailed description of variance mathematics model about dynamic load balancing, the core is to track system load, evaluation, classification and storage of each node in distributed cluster. This algorithm controls mutual feedback between node load states, idle data node allots the item of overload node, overall suppression of single point overload. After by experimental simulation, compared with the auxiliary loop hash model, this algorithm improves load balancing efficiency by 30% and settles disputes about distributed database load imbalance based on consistent hashing.

关键词： Load balancing consistent hashing distributed database dynamic variance screening model load analysis auxiliary loop hash model concurrent processing

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A Novel Solution for distributed database Problems

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2020年第10期11卷 468-474页

作者： Sawiris, Bishoy Sameeh Matta Abdel-Fattah, Manal A. Helwan Univ Fac Commerce & Business Adm Business Informat Syst Dept Cairo Egypt Helwan Univ Fac Comp & Informat Informat Syst Dept Cairo Egypt

distributed databases Systems (DDBS) are a set of logically networked computer databases, managed by different sites, locations and accessible to the user as a single database. DDBS is an emerging technology that is useful in data storage and retrieval purposes. Still, there are some problems and issues that degrade the performance of distributed databases. The Aim of this paper is to provide a novel solution to distributed database problems that is based on distributed database challenges collected in one diagram and on the relationship among DDB challenges in another diagram. This solution presents two methodologies for distributed databases management Systems: deep learning-based fragmentation and allocation, and blockchain technology-based security provisioning. The contribution of this paper is twofold. First, it summarizes major issues and challenges in the distributed database. Additionally, it reviews the research efforts presented to resolve the issues. Secondly, this paper presents a distributed database solution that resolves the major issue of distributed database technology. This paper also highlights the future research directions that are appropriate for distributed database technology after the implementation in a large-scale environment and recommended the technologies that can be used to ensure the best implementation of the proposed solution.

关键词： distributed database database challenges deep learning fragmentation blockchain security

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