In a distributed database system, the data is distributed on multiple sites in the cluster. So for join queries involving large amount of data access and complex computation, how to efficiently use each site to comple...
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In a distributed database system, the data is distributed on multiple sites in the cluster. So for join queries involving large amount of data access and complex computation, how to efficiently use each site to complete data reading and computation is one of the key issues in query optimization. With the development of network communication technology, the cost of data transmission in network is no longer the only factor limiting the query efficiency, especially for distributed databases deployed in high-speed local area networks, the cost of CPU computation of local sites and the cost of data I/O also need to be considered. In this regard, a multi-source mating selection based differential evolutionary artificial bee colony algorithm is proposed in this paper to solve the distributed database query optimization problem under high-speed local area network deployment. In this algorithm, the population is first initialized using the good node set method so that the population can be more evenly distributed in the feasible domain, and then the genetic algorithm is combined with the artificial bee colony algorithm to improve the performance of the algorithm. At the same time, spectral clustering is introduced to mine the regular characteristics of the population, and a multi-source mating selection and recombination operator is designed to guide the algorithm search based on the obtained structured information of the population, which can accelerate the convergence of the algorithm by using the recombination of similar individuals while maintaining the diversity of the population by setting multiple sources of mating selection for each individual. Finally, simulation comparison experiments are conducted with other methods under different query sizes, and the results show that the proposed method is able to produce less costly query execution plans. And to a certain extent, it is able to reduce the query response time and improve the query efficiency.
The paper presents a conception of a distributed database of video data for educational purpose. The study was conducted at the Kazan Federal University, the Kazan National Research Technological University, and the K...
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ISBN:
(纸本)9783031856518;9783031856525
The paper presents a conception of a distributed database of video data for educational purpose. The study was conducted at the Kazan Federal University, the Kazan National Research Technological University, and the Kazan State Power Engineering University. Sharing the distributed data to improve educational content and digital resources designed to serve the processes of digitalization in the Russian educational system is under analysis. Features of this conception include: stack metadata structure that provides inheritance and personalized liability in the educational information database;secure storage of texts, audio and video coding using watermarks;taking into account the structure of the speech signal based on the algorithms of its selection;connecting and maintaining the work of an intelligent analyzer. The experimental study (N = 350) involving teachers and higher education students working in schools included initial and formative stages. The result of the initial stage made it possible to reveal fragmented experience, low motivation and unformed readiness of the majority of practicing teachers for the use of a distributed educational database. Students from control and experimental groups were involved in the formative stage. Accordingly, statistically significant positive results were obtained, indicating the effectiveness of the proposed concept.
In a distributed database system (DDBS), the data are partitioned into smaller databases and distributed over multiple sites in a computer network. Associated with a DDBS are functions like query processing and concur...
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In a distributed database system (DDBS), the data are partitioned into smaller databases and distributed over multiple sites in a computer network. Associated with a DDBS are functions like query processing and concurrency control. Traditionally in DDBS research, the computer network has been considered a performance bottleneck, and much research effort has been directed towards the design of database operations that minimize the data transmission cost. With the development of high-speed networks, the network transmission costs go down and new algorithms that efficiently utilize the huge bandwidth available are required. In this paper, we first identify the issues involved in developing this distributed application in a high-speed environment. Then we demonstrate the inadequacy of existing database protocols in utilizing the gigabit network. And finally, we develop a new concurrency control protocol that performs better than traditional DDBS in a high-speed network. Both analytical and simulation results are presented. In this paper, we have concentrated on the concurrency control (CC) aspect of DDBS since this protocol is at the heart of the overall functioning of the distributed system.
In recent years, with the text, images, audio, video and other data doubled because of the rapid development of information technology, we have entered the era of big data. How to effectively analyze and use the data ...
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ISBN:
(纸本)9781509025350
In recent years, with the text, images, audio, video and other data doubled because of the rapid development of information technology, we have entered the era of big data. How to effectively analyze and use the data has been a hot research direction. So the research of distributed database came into being to adapt to this research requirement. Sometimes the traditional genetic algorithm can't generate the optimal query plan. Focusing on this defect of the traditional genetic algorithm, this paper presents an improved genetic search algorithm. The improved algorithm uses the FCM clustering algorithm to classify the data members firstly, and then set up the crossover and mutation probability for each category to solve the problem that the crossover and mutation rate is set too large or too small. Simulation results show that the improved algorithm can find the optimal query execution plan in a relatively short period of time and then improve the query efficiency.
Query optimization is an important part of database management system. In this paper, through the research on query optimization technology, based on a number of optimization algorithms commonly used in distributed qu...
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ISBN:
(纸本)9781424455379
Query optimization is an important part of database management system. In this paper, through the research on query optimization technology, based on a number of optimization algorithms commonly used in distributed query, a new algorithm is designed, and experiments show that this algorithm can significantly reduce the amount of intermediate result data, effectively reduce the network communication cost, to improve the optimization efficiency.
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. T...
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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.
With the information expanding and network popularization, the way that accessing single database can not satisfy the demands for users. The requirement to access distributed database is increased. This paper firstly ...
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ISBN:
(纸本)9780769539300
With the information expanding and network popularization, the way that accessing single database can not satisfy the demands for users. The requirement to access distributed database is increased. This paper firstly implemented distributed database query with the grid computing architecture Alchemi which is based on .NET. Then, a distributed database searching system model was constructed by grid computing technology, while the architecture and the operation process of the model were described in detail. Finally, the model was achieved with the platform of ***. According to the analyses of the configuration information and experimental results, it is proved that, compared with the current distributed database searching system, the system that developed by Alchemi is not only easy to configure, but also able to assure the efficiency and accuracy of the query.
The material requirement planning (MRP) process is crucial when software packages, like enterprise resource planning (ERP) software, are used in the production planning for manufacturing enterprises to ensure that app...
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The material requirement planning (MRP) process is crucial when software packages, like enterprise resource planning (ERP) software, are used in the production planning for manufacturing enterprises to ensure that appropriate quantities of raw materials and Subassemblies are provided at the right time. Whereas little attention has been paid to the architectural aspects of MRP process in academic studies, in practice, reports are often made of its time consuming characteristics due to intensive interactions with databases and difficulty in real time processing. This paper proposes a grid enabled MRP process in a distributed database environment and demonstrates the performance improvement of the proposed process by a simulation study.(C) 2009 Elsevier Inc. All rights reserved.
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 distrib...
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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.
This paper studies the problem of query optimization in a distributed database. Assuming a linear additive cost function (in volume of data moved), we present a fast algorithm for finding the optimal program that answ...
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This paper studies the problem of query optimization in a distributed database. Assuming a linear additive cost function (in volume of data moved), we present a fast algorithm for finding the optimal program that answers a class of common queries, called chain queries. The key to the problem formulation and to the derivation of an efficient algorithm is an elegant parameterization of the database state against which the query is to be answered. This parameterization then enables us to characterize the set of potentially optimal programs, which in turn leads to a fast dynamic programming algorithm. Since in practice the needed parameters may not be available to the database system, we also discuss how to deal with partial parameterizations of the database state.
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