Recently with the advent of the IT and the wide spread use of the Internet, new user oriented production and logistic systems, such as the Supply Chain Management System, have been required in order to cope with the d...
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Recently with the advent of the IT and the wide spread use of the Internet, new user oriented production and logistic systems, such as the Supply Chain Management System, have been required in order to cope with the drastic and continuous changes on the markets and users' preferences. Therefore, heterogeneous database systems need to be integrated in a common environment which can cope with the heterogeneous requirements of each company under an ever-evolving changing environment. That is assurance. Autonomous Decentralized database System (ADDS) is proposed as a system architecture in order to realize assurance in distributed database systems. In this system architecture, a loosely-consistency management technology is proposed in order to maintain the consistency of the system, each database can update autonomously, and confer the real time property. A background coordination technology, performed by an autonomous mobile agent, is devised to adapt the system to evolving situations. The system can achieve real time by allocating the information in advance among the sites that has different time constraints for updating. Moreover, an assurance information allocation technology is proposed when considering that a failure in the background coordination mechanism may lead to loss of data and unavailability of the system. This mechanism, in which the mobile agent autonomously regulate its own capacity for allocating the information, is proposed based on the real-time property and system's availability considerations. The effectiveness of the proposed architecture and technologies are evaluated by simulation.
The semijoin offers a method of reducing the amount of data transmission among sites in a distributed database system. Previously, the semijoin has been studied primarily for reducing communication cost in an environ...
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The semijoin offers a method of reducing the amount of data transmission among sites in a distributed database system. Previously, the semijoin has been studied primarily for reducing communication cost in an environment with global public communication networks. In a local area system, however, wide bandwidth usually is available, and the cost of communication is virtually negligible. In light of this, a simplified model of a local area network is adopted, with no constraint imposed on the transmission line capacity and the communication processing capability at each site. Each site is assumed to be able to send and/or receive any amount of data simultaneously. For the model, an efficient algorithm for deriving the shortest semijoin schedule -- in the sense of minimizing the total number of semijoin transmissions -- is developed for the class of tree queries. The algorithm is based on a schedule diagram newly introduced to represent the semijoin schedule.
The modern sensation the field of Library and Information Science is the word e-library where information's are stored in a digital format. It actually enables the use of the new emerging technique XML for transpo...
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The modern sensation the field of Library and Information Science is the word e-library where information's are stored in a digital format. It actually enables the use of the new emerging technique XML for transporting information over internet and thus nullifies the disadvantages (viz, rigid transaction set, fixed business rule, high cost, and slow pace) of previously used EDI (Electronic Data Interchange) technique. Keeping in mind the necessity of rapid and dynamic information explosion the library in the modern era should be universal. This concept of spreading a centralized system in a geographically dispersed system is known as distributed system. In this work we represent a model that is distributed in nature and information is transferred by means of XML. (C) 2012 Elsevier Ltd. All rights reserved.
A quantitative method is presented for evaluating availability in distributed database Systems. The description of the distributed system and of transaction processing is given in terms of a flow graph. System states ...
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A quantitative method is presented for evaluating availability in distributed database Systems. The description of the distributed system and of transaction processing is given in terms of a flow graph. System states are represented by a structure vector. Transitions between states are modeled as a Markov process. Solution techniques are discussed both for the case in which transition rates are independent of the system state and for the case in which they depend on it. Finally, the results for an example are given.
Compared to centralized database systems, distributed systems have certain advantages dependent on the manner in which data are redundantly distributed. These advantages include: 1. improved response time, 2. bette...
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Compared to centralized database systems, distributed systems have certain advantages dependent on the manner in which data are redundantly distributed. These advantages include: 1. improved response time, 2. better data availability, and 3. reduced transmission costs. However, distributed systems create complexities necessitating various distribution controls such as global deadlock resolution and consistency maintenance, which result in increased overhead. One of the factors mitigating this overhead is to find the optimal data-allocation schemes determined by the application environment. Thus, it is necessary to consider trade-offs between data availability, which is suitable for applications, and distribution control overhead. Some data allocation schemes are proposed, derived from an assessment of results obtained from a series of simulations that focus on both response time and communication cost against distribution control overhead in some application environments.
Using a distributed database system as a part of the distributed web sever architecture has obvious advantages. It is shown that a first phase distributed database system can be build by extending an existing object o...
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Using a distributed database system as a part of the distributed web sever architecture has obvious advantages. It is shown that a first phase distributed database system can be build by extending an existing object oriented database system with application-specific additions. A web database is implemented, as a part of the traditional HTTP-based distributed web server, using this distributed database system. (C) 1999 Elsevier Science B.V. All rights reserved.
Deadlocks may occur in distributed databases due to conflicts in data file lockings. A system is in a deadlock condition if and only if a directed cycle exists in its demand graph. The difficulties of constructing a...
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Deadlocks may occur in distributed databases due to conflicts in data file lockings. A system is in a deadlock condition if and only if a directed cycle exists in its demand graph. The difficulties of constructing a consistent demand graph are discussed, and three deadlock detection protocols for distributed databases are presented. The first protocol uses 2 communication phases; the 2nd uses a single communication phases; the 3rd, based on the 2nd, is a one-phase hierarchical deadlock detection protocol. It is assumed in all 3 protocols that the information utilized to locate a resource in a distributed database is provided by a system-wide addressing scheme. The accurate functioning of the protocols is independent of the addressing scheme.
Large-scale distributed database includes a large number of redundant data, which will lead to low correlation between the data, resulting in lower network efficiency. This paper proposes a method for optimizing redun...
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Large-scale distributed database includes a large number of redundant data, which will lead to low correlation between the data, resulting in lower network efficiency. This paper proposes a method for optimizing redundant data classification in distributed databases. Firstly, the redundant data attributes are extracted to provide the accurate data base for the classification of redundant data. Then the optimal classification threshold is obtained according to the weight probability theory, and the redundant data classification is realized. The experimental results show that the algorithm can improve the accuracy of classification and achieve satisfactory results.
In this paper, it is to focus on two areas, primarily data inconsistency problems faced by the mobile database users when they are trying to accessing or updating the database data while mobility in work, in such envi...
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In this paper, it is to focus on two areas, primarily data inconsistency problems faced by the mobile database users when they are trying to accessing or updating the database data while mobility in work, in such environment demand for appropriate strategies arises, to overcome this problem. When users come in contact with other network node, updated data is not reflected or propagated at the other sites or nodes, which is previously updated or changed at previous visited site or at activity center. Secondly, require advance replication architecture and effective network protocol based algorithms follows effective replication strategy that securely supports databases changes activities anytime and anywhere in mobile computing network environment.
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 da...
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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.
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