分布式数据库中数据分配策略及实例研究

在分布式数据库系统的设计中，数据的分配问题直接影响系统的性能。本文论述了分布式数据库中的数据分配策略，并通过实例对各种数据分配方法进行了分析与比较     

对分布式数据库发展方向的分析

本文对分布式数据库的设计方法、分割与分配技术作了一些探讨，并就分布式数据库的发展方向进行了初步分析。     

一个基于分布式数据库系统的动态负载分配算法

负载分配算法能够通过在其结点间明智地再分配工作负载而提高分布式系统的性能．在本文中,我们提出了一个新的基于分布式数据库系统的动态负载分配算法．它能够根据系统负载状况、数据的分布和结点间的通信开销自适应地改变其参数和策略。对一个分布式数据库系统的模拟表明,该算法能比稳定的发送者启动自适应算法提供更好的稳定性和性能。     

分布式数据库数据分配模型的优化算法

本文分析了广域网中影响分布式数据库系统执行总代价的主要因素,提出了以系统通讯量最少为目标的非冗余分配条件下的分布式数据库分配模型求解的优化算法,并给出了详细的论述.     

一种基于空间限制的数据库优化分配算法

本文介绍了在分布式数据库中的数据优化分配问题，提出并讨论了基于空间限制的一种数据优化分配算法。     

基于LAN的分布式数据库系统的设计研究

论文介绍了一种基于LAN的分布式数据库的设计算法FWDA,该算法采用试探式方法来解决以下两个问题:(1)同时把文件和工作负荷分配到服务器上;(2)确定构建分布式数据库所需的最佳服务器个数。最后,通过一个示例来说明这种算法在实际中的具体应用。     

浅谈分布式数据库中数据分片与分配关系的比较

通过对集中式数据库和分布式数据库的比较,指出了数据分片与分配是设计分布式数据库重要环节,给出了数据分片与分配的目的、原则以及方法,分析了数据分布的透明性,对分片与分配之间的关系予以简要说明,最后介绍了在分布式数据库设计中分片与分配产生的问题.     

分布式数据设计中数据和操作的分配

提出了将全局关系分段，将查询和更新操作分解成这些分段上的关系担任步，然后用系统费用模型将分段和操作分配到各站点以使系统费用最小，从而建立分布式数据库设计模型。     

一种基于空间限制的数据优化分配算法

本文介绍了在分布式数据库中的数据优化分配问题，提出并讨论了基于空间限制的一种数据优化分配算法     

基于本体模式的分布式数据最优分配方法

随着网络技术的发展,分布式数据库应用越来越广泛。将数据存储在合适的位置不但能够提高数据处理的效率,而且能够减少数据处理的成本。近来的大多数研究都侧重于已存在的数据库,通过分析系统操作历史来研究数据分配问题。论文提出一种基于本体模式的分布式数据库系统构造及需求分析方法,用于解决分布式数据库的数据分配问题。     

Evolutionary Algorithms for Allocating Data in Distributed Database Systems

A major cost in executing queries in a distributed database system is the data transfer cost incurred in transferring relations (fragments) accessed by a query from different sites to the site where the query is initiated. The objective of a data allocation algorithm is to determine an assignment of fragments at different sites so as to minimize the total data transfer cost incurred in executing a set of queries. This is equivalent to minimizing the average query execution time, which is of primary importance in a wide class of distributed conventional as well as multimedia database systems. The data allocation problem, however, is NP-complete, and thus requires fast heuristics to generate efficient solutions. Furthermore, the optimal allocation of database objects highly depends on the query execution strategy employed by a distributed database system, and the given query execution strategy usually assumes an allocation of the fragments. We develop a site-independent fragment dependency graph representation to model the dependencies among the fragments accessed by a query, and use it to formulate and tackle data allocation problems for distributed database systems based on query-site and move-small query execution strategies. We have designed and evaluated evolutionary algorithms for data allocation for distributed database systems.     

Five Steps to Construct a Model of Data Allocation for Distributed Database Systems

The allocation of data to nodes in a computer communications network is a critical issue in distributed database design, specially in wide area network where optimizing the distributed queries is the main objective. Numerous models of data allocation have been presented so far (Ceri and Pelagatti, 1986; Lee et al., 1994; Apers, 1988; Mahmood et al., 1994; Theel, 1994; Saha and Mukherjee, 1994; Walfson and Jajodia, 1995), but no optimal or universally accepted algorithm exists yet, and very few algorithms have been implemented to date (Rob and Cornonel, 1993). In this paper a method to construct a model of data allocation for distributed database system has been proposed. The adopted method for the construction of the data allocation model leads to an efficient model of its kind. The proposed model not only solves distributed database design problem, but also solves distributed database maintenance problem by covering initial allocation and post allocation of the data. The efficiency of proposed model has been proved by comparing proposed model with other relevant models.     

A synchronized design technique for efficient data distribution

One of the important features of database fragmentation and allocation techniques is the fact that they depend not only on the entries of a database relation, but also on their empirical frequencies of use. Distributed processing is an effective way to improve performance of database systems. However, for a Distributed Database System (DDBS) to function efficiently, fragments of the database need to be allocated carefully at various sites across the relevant communications network. Therefore, fragmentation and proper allocation of fragments across network sites is considered as a key research area in distributed database environment. However, fragments allocation to the most appropriate sites is not an easy task to perform. This paper proposes a synchronized horizontal fragmentation, replication and allocation model that adopts a new approach to horizontally fragment a database relation based on attribute retrieval and update frequency to find an optimal solution for the allocation problem. A heuristic technique to satisfy horizontal fragmentation and allocation using a cost model to minimize the total cost of distribution is developed. Experimental results are consistent with the hypothesis and confirm that the proposed model can efficiently solve dynamic fragmentation and allocation problem in a distributed relational database environment.     

Exact approaches for static data segment allocation problem in an information network

In a large distributed database, data are geographically distributed across several separate servers (or data centers). This helps in distributing load in the access network. It also helps to serve data locally where it is required. There are various approaches based on the granularity of data for efficient data distribution in a communication network. The file allocation problem (FAP) locates files to servers, the segment allocation problem (SAP) locates database segments, and the mirror location problem (MLP) locates replicas of the entire database. The placement of such data to multiple servers can be modeled as an optimization problem. The major decisions influencing optimization involves the location of servers, allocation of content and assignment of users. In this paper, we study the segment allocation problem (SAP), which is also known as the partial mirroring problem. This approach is more tractable than the file allocation problem in realistic cases and also eliminates the overhead of (constant) update costs that is incurred in the mirror location problem. Our contribution is two-fold: Firstly, earlier works on SAP assume pre-defined segments. We build a data partitioning method using well-known facility location models. We quantify the performance of the partitioning method. We show that the method partitions the database within a reasonable limit of error. Secondly, we introduce a new model for the segment allocation problem in which the segments are completely connected to each other by high-bandwidth links and contains a cost benefit for inter-segment traffic flows. We formulate this problem as an MILP and build exact solution approaches to solve large scale problems. We demonstrate some structural properties of the problem that make it solvable, using a Benders decomposition algorithm. Computational results validate the superiority of the decomposition approach.     

A high-performance computing method for data allocation in distributed database systems

Enhancing the performance of the DDBs (Distributed Database system) can be done by speeding up the computation of the data allocation, leading to higher speed allocation decisions and resulting in smaller data redundancy and shorter processing time. This paper deals with an integrated method for grouping the distributed sites into clusters and customizing the database fragments allocation to the clusters and their sites. We design a high speed clustering and allocating method to determine which fragments would be allocated to which cluster and site so as to maintain data availability and a constant systemic reliability, and evaluate the performance achieved by this method and demonstrate its efficiency by means of tabular and graphical representation. We tested our method over different network sites and found it reduces the data transferred between the sites during the execution time, minimizes the communication cost needed for processing applications, and handles the database queries and meets their future needs.     

DYFRAM: dynamic fragmentation and replica management in distributed database systems

In distributed database systems, tables are frequently fragmented and replicated over a number of sites in order to reduce network communication costs. How to fragment, when to replicate and how to allocate the fragments to the sites are challenging problems that has previously been solved either by static fragmentation, replication and allocation, or based on a priori query analysis. Many emerging applications of distributed database systems generate very dynamic workloads with frequent changes in access patterns from different sites. In such contexts, continuous refragmentation and reallocation can significantly improve performance. In this paper we present DYFRAM, a decentralized approach for dynamic table fragmentation and allocation in distributed database systems based on observation of the access patterns of sites to tables. The approach performs fragmentation, replication, and reallocation based on recent access history, aiming at maximizing the number of local accesses compared to accesses from remote sites. We show through simulations and experiments on the DASCOSA distributed database system that the approach significantly reduces communication costs for typical access patterns, thus demonstrating the feasibility of our approach.     

智能土石方调配系统的数据库设计

智能土石方调配系统对工程数据、生产数据和地理空间数据进行数字化，存入数据库服务器，根据工程进度计划，利用动态线性规划算法，生成任意时间跨度的土石方调配方案。由于大型工程数据量巨大，影响土石方调配方案的边界条件众多，且实际施工现场数据处于动态变化之中，因此智能土石方调配系统的数据库设计的好坏，直接关系到整个土石方调配平衡方案的可信度、可操作性和运行质量。通过需求分析，设计了数据库结构，开发了智能土石方调配系统并应用到世界最高的面板坝的土石方调配方案优化分析中，数据库运行状况良好，提高了土石方调配方案的准确性和可操作性。     

File allocation in a distributed database

A File allocation problem is studied in this paper. The problem formulated is to minimize transmission cost where the constraints are the number of files and the number of copies. The transmission cost also reflects concurrency control cost which is essential in a distributed database system. It is demonstrated that an optimal solution can be found by transforming this problem to a network flow problem.     

Enhanced Schemes for Data Fragmentation,Allocation, and Replication in Distributed Database Systems

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.