A Review on Fragmentation, Allocation and Replication in Distributed Database Systems

Tarun, Sashi; Batth, Ranbir Singh; Kaur, Sukhpreet

doi:10.1109/iccike47802.2019.9004233

Cited by 9 publications

(5 citation statements)

References 7 publications

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“…bitmap formats and regular expressions. Sequential algorithms are developed for mining bigger datasets by employing the concepts of data fragmentation [13], projections [14], incremental [15] & pattern growth techniques [16], task & data parallelization [17], distributed processing [18] etc. Algorithms are also designed to handle temporal, weighted as well as the user defined constraints [19].…”

Section: Related Workmentioning

confidence: 99%

Significance of Data Structures and Data Retrieval Techniques on Sequence Rule Mining Efficacy

Nayanjyoti Mazumdar

2023

IJRITCC

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Sequence mining intends to discover rules from diverse datasets by implementing Rule Mining Algorithms with efficient data structures and data retrieval techniques. Traditional algorithms struggle in handling variable support measures which may involve repeated reconstruction of the underlying data structures with changing thresholds. To address these issues the premiere Sequence Mining Algorithm, AprioriAll is implemented against an Educational and a Financial Dataset, using the HASH and the TRIE data structures with scan reduction techniques. Primary idea is to study the impact of data structures and retrieval techniques on the rule mining process in handling diverse datasets. Performance Evaluation Matrices- Support, Confidence and Lifts are considered for testing the efficacies of the algorithm in terms of memory requirements and execution time complexities. Results unveil the excellence of Hashing in tree construction time and memory overhead for fixed sets of pre-defined support thresholds. Whereas, TRIE may avoid reconstruction and is capable of handling dynamic support thresholds, leading to shorter rule discovery time but higher memory consumption. This study highlights the effectiveness of Hash and TRIE data structures considering the dataset characteristics during rule mining. It underscores the importance of appropriate data structures based on dataset features, scanning techniques, and user-defined parameters.

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Section: Related Workmentioning

confidence: 99%

Significance of Data Structures and Data Retrieval Techniques on Sequence Rule Mining Efficacy

Nayanjyoti Mazumdar

2023

IJRITCC

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“…The execution cost of the processing engine for each task is estimated using (1). The least execution cost is estimated using (2). The practical calculation of implementation for each processing engine is shown in Table 4.…”

Section: Calculation Of Total System Costmentioning

confidence: 99%

“…The success of a distributed system is determined by how data is fragmented and distributed across several geographical locations [1], [2]. One of the most difficult aspects of distributed architecture is overcoming the growing workforce load and cutting down data allocation costs.…”

Section: Introductionmentioning

confidence: 99%

An optimized cost-based data allocation model for heterogeneous distributed computing systems

Tarun

Dubey

Batth

et al. 2022

IJECE

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<span lang="EN-US">Continuous attempts have been made to improve the flexibility and effectiveness of distributed computing systems. Extensive effort in the fields of connectivity technologies, network programs, high processing components, and storage helps to improvise results. However, concerns such as slowness in response, long execution time, and long completion time have been identified as stumbling blocks that hinder performance and require additional attention. These defects increased the total system cost and made the data allocation procedure for a geographically dispersed setup difficult. The load-based architectural model has been strengthened to improve data allocation performance. To do this, an abstract job model is employed, and a data query file containing input data is processed on a directed acyclic graph. The jobs are executed on the processing engine with the lowest execution cost, and the system's total cost is calculated. The total cost is computed by summing the costs of communication, computation, and network. The total cost of the system will be reduced using a Swarm intelligence algorithm. In heterogeneous distributed computing systems, the suggested approach attempts to reduce the system's total cost and improve data distribution. According to simulation results, the technique efficiently lowers total system cost and optimizes partitioned data allocation.</span>

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“…The fragmentation of query output and evaluation of data accuracy requires an in-depth analysis of the inaccuracy distribution in database relations and their union to generate the query output [24]. For this purpose, we split database relations into areas possessing uniform accuracies.…”

Section: Introductionmentioning

confidence: 99%

Formal Approach to Data Accuracy Evaluation

Athamena

Houhamdi

2022

IJCAI

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Usually, data quality is defined by multiple attributes that allow classifying the output data (such as completeness, freshness, and accuracy) or the methods exploiting these data (such as dependability, performance, and protection). Among the suggested quality attributes, we will discuss one of the principal categories: data accuracy. Scientific experiments, decision-making, and data retrieval are examples of situations that require a formal evaluation approach to data accuracy. The evaluation approach should be adaptable to distinct understandings of data accuracy and distinct end-user expectations. This study investigates data accuracy and defines dimensions and metrics that affect its evaluation. The investigation of data accuracy generates problems in the user expectation specification and database quality models. This work describes our proposed approach for data accuracy evaluation by defining an evaluation algorithm that considers the distribution of inaccuracies in database relations. The approach decomposes the query output in accordance with data accuracy, labels every part with its accuracy value, and addresses the possibility of enforcing data accuracy by using these values. This study mainly contributes by proposing an explicit evaluation of quality attributes of data accuracy, a formal evaluation approach to data accuracy, and suggesting some improvement actions to reinforce data accuracy.Povzetek: Opisana je formalna metoda preverjanja točnosti podatkov.

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A Review on Fragmentation, Allocation and Replication in Distributed Database Systems

Cited by 9 publications

References 7 publications

Significance of Data Structures and Data Retrieval Techniques on Sequence Rule Mining Efficacy

Significance of Data Structures and Data Retrieval Techniques on Sequence Rule Mining Efficacy

An optimized cost-based data allocation model for heterogeneous distributed computing systems

Formal Approach to Data Accuracy Evaluation

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