Materialized View Selection for Query Performance Enhancement Using Stochastic Ranking Based Cuckoo Search Algorithm

Gosain, Anjana; Sachdeva, Kavita

doi:10.1142/s0218539320500084

Cited by 7 publications

(9 citation statements)

References 29 publications

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“…The other is to estimate the cost by using experience and skills according to the technical and economic indicators and actual cost data of similar projects. Gosain, A. and others found that the construction project itself has the characteristics of complexity and long construction cycle, which determines that the construction cost of the construction project is also independent, unique, and complex [10]. However, the factors affecting the project cost are not single, which has great limitations on the personal experience of manufacturing engineers in cost estimation, and cannot meet the accuracy requirements of the project.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of Cuckoo Search Algorithm in Cost Estimation of Building Energy Engineering

Liang-qiong

2022

Wireless Communications and Mobile Computing

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In order to solve the problem that the construction project cost estimation is at a relatively advanced stage, many information about the project cannot be determined, and many unforeseen things affecting the project cost will occur in the process of project construction, which makes the preparation of project investment estimation very difficult. An optimized firefly algorithm is proposed. By introducing cuckoo algorithm, the initial population of fireflies is optimized, which greatly improves the quality of the initial population and speeds up the convergence of fireflies to the optimal solution; Secondly, the performance of CSFA algorithm is tested by six standard test functions; Finally, the algorithm is applied to solve the pressure vessel design problem. The effectiveness of the experiment is verified.

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Section: Literature Reviewmentioning

confidence: 99%

Application of Cuckoo Search Algorithm in Cost Estimation of Building Energy Engineering

Liang-qiong

2022

Wireless Communications and Mobile Computing

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“…The developed scheme creates the weight-based MV selection process to choose the views significantly. Mustapha ChabaMouna et al [25] introduced a proactive selection of MVs. Here, the RE-selection scheme was considered for an optimal selection of views [29].…”

Section: Related Workmentioning

confidence: 99%

A Novel Hybrid Optimization With Ensemble Constraint Handling Approach for the Optimal Materialized Views

Vullam,

Murali Krishna,

Davuluri

et al. 2023

IJRITCC

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The datawarehouse is extremely challenging to work with, as doing so necessitates a significant investment of both time and space. As a result, it is essential to enable rapid data processing in order to cut down on the amount of time needed to respond to queries that are sent to the warehouse. To effectively solve this problem, one of the significant approaches that should be taken is to take the view of materialization. It is extremely unlikely that all of the views that can be derived from the data will ever be materialized. As a result, view subsets need to be selected intelligently in order to enable rapid data processing for queries coming from a variety of locations. The Materialized view selection problem is addressed by the model that has been proposed. The model is based on the ensemble constraint handling techniques (ECHT). In order to optimize the problem, we must take into account the constraints, which include the self-adaptive penalty, the Epsilon ()-parameter, and the stochastic ranking. For the purpose of making a quicker and more accurate selection of queries from the data warehouse, the proposed model includes the implementation of an innovative algorithm known as the constrained hybrid Ebola with COATI optimization (CHECO) algorithm. For the purpose of computing the best possible fitness, the goals of "processing cost of the query," "response cost," and "maintenance cost" are each defined. The top views are selected by the CHECO algorithm based on whether or not the defined fitness requirements are met. In the final step of the process, the proposed model is compared to the models already in use in order to validate the performance improvement in terms of a variety of performance metrics.

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“…Anjana Gosain and Kavita Sachdeva, 11 introduced a MV selection for enhancing the query performance through stochastic ranking (SR) based cuckoo search (CS) optimization. The proposed approach selects the MVs optimally and increases the efficiency.…”

Section: Related Workmentioning

confidence: 99%

“…These techniques learn the workload and choose a subset of relations that collect a single view or several, if and only if the choice of this subset minimizes the cost of workload. Several previous methods have no restriction to resolve the issues of MVS 11 . In addition, some of the approaches are optimized by establishing a few constraints on the view selection process.…”

Section: Introductionmentioning

confidence: 99%

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Multi‐objective materialized view selection using flamingo search optimization algorithm

Srinivasarao

Satish

2022

Softw Pract Exp

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A materialized view selection in data warehouse management is important to speed up query processing. The data presented in data warehouses is generally stored as a set of materialized views. The major challenge is determining which views to materialize and satisfy the response time with reduced cost functions. This paper proposed an effective multi objective cost model based flamingo search algorithm for materialized view selection in data warehouse design. The multiple view processing plan structure of the data warehouse describes the search space of problem in order to select the optimal materialized views. The proposed model evaluates a multi-objective optimization problem based on the cost functions resulting from materialization. The multiple objective functions of the proposed model are maintenance costs, current query processing costs, response cost and previous query processing costs. This model selects the top-k views for materialization by satisfying the mentioned multi-objective functions. The experimental results are simulated using the TPC-H dataset. The efficacy of proposed model is measured by comparing the obtained results of the proposed model with various existing approaches.

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Materialized View Selection for Query Performance Enhancement Using Stochastic Ranking Based Cuckoo Search Algorithm

Cited by 7 publications

References 29 publications

Application of Cuckoo Search Algorithm in Cost Estimation of Building Energy Engineering

Application of Cuckoo Search Algorithm in Cost Estimation of Building Energy Engineering

A Novel Hybrid Optimization With Ensemble Constraint Handling Approach for the Optimal Materialized Views

Multi‐objective materialized view selection using flamingo search optimization algorithm

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