Hybrid metaheuristic model based performance-aware optimization for map reduce scheduling

Q2 Computer Science

International Journal of Computers and Applications Pub Date : 2023-11-21 DOI:10.1080/1206212X.2023.2277553

Vishal Kumar, Sumit Kushwaha

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引用次数: 0

Abstract

Because of the rapid rise in the count of corporations using cloud-dependent infrastructure as the foundation for big data storing and analysis. The fundamental difficulty in scheduling big data services in cloud-dependent systems is ensuring the shortest possible makespan while simultaneously reducing the number of resources being used. We have created a new, secure map reduce scheduling method that functions as follows. Initially, the cloud architecture is designed and the tasks are generated. In the pre-processing phase, the huge set of tasks was processed by the map-reduce scheduling framework. Afterward, the optimal task scheduling task is conducted which utilizes a hybrid algorithm named Tunicate Combined Moth Flame Algorithm (TCMFA), which provides better task scheduling via providing optimal makespan, execution time, and security. This proposed TCMFA is the hybridization of both Moth Flame Optimization (MFO) and Tunicate Swarm Algorithm (TSA). The error rate of the TCMFA gets reduced to 320 approximately over other conventional methods such as RSA, ACO, GHO, BTS, OWPSO, BES, PRO, SOA, COOT, TSA & MFO which proves the accuracy of our TCMFA and makes it more efficient and secure for optimal map-reduce scheduling.

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基于性能感知模型的混合元搜索优化 map reduce 调度

由于使用云基础设施作为大数据存储和分析基础的企业数量迅速增加。在依赖云的系统中调度大数据服务的根本困难在于确保尽可能短的时间跨度，同时减少使用的资源数量。我们创建了一种新的、安全的 map reduce 调度方法，其功能如下。首先，设计云架构并生成任务。在预处理阶段，庞大的任务集由 map-reduce 调度框架处理。随后，利用一种名为 Tunicate Combined Moth Flame Algorithm（TCMFA）的混合算法进行优化任务调度，该算法通过提供最优的时间跨度、执行时间和安全性来提供更好的任务调度。所提出的 TCMFA 是飞蛾火焰优化算法（MFO）和unicate 蜂群算法（TSA）的混合。与其他传统方法（如 RSA、ACO、GHO、BTS、OWPSO、BES、PRO、SOA、COOT、TSA 和 MFO）相比，TCMFA 的错误率降低到 320 左右，这证明了我们的 TCMFA 的准确性，并使其在优化 map-reduce 调度方面更加高效和安全。

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来源期刊

International Journal of Computers and Applications Computer Science-Computer Graphics and Computer-Aided Design

CiteScore

4.70

自引率

0.00%

发文量

期刊介绍： The International Journal of Computers and Applications (IJCA) is a unique platform for publishing novel ideas, research outcomes and fundamental advances in all aspects of Computer Science, Computer Engineering, and Computer Applications. This is a peer-reviewed international journal with a vision to provide the academic and industrial community a platform for presenting original research ideas and applications. IJCA welcomes four special types of papers in addition to the regular research papers within its scope: (a) Papers for which all results could be easily reproducible. For such papers, the authors will be asked to upload "instructions for reproduction'''', possibly with the source codes or stable URLs (from where the codes could be downloaded). (b) Papers with negative results. For such papers, the experimental setting and negative results must be presented in detail. Also, why the negative results are important for the research community must be explained clearly. The rationale behind this kind of paper is that this would help researchers choose the correct approaches to solve problems and avoid the (already worked out) failed approaches. (c) Detailed report, case study and literature review articles about innovative software / hardware, new technology, high impact computer applications and future development with sufficient background and subject coverage. (d) Special issue papers focussing on a particular theme with significant importance or papers selected from a relevant conference with sufficient improvement and new material to differentiate from the papers published in a conference proceedings.