Open Access

ARTICLE

Real-Time Memory Data Optimization Mechanism of Edge IoT Agent

by Shen Guo^*, Wanxing Sheng, Shuaitao Bai, Jichuan Zhang, Peng Wang

China Electric Power Research Institute, Beijing, 100192, China

* Corresponding Author: Shen Guo. Email:

Intelligent Automation & Soft Computing 2023, 37(1), 799-814. https://doi.org/10.32604/iasc.2023.038330

Received 12 December 2022; Accepted 24 February 2023; Issue published 29 April 2023

Abstract

With the full development of disk-resident databases (DRDB) in recent years, it is widely used in business and transactional applications. In long-term use, some problems of disk databases are gradually exposed. For applications with high real-time requirements, the performance of using disk database is not satisfactory. In the context of the booming development of the Internet of things, domestic real-time databases have also gradually developed. Still, most of them only support the storage, processing, and analysis of data values with fewer data types, which can not fully meet the current industrial process control system data types, complex sources, fast update speed, and other needs. Facing the business needs of efficient data collection and storage of the Internet of things, this paper optimizes the transaction processing efficiency and data storage performance of the memory database, constructs a lightweight real-time memory database transaction processing and data storage model, realizes a lightweight real-time memory database transaction processing and data storage model, and improves the reliability and efficiency of the database. Through simulation, we proved that the cache hit rate of the cache replacement algorithm proposed in this paper is higher than the traditional LRU (Least Recently Used) algorithm. Using the cache replacement algorithm proposed in this paper can improve the performance of the system cache.

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Keywords

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