An Efficient Crash Recovery Technique for Real-Time Main Memory Database

This paper presents an efficient recovery scheme suitable for real-time mainmemory database. In the recovery scheme, log records are stored in non-volatile RAM which is dividedinto four different partitions based on transaction types. Similarly, a main memory database isdivided into four partitions based data types. When the using ratio of log store area exceeds thethreshold value, checkpoint procedure is triggered. During executing checkpoint procedure, someuseless log records are deleted. During restart recovery after a crash, partition reloading policyis adopted to assure that critical data are reloaded and restored in advance, so that the databasesystem can be brought up before the entire database is reloaded into main memory. Therefore downtime is obvionsly reduced. Simulation experiments show our recovery scheme obviously improves thesystem performance, and does a favor to meet the dtadlints of real-time transactions.

Validation concurrency control protocol in parallel real-time database systems

In parallel real-time database systems, concurrency control protocols must satisfy time constraints as well as the integrity constraints. The authors present a validation concurrency control(VCC) protocol, which can enhance the performance of real-time concurrency control mechanism by reducing the number of transactions that might miss their deadlines, and compare the performance of validation concurrency control protocol with that of HP2PL(High priority two phase locking) protocol and OCC-TI-WAIT-50(Optimistic concurrency control-time interval-wait-50) protocol under shared-disk architecture by simulation. The simulation results reveal that the protocol the author presented can effectively reduce the number of transactions restarting which might miss their deadlines and performs better than HP2PL and OCC-TI-WAIT-50. It works well when arrival rate of transaction is lesser than threshold. However, due to resource contention the percentage of missing deadline increases sharply when arrival rate is greater than the threshold.

A dynamic crash recovery scheme for distributed real-time database systems

Recovery performance in the event of failures is very important for distributed real-time database systems. This paper presents a time-cognizant logging-based crash recovery scheme （TCLCRS） that aims at distributed real-time databases, which adopts a main memory database as its ground support. In our scheme, each site maintains a real-time log for local transactions and the subtransactions, which execute at the site, and execte local checkpointing independently. Log records are stored in non-volatile high- speed store, which is divided into four different partitions based on transaction classes. During restart recovery after a site crash, partitioned crash recovery strategy is adopted to ensure that the site can be brought up before the entire local secondary database is reloaded in main memory. The partitioned crash recovery strategy not only guarantees the internal consistency to be recovered, but also guarantee the temporal consistency and recovery of the sates of physical world influenced by uncommitted transactions. Combined with two- phase commit protocol, TCLCRS can guarantee failure atomicity of distributed real-time transactions.

Real-Time Memory Data Optimization Mechanism of Edge IoT Agent

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.

An Efficient Secure Real-Time Concurrency Control Protocol

Secure real-time databases must simultaneously satisfy two requirements in guaranteeing data security and minimizing the missing deadlines ratio of transactions. However, these two requirements can conflict with each other and achieve one requirement is to sacrifice the other. This paper presents a secure real-time concurrency control protocol based on optimistic method. The concurrency control protocol incorporates security constraints in a real-time optimistic concurrency control protocol and makes a suitable tradeoff between security and real-time requirements by introducing secure influence factor and real-time influence factor. The experimental results show the concurrency control protocol achieves data security without degrading real-time perform ance significantly.

openPlant实时数据库在电厂SIS中的应用

厂级监控系统在电厂实时生产过程监测、优化控制、实时生产过程管理中发挥着重要作用.在SIS系统中,实时数据库是核心数据平台.文章介绍了具有国内自主产权的openPlant实时数据库功能,以及它所具有的客户端应用模块.openPlant采用标准的C/C++语言编写,从而具有优异的跨平台性能,支持标准的B/S和C/S结构.此外openPlant还采用基于时间和空间维度的高效压缩算法,死区与线性压缩相结合,使得数据库具有数据库容量大、可扩展性、开放性和实时性等特点.最后给出openPlant实时数据库在珠海电厂的应用实例.实际应用表明,openPlant实时数据库与PI、eDNA和iHistorian等国外知名的实时数据库相比,具有性能价格比高的绝对优势.

OpenPlant软件在井下综合管网设计中的应用

煤矿井下综合管网设计是矿井设计的一个重要组成部分,对井下各专业管道的安装准确性、系统流畅性有着直接影响。而鉴于管道设计的复杂性和传统管道设计方式的不足,借助于OpenPlant三维设计软件,通过介绍三维管道设计的模式和流程,阐述了系统建模、数据库建立、碰撞检查和材料报表输出的操作流程,对井下综合管网的三维设计方式进行了有益的探索。

OpenPlant Modeler三维设计软件在大型水电站的应用分析

随着"数字化电厂"概念的提出,三维设计对设计软件的数字化要求日益提高。OpenPlant Modeler支持自定义数据库和参数化模型,结合自动编码功能可快速实现三维模型的数字化。基于OpenPlant Modeler软件进行某大型水电站的三维设计,结合软件的碰撞检查功能,实现了水电站设备的优化布置设计;同时结合三维模型对电站数字化应用进行了研究分析。

Research on Real-time Data Sharing in Power Integrated Automation System

The Power Integrated Automation System has a large amount of the real-time data, it needs to achieve data sharing in different modules in its own system, sometimes even needs to be shared with the other systems. The thesis discusses the characteristics and the ways of the real-time data sharing in the first place. Then, it compares the merits and drawbacks in different ways. Besides, it gives a viable resolution in different aspects, such as the design of the real-time database, the framework of the communication system and the design of the communication software, as well as the real-time data sharing in different systems.

The Multi-level Recovery of Main-memory Real-time Database Systems with ECBH

Storing the whole database in the main-memory is a common method to processreal-time transaction in real-time database systems. The recovery mechanism of Main-memory Real-timeDatabase Systems (MMRTDBS) should reflect the characteristics of the main-memory database andreal-time database because their structures are quite different from other conventional databasesystems. In this paper, therefore, we propose a multi-level recovery mechanism for main-memoryreal-time database systems with Extendable Chained Bucket Hashing (ECBH). Owing to the occurrence ofreal-time data in real-time systems, we should also consider it in our recovery mechanism .According to our performance test, this mechanism can improve the transaction concurrency, reducingtransactions ' deadline missing rate.

An IoT-Based Aquaculture Monitoring System Using Firebase

Indonesia is a producer in the fisheries sector,with production reaching 14.8 million tons in 2022.The production potential of the fisheries sector can be optimally optimized through aquaculture management.One of the most important issues in aquaculture management is how to efficiently control the fish pond water conditions.IoT technology can be applied to support a fish pond aquaculture monitoring system,especially for catfish species(Siluriformes),in real-time and remotely.One of the technologies that can provide this convenience is the IoT.The problem of this study is how to integrate IoT devices with Firebase’s cloud data system to provide reliable and precise data,which makes it easy for fish cultivators to monitor fishpond conditions in real time and remotely.The IoT aquaculture fishpond monitoring use 3 parameters:(1)water temperature;(2)pHwater level;and(3)turbidity level of pond water.IoT devices use temperature sensors,pH sensors,and turbidity sensors,which are integrated with a microcontroller and Wi-Fi module.Data from sensor readings are sent to the Firebase cloud via theWi-Fi module so that it can be accessed in real time by end users with an Androidbased mobile app.The findings are(1)the IoT-based aquaculture monitoring system device has a low error rate in measuring temprature,pH,and turbidity with a percentage of 1.75%,1.94% and 9.78%,respectively.Overall,the total average error of the three components is 4.49%;(2)in cost analysis,IoT-based has a cost-effectiveness of 94.21% compared to labor costs.An IoT-based aquaculture monitoring system using Firebase can be effectively used as a technology for monitoring fish pond conditions in real-time and remotely for fish cultivators that contribute to providing an IoT-based aquaculture monitoring system that produces valid data,is precise,is easy to implement,and is a low-cost system.

A Partition Checkpoint Strategy Based on Data Segment Priority

A partition checkpoint strategy based on data segment priority is presented to meet the timing constraints of the data and the transaction in embedded real-time main memory database systems（ERTMMDBS） as well as to reduce the number of the transactions missing their deadlines and the recovery time.The partition checkpoint strategy takes into account the characteristics of the data and the transactions associated with it;moreover,it partitions the database according to the data segment priority and sets the corresponding checkpoint frequency to each partition for independent checkpoint operation.The simulation results show that the partition checkpoint strategy decreases the ratio of trans-actions missing their deadlines.