Real-time Transaction Processing Research Articles

Web-based Palm Oil Seedling Sales Information System (Case Study: CV. XYZ)

Oil palm seedling sales are one of the important aspects of the agricultural industry in Indonesia. However, conventional sales processes often encounter various obstacles, such as limited access to information for consumers, difficulties in inventory management, and low operational efficiency. To overcome these problems, this study aims to develop a Web-based Oil Palm Seedling Sales Information System at CV. XYZ. We designed this system to offer a comprehensive solution for sales management, encompassing stock recording and real-time transaction processing. This study uses a system development method with the waterfall method, in which the development stages include requirements, system design, implementation, verification, and maintenance. We collected data through direct observation at CV XYZ, interviews with management and customers, and related literature studies. Users then tested the prototype to identify potential problems and gather feedback for system improvement. According to the study's findings, the implementation of this web-based information system has resulted in increased efficiency in sales and inventory management. Users can easily access product information, place orders, and track the status of their orders. In addition, this system also allows integration with payment gateways, so that the transaction process becomes faster and safer. This system simplifies customer data management, sales recording, and financial report analysis from a management standpoint. At CV. XYZ, the development of the Web-based Palm Oil Seedling Sales Information System positively impacted operational efficiency and effectiveness. This system not only increases customer satisfaction by providing faster and more transparent services, but it also helps management make more accurate decisions based on available data. We need to add more advanced data analysis features to forecast sales trends and market demands, and integrate the system with e-commerce platforms to broaden our market reach.

Mart Billing System

The Mart Billing System for Mega Project is a comprehensive software solution designed to streamline and automate the billing process for large-scale mart operations. In the contemporary retail landscape, efficient billing systems are indispensable for managing transactions, inventory, and customer interactions seamlessly. This project addresses the complexities of managing billing operations in mega marts by integrating advanced features and technologies. Key features of the Mart Billing System include a user-friendly interface for both cashiers and customers, robust inventory management capabilities, real-time transaction processing, and secure payment options. The system is designed to handle high volumes of transactions efficiently, ensuring minimal wait times for customers during peak hours. Moreover, the Mart Billing System incorporates advanced reporting and analytics tools, enabling mart managers to gain valuable insights into sales trends, inventory turnover rates, and customer preferences. These insights empower decision-makers to optimize pricing strategies, stock levels, and promotional campaigns for enhanced profitability and customer satisfaction.

Type-2 Neutrosophic Set and Their Applications in Medical Databases Deadlock Resolution

Electronic patient data gives many advantages, but also new difficulties. Deadlocks may delay procedures like acquiring patient information. Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties. Soft computing-based solutions have been developed to solve this challenge. In a single framework, ambiguous, vague, incomplete, and inconsistent transaction attribute information has received minimal attention. The work presented in this paper employed type-2 neutrosophic logic, an extension of type-1 neutrosophic logic, to handle uncertainty in real-time deadlock-resolving systems. The proposed method is structured to reflect multiple types of knowledge and relations among transactions’ features that include validation factor degree, slackness degree, degree of deadline-missed transaction based on the degree of membership of truthiness, degree of membership of indeterminacy, and degree of membership of falsity. Here, the footprint of uncertainty (FOU) for truth, indeterminacy, and falsity represents the level of uncertainty that exists in the value of a grade of membership. We employed a distributed real-time transaction processing simulator (DRTTPS) to conduct the simulations and conducted experiments using the benchmark Pima Indians diabetes dataset (PIDD). As the results showed, there is an increase in detection rate and a large drop in rollback rate when this new strategy is used. The performance of Type-2 neutrosophic-based resolution is better than the Type-1 neutrosophic-based approach on the execution ratio scale. The improvement rate has reached 10% to 20%, depending on the number of arrived transactions.

The Impact of Revolution Strategies and Competitive Advantage on Nigerian Banks

Purpose: The purpose of this study was to examine how Revolution strategies affected competitive advantage of Nigerian Commercial Banks.
 Methodology: This study adopted descriptive and explanatory research designs. The study used primary data collected using semi-structured questionnaires. Reliability was tested through a pilot study on 5 deposits taking micro finance using the test–retest method. Data was analyzed descriptively and inferentially. Descriptive statistics including frequency, percentage, mean and standard deviation was used after which the data was presented using tables and charts. 
 Results: The study revealed that whereas process, product and market revolution have an effect on competitive advantage, technology Revolution was the key driver in competitive advantage as it allowed real time transaction processing, overall customer experience and offered convenience to the customers.
 Conclusion: The study concludes that process Revolution, product Revolution, market Revolution and technology Revolution significantly influences competitive advantage among commercial banks in Nigeria. 
 Recommendation: The study recommended that banks must take immediate steps to improve Revolution by critically assessing current Revolution capabilities and performance, and ensure they are aligned in creating value and convenience to customers while reducing the cost of doing business. 

Artificial Intelligence for Demystifying Blockchain Technology Challenges: A Survey of Recent Advances

Blockchain technology has gained lots of traction in the past five years due to the innovations introduced in digital currency, the Bitcoin. This technology is powered by distributed ledger technology, which is a distributed database system. It is often renowned for decentralization, anti-attack, and unfalsified attributes making it a top choice in several non-monetary applications. In fact, the problem of privacy and security of the Internet of Things has been undertaken aggressively with Blockchain. Several problems have been identified with blockchain technology such as large delays and lack of support for real-time transaction processing, authorization, node verification, and consensus mechanisms. This article intends to provide a comprehensive survey on the recent advances and solutions to the problems of blockchain technology by leveraging the artificial intelligence approaches. The outcomes of this study will provide valuable information and guidance on the design of Blockchain-based systems to support time-sensitive and real-time specific applications and processes.

Efficacy of Real-Time Transaction Processing System

Efficacy of Real-Time Transaction Processing System

Rahasak—Scalable blockchain architecture for enterprise applications

Blockchain-based decentralized infrastructure has been adapted in various industries to handle the sensitive data in a privacy-preserving manner without trusting third parties. However, integrating state-of-the-art blockchain platforms with the scalable, enterprise-level applications result in several challenges. Current blockchain platforms do not support high transaction throughput, lack high scalability, and cannot provide real-time transaction processing and back-pressure operation handling in high transaction throughput applications (e.g Big data, IoT). In this paper, we propose a novel permissioned blockchain platform “Rahasak” for highly scalable, enterprise applications. Rahasak blockchain adopts the Apache Kafka-based consensus on top of a “Validate-Execute-Group” blockchain architecture to handle real-time transaction execution on the blockchain. The architecture is equipped with a functional programming and actor-based smart contract platform that enables concurrent execution of transactions in the blockchain. Rahasak supports high transaction throughput, high scalability, concurrent transaction execution, data analytics features. With Rahasak, we make blockchain more scalable, secure, structured and meaningful for further data analytics.

Health-care databases and its role in transformation of medicine

Health-care database is a collection of health-care data organized for storage, accessibility, and retrieval. Health-care database serves to replace the paper documents, filing cabinets of old, and file folders, which will be more convenient and immediate. At present, health-care system is in a transition from a patient care perspective toward information-based medicine requiring data from various sources such as laboratory tests, genetic tests, medical images, family histories, and patient medical records, which need to be easily stored, integrated, and analyzed. The most commonly used database in health care is the online transaction processing (OLTP) database among different types of databases available. OLTP database is the one that is a single computer application runs on, and the main strength of it is quick and real-time transaction processing. Electronic health record is a prime example of the OLTP, and practitioners enter routine clinical and laboratory data into them during usual practice as a record of the patient's care. Data can be stored externally in a secure place and can be backed up to prevent data loss with these health-care databases. The back-end data can therefore become more accurate and standardized because of the front-end software providing tip text and enforce data. Furthermore, the health-care database allows the rapid processing of classical transactions such as laboratory results and payment claims as the data are computerized.

A Deep Dive: Does Big Data Improve Maturity in the Developed Capital Markets?

Over this decade, the concept of big data has been applied to industries but the capital markets have been traditionally laggard to adoption. Within the financial services’ sector, Big Data has gained far more traction within retail banking and insurance due to the increasing desire of these financial institutions to profile and analyze their customers in a similar manner to early adopters of Big Data strategy such as Amazon, Baidu or Google. However, Big Data strategies have begun to make some impacts on few selected areas of the capital markets, including the social media sentiment analysis on the structured and unstructured data for trading, growth in volume, risk analytics, fraud prevention, market surveillance, predictability and forecasting of the equity prices; those are the early sign of the maturity of the capital markets. Technical and theoretical measures have evolved, but still these dimensions of the capital markets have been a mystery for the human beings till now. The Big Data in the form of structured, semi-structured and unstructured socio-economic and demographic information from social media and blogs from consumers has started indicating impacts on the capital markets which can lead to improving the real-time systems and transaction processing, and improving operational efficiency and maturity. The intent of this paper is threefold. First, it aims to bring the clear inference from the past researches to take a holistic analysis of the work done in the emerging area of Big Data and its implications on capital markets. Second, it’s to perform a deep analysis on how the influences of Big Data affect the assumptions in connection with Random Walk theory and Efficient Market Hypothesis. Third, it will provide a conclusive theoretical analysis of past research work by the scholars, which can establish the model to refine the nexus between investors’ sentiments and assets’ prices with advanced techniques in the Big Data. The paper has been divided into 4 broad sections. In the first section, the paper sets the introduction of connecting the dots and setting the context for the two different fields like Big Data and its influences on the capital markets. The second section explains the theoretical premises and frameworks needed for this research and does deep studies of the previous works in this area to establish conclusive references for the future study. The third section carries out the studies of emerging social media and technologies, analysis of the previous research works from the social media and the capital markets perspective. Finally, the fourth section concludes findings with recommendations.

Taking omid to the clouds

We describe how we evolve Omid, a transaction processing system for Apache HBase, to power Apache Phoenix, a cloud-grade real-time SQL analytics engine. Omid was originally designed for data processing pipelines at Yahoo, which are, by and large, throughput-oriented monolithic NoSQL applications. Providing a platform to support converged real-time transaction processing and analytics applications - dubbed translytics - introduces new functional and performance requirements. For example, SQL support is key for developer productivity, multi-tenancy is essential for cloud deployment, and latency is cardinal for just-in-time data ingestion and analytics insights. We discuss our efforts to adapt Omid to these new domains, as part of the process of integrating it into Phoenix as the transaction processing backend. A central piece of our work is latency reduction in Omid's protocol, which also improves scalability. Under light load, the new protocol's latency is 4x to 5x smaller than the legacy Omid's, whereas under increased loads it is an order of magnitude faster. We further describe a fast path protocol for single-key transactions, which enables processing them almost as fast as native HBase operations.

Modelling and analysis of protection and control applications in smart substation

The real-time transaction processing was a key and challenging technology to protect systems from various failures in smart substation. This paper introduces the time critical communication between the protection and control devices and the primary apparatuses in three-level communication network architecture based on IEC61850, and analyses the process of information exchange and delay requirement of Protection and Control P&C applications between level and level, bay and bay, station and station in smart substation. The generic model of the P&C applications was modelling by latency requirement on OPNET, then the simulation and discussion on using those models to construct IEC61850 network validated the real-time of the application model. In the meantime, the delay performance of the P&C application is analysed in scenarios multiple services sharing substation network, which is an attempt to discuss the possibility of establishing a smart substation network simulation platform on OPNET.

An analysis of deterring and facilitating factors in trade service business -on the basis of customs broker task-

During a decade, e-Commerce environments supporting real-time transaction processing have been getting larger. In telecommunication and financial environments, research and building for main memory database systems have been doing to support real-time transaction processing. A research on indexing for fast transaction support focuses on reducing cache misses or reducing memory access latency when cache misses happen. In the paper, we propose a prefetch method for tree index structures to reduce memory access latency. We present a prefetch-efficient pCST-tree and show superiority of the proposed tree by experiments.

Research on the Embedded Real-Time Database Key Characteristics Analysis and Testing Technology

Currently, the embedded real-time database is widely applied in the embedded system and plays an important role. But on account of being mainly applied to the most important fields such as Communication, Spaceflight and Military as a key task control management, errors by it often results in irreversible fatal losses. Therefore, it is necessary to analyze the embedded real-time database key characteristics and test. This paper, by researching the characteristics, architecture and implementation technique of the embedded real-time database, analyzes its key properties including real-time transaction processing, concurrency control, recovery management, etc., and finally proposes applicable testing strategy and methods which have been proved in the actual test, being as a technique to evaluate the performance of the embedded real-time database.

Data Prefetching to Support Real-time Transactions Processing in Mobile Environments

With the rapid advances in mobile computing technology,there is an increasing demand for processing real-time transactions in mobile environments.Due to the intrinsic limitations of a mobile environment,there can be long time latency for a data access.Sometimes the data can even be unavailable due to the network disconnection.Data prefetching is an approach to this problem.However,most of the previous studies in data prefetching don't consider the timeliness for data objects and deadlines of transactions.Therefore they are inefficient for supporting mobile real-time transaction processing.This paper proposes a data prefetching strategy to support real-time transaction processing in a mobile data broadcast environment.Each data object is assigned a prefetching value determined by its changeability,access frequency.For the data objects with bigger prefetching values,by further considering the priorities of the transactions which access the data objects and the validity intervals for these data objects,the authors determine whether these data objects are actually prefetched.Extensive simulation experiments are conducted and show that when using the proposed data prefetching strategy,more mobile real-time transactions can meet their deadlines.

Distributed real time database systems: background and literature review

Today's real-time systems (RTS) are characterized by managing large volumes of dispersed data making real-time distributed data processing a reality. Large business houses need to do distributed processing for many reasons, and they often must do it in order to stay competitive. So, efficient database management algorithms and protocols for accessing and manipulating data are required to satisfy timing constraints of supported applications. Therefore, new research in distributed real-time database systems (DRTDBS) is needed to investigate possible ways of applying database systems technology to real-time systems. This paper first discusses the performance issues that are important to DRTDBS, and then surveys the research that has been done so far on the issues like priority assignment policy, commit protocols and optimizing the use of memory in non-replicated/replicated environment pertaining to distributed real time transaction processing. In fact, this study provides a foundation for addressing performance issues important for the management of very large real time data and pointer to other publications in journals and conference proceedings for further investigation of unanswered research questions.

Supporting UML Sequence Diagrams with a Processor Net Approach

UML sequence diagrams focus on the interaction between different classes. For distributed real time transaction processing it is possible to end up with complex sequence diagrams, containing messages related to system processes. It is difficult to examine alternative combinations of message passing. A solution is to translate these diagrams into an executable processor net model. This is based on the ‘actor model’, Petri net concepts and higher order net constructs. A case study taken from a flight reservation scenario is introduced and used to create a processor net model. This approach offers various advantages like identifying the main processes, executable model creation, verification, formalization, defining schemas and performance analysis.

Simulating Concurrency Control with Deadlock Avoidance in Real-Time Transaction Processing

The correctness of real-time database systems depends on both the data consistency and the timeliness of the results. We present a very comprehensive study which demonstrates the effect of using various priority assignment and concurrency control protocols with a variety of underlying system configurations, including use of multiple disks, CPUs, and buffer sizes. The study identifies various bottlenecks and solutions under varying system loads and transaction parameters. Both preemptive and non-preemptive protocols are studied under realistic assumptions. Finally, a performance comparison of such a system operating under deadlock and no-deadlock conditions provides insight into the potential waste of resources when concurrency is restricted.

DESIGN OF EXPERIMENTAL PLATFORM FOR TESTING REAL-TIME DATABASE TRANSACTION PROCESSING

It is very difficult to achieve guaranteed real time database services when putting a database into a real-time environment because various components can compete for system resources. Previous research in real-time databases has focused primarily on evolution of transaction processing algorithms, priority assignment strategies and concurrency control techniques. But for the most part the research efforts are based only on simulation studies with many parameters defined. Our objective is to design and implement an experimental real-time database system suitable for study of real time transaction processing. The experimental system is implemented as an integrated set of the most important functional parts upon the real-time operating system VxWorks. It serves as a support platform for performance evaluation of known and new algorithms of the particular processing components to understand their effect on system performance and to identify the most influencing factors.

Real-time transaction processing for autonomic Grid applications

The future Grid will be an autonomic environment that can not only assist users to share large-scale resources and accomplish collaborative tasks but also self-manage to reduce the users’ interventions as much as possible. In such an autonomic Grid environment, the real-time transaction processing is a key and challenging technology to protect systems from various failures. This paper presents an autonomic real-time transaction service (ARTTS) that can (1) dynamically discover Grid services as participants to execute specified sub-transactions, (2) coordinate these participants to achieve the real-time and transactional requirements, and (3) assign priorities to schedule concurrent transactions. Petri nets are used to model and validate the coordination algorithms of real-time Grid transactions and experiment result demonstrates the feasibility of the ARTTS and the performance of the algorithms in different workloads. By handling the potential failures and exceptions autonomically, the ARTTS can facilitate the implementation of real-time Grid transactions and simplify the system management work, which frees users from the complex interference in the autonomic Grid environment.

Real-time transaction processing for autonomic Grid applications☆

The future Grid will be an autonomic environment that can not only assist users to share large-scale resources and accomplish collaborative tasks but also self-manage to reduce the users’ interventions as much as possible. In such an autonomic Grid environment, the real-time transaction processing is a key and challenging technology to protect systems from various failures. This paper presents an autonomic real-time transaction service (ARTTS) that can (1) dynamically discover Grid services as participants to execute specified sub-transactions, (2) coordinate these participants to achieve the real-time and transactional requirements, and (3) assign priorities to schedule concurrent transactions. Petri nets are used to model and validate the coordination algorithms of real-time Grid transactions and experiment result demonstrates the feasibility of the ARTTS and the performance of the algorithms in different workloads. By handling the potential failures and exceptions autonomically, the ARTTS can facilitate the implementation of real-time Grid transactions and simplify the system management work, which frees users from the complex interference in the autonomic Grid environment.