Backend Database System Research Articles

The application of backend database systems in precision marketing: A case study of Nike official online store

In the era of big data, databases have become a powerful tool for enterprises to gain insight into consumer behavior and market dynamics. However, some enterprises, especially small and medium-sized ones, focus too much on data volume growth while ignoring the importance of data relevance, resulting in unsatisfactory marketing outcomes. Based on this, this paper provides an example of Nike official online store. With the assistance of structured query language (SQL), a backend database system is created under the Oracle11g R2 environment, and its functions are simulated and demonstrated. The system is capable of managing user, product, and order transaction information through basic functions such as adding, querying, modifying, and deleting. In addition, it serves as a foundation for Nike's precision marketing efforts through user profile construction, user behavior analysis, and demand forecasting based on basic statistical methods of counting, proportioning, and sorting.

The Threat Detection Framework for Securing Semantic Web Services

Security is a necessary aspect of modern life for organizations and individuals who use the semantic web to provide various services. Semantic web applications are being used as a portal to communicate with back-end database systems and to support business processes. The confidential and personal information of any organization is stored on these systems. Access Control ensures that the requesting user has to meet certain criteria to access these systems. In most cases, it has been observed that access control only provides protection against external threats. There is no provision for detecting internal attacks. Therefore, there is a need for a mechanism that can be able to detect the malicious behaviour of previously authorized users. This paper proposes two algorithms to detect anomalous behaviour performed by the legitimate insider. During training phase, the first algorithm will create the query signature of each incoming query submitted by the legitimate insider. It also estimates the amount of data that can be extracted by the submitted query and includes in the query signature. The second algorithm will detect incongruous data extraction from the database by comparing the current query signature with the previous signature. If both signatures are identical, the query is considered safe for execution. Otherwise, the query will be considered as threat. In this paper, efforts are being made to give details of the security structure on the semantic web service.

An Ensemble Intrusion Detection Technique Based on Proposed Statistical Flow Features for Protecting Network Traffic of Internet of Things

Internet of Things (IoT) plays an increasingly significant role in our daily activities, connecting physical objects around us into digital services. In other words, IoT is the driving force behind home automation, smart cities, modern health systems, and advanced manufacturing. This also increases the likelihood of cyber threats against IoT devices and services. Attackers may attempt to exploit vulnerabilities in application protocols, including Domain Name System (DNS), Hyper Text Transfer Protocol (HTTP) and Message Queue Telemetry Transport (MQTT) that interact directly with backend database systems and client–server applications to store data of IoT services. Successful exploitation of one or more of these protocols can result in data leakage and security breaches. In this paper, an ensemble intrusion detection technique is proposed to mitigate malicious events, in particular botnet attacks against DNS, HTTP, and MQTT protocols utilized in IoT networks. New statistical flow features are generated from the protocols based on an analysis of their potential properties. Then, an AdaBoost ensemble learning method is developed using three machine learning techniques, namely decision tree, Naive Bayes (NB), and artificial neural network, to evaluate the effect of these features and detect malicious events effectively. The UNSW-NB15 and NIMS botnet datasets with simulated IoT sensors’ data are used to extract the proposed features and evaluate the ensemble technique. The experimental results show that the proposed features have the potential characteristics of normal and malicious activity using the correntropy and correlation coefficient measures. Moreover, the proposed ensemble technique provides a higher detection rate and a lower false positive rate compared with each classification technique included in the framework and three other state-of-the-art techniques.

Interpretation of Implicit Conditions in Database Search Dialogues

Targeting the database search dialogue, we propose to utilise information in the user utterances that do not directly mention the database (DB) field of the backend database system but are useful for constructing database queries. We call this kind of information implicit conditions. Interpreting the implicit conditions enables the dialogue system more natural and efficient in communicating with humans. We formalised the interpretation of the implicit conditions as classifying user utterances into the related DB field while identifying the evidence for that classification at the same time. Introducing this new task is one of the contributions of this paper. We implemented two models for this task: an SVM-based model and an RCNN-based model. Through the evaluation using a corpus of simulated dialogues between a real estate agent and a customer, we found that the SVM-based model showed better performance than the RCNN-based model.

R-memcached: A reliable in-memory cache for big key-value stores

Large-scale key-value stores are widely used in many Web-based systems to store huge amount of data as (key, value) pairs. In order to reduce the latency of accessing such (key, value) pairs, an in-memory cache system is usually deployed between the front-end Web system and the back-end database system. In practice, a cache system may consist of a number of server nodes, and fault tolerance is a critical feature to maintain the latency Service-Level Agreements (SLAs). In this paper, we present the design, implementation, analysis, and evaluation of R-Memcached, a reliable in-memory key-value cache system that is built on top of the popular Memcached software. R-Memcached exploits coding techniques to achieve reliability, and can tolerate up to two node failures. Our experimental results show that R-Memcached can maintain very good latency and throughput performance even during the period of node failures.

Multi Guard Detecting Intrusions in Web Applications

Web services and applications have increased over the past few years. Recently, the web applications are using multi tier design. The front end include web server which can used to process the request and gives that output to back end. An attention of hackers has been focus from attacking the front end and to taint the back-end database system. We present Triple guard system that models the network behaviour of user sessions across both the front-end web server and the back end database and also provides confidential service. By using Triple IDS, we able to ferret out attacks and free from traffic that occur in web application.

Tamper Detection in RFID Tags Using Zero-Watermarks

Recently data integrity issues of applications based on radio frequency identification (RFID) have drawn great concerns worldwide and many watermarking-based schemes have been proposed. While those schemes can effectively verify if the protected tag data be modified, they also expose both the protected data and the watermark to any adversaries. In this paper, we present a zero-watermark scheme, which stores the watermark not in part of the data fields of RFID tags but in the back-end database system or that of a trusted third party without any modification of the original RFID data. The novelty of this zero-watermark scheme lies in the fact that we extend the zero-watermark technology to the RFID tags and the use of data tampering from the limited applications of copyright protection of digital works. We term this scheme ZMark-TamDetect because it is a tamper detection solution using zero-watermarks, which is so designed that it can be easily plugged into existing RFID middleware applications. This proposal is one of the first works that integrates zero-watermark and RFID technologies together and it provides a detailed theoretical foundation for the ZMark-TamDetect.

Design and Implementation of Mine-Map Management Information System Based on B/S Model

Analyzing the existing problems of traditional management model of mine-map and the development significance of mine-map management information system on the basis of B/S model, combining with the actual situation of mining enterprises, this paper designs mine-map management information system on the basis of B/S model using ASP technology, backend database system using Microsoft SQL Server 2000 simplified enterprise edition. The system mainly consists of four main modules such as interface module, system setting module, task assigned module, maps consulting modules, the task of each module is definitude, the function is independent. Field application shows that the system realizes line production of mine-map management, such as submission, examination and approval, storage and consulting etc, enhances the efficiency of examination and approval and management for mine-map.

Experience with Multi-Tier Grid MySQL Database Service Resiliency at BNL

We describe the use of F5's BIG-IP smart switch technology (3600 Series and Local Traffic Manager v9.0) to provide load balancing and automatic fail-over to multiple Grid services (GUMS, VOMS) and their associated back-end MySQL databases. This resiliency is introduced in front of the external application servers and also for the back-end database systems, which is what makes it "multi-tier".The combination of solutions chosen to ensure high availability of the services, in particular the database replication and fail-over mechanism, are discussed in detail. The paper explains the design and configuration of the overall system, including virtual servers, machine pools, and health monitors (which govern routing), as well as the master-slave database scheme and fail-over policies and procedures. Pre-deployment planning and stress testing will be outlined. Integration of the systems with our Nagios-based facility monitoring and alerting is also described. And application characteristics of GUMS and VOMS which enable effective clustering will be explained.We then summarize our practical experiences and real-world scenarios resulting from operating a major US Grid center, and assess the applicability of our approach to other Grid services in the future.

Performance analysis and optimization of AMGA for the large‐scale virtual screening

AbstractThis paper addresses performance issues on ARDA Metadata Grid Application (AMGA) and presents new techniques to improve the throughput of AMGA for the WISDOM environment. The first issue is a performance degradation problem when AMGA is used as a metadata service for task retrieval in the WISDOM environment. To deal with the issue, a new AMGA operation designed to reduce the communication overhead required to retrieve a task from AMGA is proposed. According to a performance study conducted with the new operation, the throughput of task retrieval using the proposed operation can be as much as 70 times higher than the throughput when using the existing AMGA operations. The second issue is an AMGA throughput issue in large‐scale grid‐enabled applications such as WISDOM, where it is not uncommon that thousands of jobs running on grid nodes access the AGMA service simultaneously. To address this issue, integration of a load‐balancing technique and a DB connection pool technique into the AMGA are proposed. Test results demonstrate that the performance can be improved linearly in proportion to the number of AMGA servers set up for load balancing; the performance improvement continues until the performance limit of the backend database system is reached. Copyright © 2009 John Wiley & Sons, Ltd.

CREATING AND UTILIZING METHOD OF DETAILED DIGITAL ARCHIVE FOR ARCHITECTURE

In the movement of making digital archives of cultural assets, you can see the similar approaches in the architectural field. Most of these are simply creating computer graphics of outside appearance, few are precisely digitizing inside mechanism. Considering academic significance, the latter are more valuable than the former. Precisely detailed digital archive includes huge amount of three-dimensional geometric data, illustration and commentary, so that it requires sophisticated system for managing data consistency.The authors customized a commercial 3D CAD system to interactively communicate with a backend relational database system which stores various building information. In this paper, the authors propose brand-new digital-archive method using the "CAD w/ DB" system.

Scalable query result caching for web applications

The backend database system is often the performance bottleneck when running web applications. A common approach to scale the database component is query result caching, but it faces the challenge of maintaining a high cache hit rate while efficiently ensuring cache consistency as the database is updated. In this paper we introduce Ferdinand, the first proxy-based cooperative query result cache with fully distributed consistency management. To maintain a high cache hit rate, Ferdinand uses both a local query result cache on each proxy server and a distributed cache. Consistency management is implemented with a highly scalable publish/subscribe system. We implement a fully functioning Ferdinand prototype and evaluate its performance compared to several alternative query-caching approaches, showing that our high cache hit rate and consistency management are both critical for Ferdinand's performance gains over existing systems.

Multitiered Cache Management and Acceleration for Database-Driven Websites

Response time is a key differentiation point among electronic commerce (e-commerce) applications. For many e-commerce applications, web pages are created dynamically based on the current state of a business stored in database systems. To improve the response time, many e-commerce websites deploy caching solutions for acceleration of content delivery. There are multiple tiers in the content delivery infrastructure where cache servers can be deployed, including (1) data caching (in data centers), (2) content page caching (in edge or front end caches), and (3) database query result set caching (between application servers and DBMS). The architecture of database-driven e-commerce websites is more complex than that of typical websites. It requires the integration of web servers, application servers, and back end database systems as well as dynamic content caching solutions. In this paper, the issues associated with the management of content page caching and database query result set caching tiers are studied. It is observed that caching management for these two tiers have their unique characteristics. It is because cached object types and information available for the caching management in the two tiers are different. Solutions are proposed for effective caching management for each tier and extensive evaluations are conducted. The experimental results show the usefulness of the technology in improving overall system performance.

Evaluations of architectural designs and implementation for database-driven web sites

Response time is a key differentiation point among electronic commerce (e-commerce) applications. For many e-commerce applications, Web pages are created dynamically based on the current business state, stored in database systems. The architecture of database-driven e-commerce Web sites are more complex than that of typical Web sites. It requires integration of Web servers, application servers, and back-end database systems as well as synchronization of multiple databases if caches are used for acceleration of content delivery. In this paper, we analyze the factors that impact the performance and scalability of a database-driven Web site. We experimentally test (1) the performance metrics of database update, query, and synchronization; (2) trigger overhead; and (3) application server (AS) and database connection overhead and constraints. We describe several architectural design approaches for database-driven Web sites and present experimental results on their performance under various conditions, including varying request rates, update-to-request ratio, cache hit ratio, number of regional AS/data cache suites deployed, and database size. We also discuss how to handle Web page requests that involve SSL, cookies, and fragment pages (i.e. by frame or JSP).

The Design of Metadata Interchange for Chinese Information and Implementation of Metadata Management System

With the development of Internet, digital libraries/museums have received worldwide attention and many developed countries are doing extensive researches on digital libraries/museums. In Taiwan, many institutions have digitized their collections. In addition, major research projects such as Digital Museum Project, Digital Archive Program, Digital Local Document Program, and CMNet are either in progress or about to begin. To digitize resources and present them on the WWW is the first priority; nevertheless, it is more important to organize these resources based on their characteristics, so users may retrieve and use them effectively. In digital library/museum systems, metadata plays a crucial role: its formulation has to begin with understanding the user demands and object characteristics, and standardization is essential for * The work is partially supported by National Science Council under grant NSC 89-2750-P-002-012.

Performance analysis of several backend database system architectures

Performance analysis of several backend database system architectures