Real-Time Query Processing on Live Videos in Networks of Distributed Cameras

2012 ◽  
pp. 27-48 ◽  
Author(s):  
Rui Peng ◽  
Alex J. Aved ◽  
Kien A. Hua
Keyword(s):  
Query Processing ◽  
Real Time ◽  
Database Management ◽  
High Speed ◽  
Query Language ◽  
Optimization Technique ◽  
Database Management System ◽  
Live Video ◽  
Storage Devices ◽  
Distributed Cameras

With the proliferation of inexpensive cameras and the availability of high-speed wired and wireless networks, systems of distributed cameras are becoming an enabling technology for a broad range of interdisciplinary applications in domains such as public safety and security, manufacturing, transportation, and healthcare. Today’s live video processing systems on networks of distributed cameras, however, are designed for specific classes of applications. To provide a generic query processing platform for applications of distributed camera networks, the authors designed and implemented a new class of general purpose database management systems, the live video database management system (LVDBMS). The authors view networked video cameras as a special class of interconnected storage devices, and allow the user to formulate ad hoc queries expressed over real-time live video feeds. This paper introduces their system and presents the live video data model, the query language, and the query processing and optimization technique.

Real-Time Query Processing on Live Videos in Networks of Distributed Cameras

2010 ◽  
Vol 2 (1) ◽  
pp. 27-48 ◽  
Author(s):  
Rui Peng ◽  
Alex J. Aved ◽  
Kien A. Hua
Keyword(s):  
Query Processing ◽  
Real Time ◽  
Database Management ◽  
High Speed ◽  
Query Language ◽  
Optimization Technique ◽  
Database Management System ◽  
Video Data ◽  
Live Video ◽  
Distributed Cameras

With the proliferation of inexpensive cameras and the availability of high-speed wired and wireless networks, systems of distributed cameras are becoming an enabling technology for a broad range of interdisciplinary applications in domains such as public safety and security, manufacturing, transportation, and healthcare. Today’s live video processing systems on networks of distributed cameras, however, are designed for specific classes of applications. To provide a generic query processing platform for applications of distributed camera networks, the authors designed and implemented a new class of general purpose database management systems, the live video database management system (LVDBMS). The authors view networked video cameras as a special class of interconnected storage devices, and allow the user to formulate ad hoc queries expressed over real-time live video feeds. This paper introduces their system and presents the live video data model, the query language, and the query processing and optimization technique.

MonogDB

2017 ◽  
pp. 64-91
Author(s):  
Sonali Tidke
Keyword(s):  
Management System ◽  
Database Management ◽  
Query Language ◽  
Database Management System ◽  
Management Model ◽  
Nosql Databases ◽  
Performance Indexes ◽  
And Behavior ◽  
Relational Database Management ◽  
Partitioning Technique

MongoDB is a NoSQL type of database management system which does not adhere to the commonly used relational database management model. MongoDB is used for horizontal scaling across a large number of servers which may have tens, hundreds or even thousands of servers. This horizontal scaling is performed using sharding. Sharding is a database partitioning technique which partitions large database into smaller parts which are easy to manage and faster to access. There are hundreds of NoSQL databases available in the market. But each NoSQL product is different in terms of features, implementations and behavior. NoSQL and RDBMS solve different set of problems and have different requirements. MongoDB has a powerful query language which extends SQL to JSON enabling developers to take benefit of power of SQL and flexibility of JSON. Along with support for select/from/where type of queries, MongoDB supports aggregation, sorting, joins as well as nested array and collections. To improve query performance, indexes and many more features are also available.

SQL Code Poisoning

2011 ◽  
pp. 161-171
Author(s):  
Theodoros Tzouramanis
Keyword(s):  
Anomaly Detection ◽  
Management System ◽  
Database Management ◽  
Query Language ◽  
Database Management System ◽  
Sql Injection ◽  
Database Administrator ◽  
Structured Query Language ◽  
Sql Injection Attack ◽  
Cross Site

Anomaly Detection; Cookie Poisoning; CRLF Injection Attack; Cross-Site Scripting (or CSS) Attack Database Administrator (DBA); Database Management System (DBMS); Database Structured Query Language (SQL); Directory Traversal Attack; Google Hacking Attack; Secrecy; Integrity; and Availability; SQL Code Poisoning (or SQL Injection) Attack

scholarly journals PENGERIAN DAN KOMPONEN SQL MUHAMMAD DENNY PRAYOGA 165100046

2018 ◽  
Author(s):  
Muhammad denny prayoga
Keyword(s):  
Relational Database ◽  
Management System ◽  
Database Management ◽  
Query Language ◽  
Database Management System ◽  
Relational Database Management System ◽  
Structured Query Language ◽  
Relational Database Management

Pengertian SQLSQL (Structured Query Language) adalah sebuah bahasa yang digunakan untuk mengakses data dalam basis data relasional.SQL secara de facto merupakan bahasa standar yang digunakan dalam RDBMS (relational database management system).Saat ini hampir semua server basis data yang ada mendukung bahasa SQL untuk melakukan manajemen datanya.SQL merupakan bahasa baku (ANSI/SQL), non prosedural dan berorientasi himpunan (set oriented language)SQL dapat digunakan baik secara interaktif atau ditempelkan (embedded) pada sebuah program aplikasi.

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