An Embedded Cloud Database Service Method for Distributed Industry Monitoring

Abstract

Current client/server or multiagent based embedded database systems are hard to match the quality of service of distributed industry monitoring. To address the issues, an embedded cloud database service (ECDBS) method is proposed. First, an ECDBS framework is constructed, and a dual-timing transaction control (DT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C) method is proposed to increase the real-time performance and stableness of transaction processing. Then, a cloud computing middleware subsystem is developed to perform dynamical device management and real-time DB query, and a distributed network sniff-timing scheduling (DNS <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) algorithm is proposed to improve the efficiency of ECDBS system. Finally, the numerical/industrial experiment results show that the DT <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> C method can improve the real-time performance of transaction processing in a condition that guaranteed the accessing stability, and the data transfer rate can reach more than 20 MB/s; the DNS <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> algorithm can perform the better throughput and time delay, and decrease the power consumption; compared with the MySQL and Berkeley DB, the total transaction processing time can decrease 45.5% and 36.7%, respectively.