Real-time positioning of a specific object in the big data environment

Abstract

Abstract Real-time positioning of a specific object in the big data environment can improve the monitoring and management capacity for network data. For the real-time positioning of the specific object, it is necessary to quickly search the network data representing a specific object and match its pattern strings and compare the corresponding Internet protocol (IP) address of the matched network data with the IP address library in real time, so as to determine the position of the specific object. When a traditional method is used for pattern string matching, it will occupy a lot of memories and network resources, thereby reducing the positioning effect of the specific object in the big data environment. A positioning method for a specific object of high performance and multi-pattern matching based on three indexes in the big data network environment is proposed in this paper. Firstly, the initialization of Modified Wu-Manber (MWM) algorithm was carried out, and the algorithm was used to match the network data continuously. Secondly, the three indexes were used to improve the MWM algorithm, and the real-time and fast positioning of a specific object in the big data environment was completed by the Third Index Modified Wu-Manber (TMWM). The experimental results show that compared with the traditional method, the proposed algorithm reduces the pattern string matching scope of network data representing the specific object, improves the search speed of the specific object, and locates the specific object in the big data environment in an effective and rapid manner.

Keywords

• Big data
• Specific object
• TMWM
• Positioning