Data storage and query method based on classification characteristics and balanced binary tree

A balanced binary tree and data storage technology, applied in the field of Internet of Things communication, can solve the problems that it is difficult to meet the real-time requirements of large data volume processing and high time complexity, and achieve fast and efficient storage and query, low algorithm complexity, and improved efficiency effect

Inactive Publication Date: 2012-06-27
GUANGDONG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Traditional static search methods such as sequential search, binary search, and index search are difficult to meet the real-time requirements of current large data processing
For dynamic search (DST), such as binary search tree, B-tree, hash (Hash) search method, key tree, etc., its time complexity is much higher than that of static search

Method used

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  • Data storage and query method based on classification characteristics and balanced binary tree
  • Data storage and query method based on classification characteristics and balanced binary tree
  • Data storage and query method based on classification characteristics and balanced binary tree

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Embodiment Construction

[0050] The present invention will be further described below in conjunction with the accompanying drawings and examples, taking in-order traversal as an example.

[0051] The present invention is a data storage and fast query method for a large amount of data applied in the communication field of the Internet of Things. For example, for 50,000 people in the terminal site in the Internet of Things (number of nodes N=50,000), IC card number (1 byte), name (10 bytes), personnel number (2 bytes), attendance information (2 bytes) ), assisted inquiry notification information (200 bytes) and other related information are managed in a unified manner. The terminal RAM space resource is 8M. For data information inquiry, you can use card swiping and manual inquiry.

[0052] In view of the above requirements, the present invention is used to realize the AVL tree as the node class index, and the left pointer (4 bytes), the IC card number (1 byte), and the node information storage address (...

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Abstract

The invention discloses a data storage and query method based on classification characteristics and balanced binary tree. The method comprises the following steps: constructing a balanced binary tree to create nodes; dynamically classifying and storing data information in corresponding nodes according to the sequence of inorder traversal, preorder traversal and postorder traversal; and inputting an enquired content, dynamically traversing the AVL tree to obtain the desired data information. The method provided by the invention can lower the time complexity of dynamic query to static query level, thereby greatly improving storage and query efficiency. The method has the advantages of high speed, low energy consumption, less memory usage, and simple algorithm, and can be implemented by a plurality of languages. The method is widely suitable for data management in the communication field, in particular to massive data storage and query in communication of the internet of things.

Description

technical field [0001] The invention belongs to the field of large data storage and query methods in the communication field of the Internet of Things, in particular to a data storage and query method based on classification characteristics and a balanced binary tree. Background technique [0002] In communication technology, traditional data query methods include static search methods and dynamic search methods. Static search methods include sequential search, binary search, and index search; dynamic search methods include binary search tree, B-tree, hash (Hash) search method, key tree, etc. [0003] In the sequential search, it is assumed that for a lookup table with n records, the average search length when the search is successful is ASL (Average Search Length), ASL= = , and the number of comparisons is =n-i+1, and the probability of finding is P i = Then ASL=nP 1 +(n-1)P 2 +...+2P n-1 +P n = = , then its algorithm time complexity is O(n). [0004] Bi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCY02D10/00
Inventor 韩一石孙运龙王建华黄明政
Owner GUANGDONG UNIV OF TECH
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