Adaptive Cloud Resource Scheduling Model Based on Improved Ant Colony Algorithm

2020 ◽  
Vol 57 (1) ◽  
pp. 010603
Author(s):  
聂清彬 Nie Qingbin ◽  
潘峰 Pan Feng ◽  
吴嘉诚 Wu Jiacheng ◽  
曹耀钦 Cao Yaoqin
Keyword(s):  
Ant Colony Algorithm ◽  
Resource Scheduling ◽  
Ant Colony ◽  
Model Based ◽  
Scheduling Model ◽  
Cloud Resource ◽  
Cloud Resource Scheduling ◽  
Improved Ant Colony Algorithm

Application and Analysis of Improved Ant Colony Algorithm in Physical Fitness Test

2021 ◽  
Vol 7 (5) ◽  
pp. 5009-5017
Author(s):  
Lili Zhang
Keyword(s):  
Physical Fitness ◽  
Shortest Path ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Physical Fitness Test ◽  
Physical Test ◽  
Fitness Test ◽  
Model Based ◽  
Physical Tests ◽  
Improved Ant Colony Algorithm

Objectives: The ant colony algorithm is an algorithm that the Italian scholar sums up by studying the living habits of the creatures, and algorithm model established by inspiration according to ants finding things in the shortest path. Methods: In this paper, through the establishment of algorithm model based on an ant colony algorithm, all kinds of problems in physical fitness test were solved, which makes the physical test more efficient and convenient. Results: Through the testing and use of the algorithm model, it is found that the ant colony algorithm established in this paper can meet the requirements, can plan the information of physical fitness test as a whole, Conclusion: and help to deal with the problems of physical tests, so it is a good performance algorithm.

scholarly journals Design of Intelligent Building Scheduling System for Internet of Things and Cloud Computing

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Tiangang Wang ◽  
Zhe Mi
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Real Time ◽  
High Speed ◽  
Ant Colony Algorithm ◽  
Resource Scheduling ◽  
Ant Colony ◽  
Local Optimum ◽  
The Real ◽  
Improved Ant Colony Algorithm

The cloud computing (CC) and Internet of Things (IoT) are widely utilized and provided for intelligent perception and on-demand utilization like industries and public areas. The full sharing, free circulation and various manufacturing resources allocation are investigated in manufacturing. In order to ensure the real-time and effectiveness of resource storage scheduling in Internet of things information system, there are many kinds and quantities of building equipment. An improved ant colony algorithm is presented to remove the shortcomings of the existing ant colony algorithm with slow speed and fall into local optimum. The improved ant colony algorithm is transplanted into cloud computing environment. The advantages of fast computing and high speed storage of cloud computing can realize the real-time resource scheduling of building equipment. The experimental results present that the improved ant colony algorithm can obviously improve the efficiency of resource scheduling in cloud computing environment.All the experiments are performed on the MATLAB.

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