Adaptive weight load balancing algorithm based on reverse chaotic cuckoo search

A cuckoo search and adaptive weight technology, applied in the field of distributed computing, can solve problems such as slow algorithm convergence and unfavorable global optimization, so as to achieve the effect of improving the effect, reducing service response time, and avoiding shock

Active Publication Date: 2022-03-18
ZHEJIANG SCI-TECH UNIV
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Problems solved by technology

The analysis found that the cloud resource scheduling model based on cuckoo search is not completely suitable for the load balancing scheduling of Web clusters, and the random walk of the algorithm itself may lead to slow convergence speed, which is not conducive to global optimization

Method used

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  • Adaptive weight load balancing algorithm based on reverse chaotic cuckoo search
  • Adaptive weight load balancing algorithm based on reverse chaotic cuckoo search
  • Adaptive weight load balancing algorithm based on reverse chaotic cuckoo search

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Embodiment

[0081] In order to test the effect of the algorithm in the Web cluster load balancing problem, this paper verifies the performance of the improved algorithm by comparing the simulation experiment with the benchmark function. The simulation test environment is as follows: Windows10 operating system, Intel(R) Core(TM) i7-5500CPU 2.40GHa, 8GB memory, Matlab R2014b simulation software. In this paper, four common high-dimensional optimization algorithm test functions are selected for testing, and the test functions are shown in Table 1. 1 ~ f 4 . Among them, the four test functions set the initial range as follows:

[0082] (1) The value range of Rastrigin is x∈[-5.12,5.12], and the theoretical optimal value is 0. This function is a multi-peak function, and the height of the peaks varies, so it is difficult to find the global optimal solution.

[0083] (2) The value range of Griewank is x∈[-20,20], and the theoretical optimal value is 0. There are many local minimum points in th...

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Abstract

The invention discloses an adaptive weight load balancing algorithm based on reverse chaotic cuckoo search, which belongs to the field of distributed computing. The present invention comprises the following steps: S1: FCFS task allocation weight calculation; S2, initializing the population individual; S3, evaluating the fitness of the population individual; S4, evaluating and updating the solutions of each dimension according to the reverse learning strategy; S5, updating the population , iterate again; S6, output the optimal task allocation weight. Considering the characteristics of cluster request task allocation, a task allocation weight model is established. The strategy of mapping the chaotic mutation operator to the cuckoo search population is used to deal with the optimal solution selection and inferior solution update in each stage of the search process. Nest positions in different stages are adjusted by a reversely learned diversity factor. Through the improved algorithm, the efficiency of finding the optimal solution is improved, which effectively improves the optimization efficiency of cuckoo search and is more suitable for cluster load balancing.

Description

technical field [0001] The invention belongs to the field of distributed computing, and in particular relates to an adaptive weight load balancing algorithm based on reverse chaotic cuckoo search. Background technique [0002] With the rapid development of the Internet, the scale of various networked information systems is getting larger and larger, and business scenarios such as "big promotion" and "second kill" make the access traffic increase exponentially. Web clusters use multiple node servers to share the pressure of client requests, thereby increasing the scalability and fault tolerance of the entire site system, and improving system response efficiency and reliability. Web clusters often experience load imbalances, resulting in low system utilization, poor response to user requests, and a sharp drop in service quality. Therefore, how to efficiently balance the load of each server node is a key problem to be solved by the server cluster. [0003] As a relatively new...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F9/50G06F9/48G06N3/00
CPCG06F9/5083G06F9/4881G06N3/006
Inventor 张娜董亮亮包晓安
Owner ZHEJIANG SCI-TECH UNIV
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