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Journal of Intelligent Systems and Internet of Things
Volume 4 , Issue 1, PP: 08-25 , 2021 | Cite this article as | XML | Html |PDF

Title

Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment

  Mustafa El-Taie 1 * ,   Aaras Y.Kraidi 2

1  Digital Charging Solutions GmbH, Germany
    (Mustafa.iessa@gmail.com)

2  University of Technology and Applied Science, Shinas, Oman
    (aaras.kraidi@shct.edu.om)

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Doi   :   https://doi.org/10.54216/JISIoT.040101

Received: January 21, 2021 Accepted: may 15, 2021

Abstract :

The crowd-creation space is a manifestation of the development of innovation theory to a certain stage. With the creation of the crowd-creation space, the problem of optimizing the resource allocation of the crowd-creation space has become a research hotspot. The emergence of cloud computing provides a new idea for solving the problem of resource allocation. Common cloud computing resource allocation algorithms include genetic algorithms, simulated annealing algorithms, and ant colony algorithms. These algorithms have their obvious shortcomings, which are not conducive to solving the problem of optimal resource allocation for crowd-creation space computing. Based on this, this paper proposes an In the cloud computing environment, the algorithm for optimizing resource allocation for crowd-creation space computing adopts a combination of genetic algorithm and ant colony algorithm and optimizes it by citing some mechanisms of simulated annealing algorithm. The algorithm in this paper is an improved genetic ant colony algorithm (HGAACO). In this paper, the feasibility of the algorithm is verified through experiments. The experimental results show that with 20 tasks, the ant colony algorithm task allocation time is 93ms, the genetic ant colony algorithm time is 90ms, and the improved algorithm task allocation time proposed in this paper is 74ms, obviously superior. The algorithm proposed in this paper has a certain reference value for solving the creative space computing optimization resource allocation.

Keywords :

Cloud Computing , Crowd Creation Space , Optimized Resource Allocation , Algorithm Optimization , Improved Genetic Ant Colony Algorithm

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Cite this Article as :
Style #
MLA Mustafa El-Taie , Aaras Y.Kraidi. "Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment." Journal of Intelligent Systems and Internet of Things, Vol. 4, No. 1, 2021 ,PP. 08-25 (Doi   :  https://doi.org/10.54216/JISIoT.040101)
APA Mustafa El-Taie , Aaras Y.Kraidi. (2021). Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment. Journal of Journal of Intelligent Systems and Internet of Things, 4 ( 1 ), 08-25 (Doi   :  https://doi.org/10.54216/JISIoT.040101)
Chicago Mustafa El-Taie , Aaras Y.Kraidi. "Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment." Journal of Journal of Intelligent Systems and Internet of Things, 4 no. 1 (2021): 08-25 (Doi   :  https://doi.org/10.54216/JISIoT.040101)
Harvard Mustafa El-Taie , Aaras Y.Kraidi. (2021). Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment. Journal of Journal of Intelligent Systems and Internet of Things, 4 ( 1 ), 08-25 (Doi   :  https://doi.org/10.54216/JISIoT.040101)
Vancouver Mustafa El-Taie , Aaras Y.Kraidi. Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment. Journal of Journal of Intelligent Systems and Internet of Things, (2021); 4 ( 1 ): 08-25 (Doi   :  https://doi.org/10.54216/JISIoT.040101)
IEEE Mustafa El-Taie, Aaras Y.Kraidi, Optimized Resource Allocation Algorithm for Crowd-Creation Space Computing Based on Cloud Computing Environment, Journal of Journal of Intelligent Systems and Internet of Things, Vol. 4 , No. 1 , (2021) : 08-25 (Doi   :  https://doi.org/10.54216/JISIoT.040101)
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