<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Through the research of MapReduce programming framework of cloud computing, the current MapReduce program only solves specific problems, and there is no design experience or design feature summary of MapReduce program, let alone formal description and experience inheritance and application of knowledge base. In order to solve the problem of intelligent cloud computing program, a general MapReduce program generation method is designed. This paper proposes the architecture of intelligent cloud computing by studying AORBCO model and combining cloud computing technology. According to the behavior control mechanism in AORBCO model, a program generation method of MapReduce in intelligent cloud computing is proposed. This method will extract entity information in input data set and entity information in knowledge base in intelligent cloud computing for similarity calculation, and extract the entity in the top order as key key-value pair information in intelligent cloud computing judgment data set. The data processing types are divided, and then aligned with each specific MapReduce capability, and the MapReduce program generation experiment is verified in the AORBCO model development platform. The experiment shows that the complexity of big data MapReduce program code is simplified, and the generated code execution efficiency is good.</p>
</abstract>

Through the research of MapReduce programming framework of cloud computing, the current MapReduce program only solves specific problems, and there is no design experience or design feature summary of MapReduce program, let alone formal description and experience inheritance and application of knowledge base. In order to solve the problem of intelligent cloud computing program, a general MapReduce program generation method is designed. This paper proposes the architecture of intelligent cloud computing by studying AORBCO model and combining cloud computing technology. According to the behavior control mechanism in AORBCO model, a program generation method of MapReduce in intelligent cloud computing is proposed. This method will extract entity information in input data set and entity information in knowledge base in intelligent cloud computing for similarity calculation, and extract the entity in the top order as key key-value pair information in intelligent cloud computing judgment data set. The data processing types are divided, and then aligned with each specific MapReduce capability, and the MapReduce program generation experiment is verified in the AORBCO model development platform. The experiment shows that the complexity of big data MapReduce program code is simplified, and the generated code execution efficiency is good.

Research on Intelligentization of Cloud Computing Programs Based on Self-awareness

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Through the research of MapReduce programming framework of cloud computing, the current MapReduce program only solves specific problems, and there is no design...

Research on Intelligentization of Cloud Computing Programs Based on Self-awareness

Data publikacji: 16 sie 2023

Zakres stron: 89 - 98

DOI: https://doi.org/10.2478/ijanmc-2023-0060

Słowa kluczowe
Cloud Computing, Artificial Intelligence, Intelligence, MapReduce, AORBCO Model

© 2023 Hanpeng Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Research on Intelligentization of Cloud Computing Programs Based on Self-awareness

Data publikacji: 16 sie 2023

Zakres stron: 89 - 98

DOI: https://doi.org/10.2478/ijanmc-2023-0060

Słowa kluczoweCloud Computing, Artificial Intelligence, Intelligence, MapReduce, AORBCO Model

© 2023 Hanpeng Liu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Słowa kluczowe
Cloud Computing, Artificial Intelligence, Intelligence, MapReduce, AORBCO Model