TY - JOUR
T1 - Intelligent resource management schemes for systems, services, and applications of cloud computing based on artificial intelligence
AU - Lim, Jong Beom
AU - Lee, Dae Won
AU - Chung, Kwang Sik
AU - Yu, Heon Chang
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.
AB - Recently, artificial intelligence techniques have been widely used in the computer science field, such as the Internet of Things, big data, cloud computing, and mobile computing. In particular, resource management is of utmost importance for maintaining the quality of services, service-level agreements, and the availability of the system. In this paper, we review and analyze various ways to meet the requirements of cloud resource management based on artificial intelligence. We divide cloud resource management techniques based on artificial intelligence into three categories: fog computing systems, edge-cloud systems, and intelligent cloud computing systems. The aim of the paper is to propose an intelligent resource management scheme that manages mobile resources by monitoring devices' statuses and predicting their future stability based on one of the artificial intelligence techniques. We explore how our proposed resource management scheme can be extended to various cloud-based systems.
KW - Artificial intelligence
KW - Cloud computing
KW - Edge-cloud systems
KW - Fog computing
KW - Resource management
UR - http://www.scopus.com/inward/record.url?scp=85074926452&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85074926452&partnerID=8YFLogxK
U2 - 10.3745/JIPS.04.0139
DO - 10.3745/JIPS.04.0139
M3 - Article
AN - SCOPUS:85074926452
SN - 1976-913X
VL - 15
SP - 1192
EP - 1200
JO - Journal of Information Processing Systems
JF - Journal of Information Processing Systems
IS - 5
ER -