TY - JOUR
T1 - Resource Management in Cloud and Cloud-influenced Technologies for Internet of Things Applications
AU - Jeyaraj, Rathinaraja
AU - Balasubramaniam, Anandkumar
AU - Kumara, M. A.Ajay
AU - Guizani, Nadra
AU - Paul, Anand
N1 - Publisher Copyright:
© 2023 Association for Computing Machinery.
PY - 2023/3/2
Y1 - 2023/3/2
N2 - The trend of adopting Internet of Things (IoT) in healthcare, smart cities, Industry 4.0, and so on is increasing by means of cloud computing, which provides on-demand storage and computation facilities over the Internet. To meet specific requirements of IoT applications, the cloud has also shifted its service offering platform to its next-generation models, such as fog, mist, and dew computing. As a result, the cloud and IoT have become part and parcel of smart applications that play significant roles in improving the quality of human life. In addition to the inherent advantages of advanced cloud models, to improve the performance of IoT applications further, it is essential to understand how the resources in the cloud and cloud-influenced platforms are managed to support various phases in the end-to-end IoT deployment. Considering this importance, in this article, we provide a brief description, a systematic review, and possible research directions on every aspect of resource management tasks, such as workload modeling, resource provisioning, workload scheduling, resource allocation, load balancing, energy management, and resource heterogeneity in such advanced platforms, from a cloud perspective. The primary objective of this article is to help early researchers gain insight into the underlying concepts of resource management tasks in the cloud for IoT applications.
AB - The trend of adopting Internet of Things (IoT) in healthcare, smart cities, Industry 4.0, and so on is increasing by means of cloud computing, which provides on-demand storage and computation facilities over the Internet. To meet specific requirements of IoT applications, the cloud has also shifted its service offering platform to its next-generation models, such as fog, mist, and dew computing. As a result, the cloud and IoT have become part and parcel of smart applications that play significant roles in improving the quality of human life. In addition to the inherent advantages of advanced cloud models, to improve the performance of IoT applications further, it is essential to understand how the resources in the cloud and cloud-influenced platforms are managed to support various phases in the end-to-end IoT deployment. Considering this importance, in this article, we provide a brief description, a systematic review, and possible research directions on every aspect of resource management tasks, such as workload modeling, resource provisioning, workload scheduling, resource allocation, load balancing, energy management, and resource heterogeneity in such advanced platforms, from a cloud perspective. The primary objective of this article is to help early researchers gain insight into the underlying concepts of resource management tasks in the cloud for IoT applications.
KW - Additional Key Words and PhrasesCloud computing
KW - dew computing
KW - edge computing
KW - fog computing
KW - Internet of Things
KW - load balancing
KW - mist computing
KW - resource allocation
KW - resource heterogeneity
KW - resource provisioning
KW - resource scheduling
UR - http://www.scopus.com/inward/record.url?scp=85152599136&partnerID=8YFLogxK
U2 - 10.1145/3571729
DO - 10.1145/3571729
M3 - Article
AN - SCOPUS:85152599136
SN - 0360-0300
VL - 55
JO - ACM Computing Surveys
JF - ACM Computing Surveys
IS - 12
M1 - 3571729
ER -