JAVP: Joint-Aware Video Processing with Edge-Cloud Collaboration for DNN Inference

Yang, Zheming; Ji, Wen; Guo, Qi; Wang, Zhi

doi:10.1145/3581783.3613914

Cited by 2 publications

(1 citation statement)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…what happened and why it happened) and predict the future (i.e. what will happen and what should be done) of cloud computing resource allocation [10][11]. For example, a reinforcement learning algorithm for efficient virtual machine allocation on cloud computing systems that utilize multi-servers was proposed [12].…”

Section: Introductionmentioning

confidence: 99%

Data Analytics Techniques for Addressing Cloud Computing Resources Allocation Challenges: A Bibliometric Analysis Approach

Sekwatlakwatla,

Malele

2024

J. Inf. Syst. Informatics

View full text Add to dashboard Cite

The increase in the use of digital technology led to an increase in online activities. In this regard, many organizations adopted cloud computing systems to manage this online traffic. It is plan of every cloud computing resource provider to manage their system effectively and efficiently. This paper uses bibliometric analysis technique to look at the prevalence of utilization of data analytics techniques in addressing cloud computing resource allocation challenges. In this regard, the following research databases the Association for Computing Machinery, the Institute of Electrical and Electronics Engineering, Web of Science and Scopus databases, were consulted. The research articles published before the beginning of 2017 to 2023 were considered as part of the analysis. The results showed that the prevalent data analytics techniques used to address the cloud computing resources allocation challenge are Support Vector Machine, Spatio-temporal and edge-cloud collaborative scheme. Failure to effectively and efficiently provide cloud computing management resource allocation will lead to system bottlenecks especially during peak periods. In this regard, such a failure could lead to dissatisfied clients.

show abstract

Section: Introductionmentioning

confidence: 99%