Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Intelligent architecture and platforms for private edge cloud systems: A review
AU - Xu, Xiyuan
AU - Zang, Shaobo
AU - Bilal, Muhammad
AU - Xu, Xiaolong
AU - Dou, Wanchun
PY - 2024/11/30
Y1 - 2024/11/30
N2 - The development of cloud, fog, and edge computing has led to great advances in reducing latency and saving bandwidth, and these methods have therefore been broadly applied in various domains, including healthcare, transportation, and the Internet of Things (IoT). Traditional edge computing solutions have proven to be insufficient in fulfilling the demanding prerequisites of low latency and high data rates. Additionally, publicly available edge cloud solutions fail to meet the required standards for ensuring privacy protection. Consequently, Private Edge Cloud Systems (PECSs) have garnered attention as a prospective solution owing to their capacity to mitigate privacy risks and their significant computing capacity. PECS research has seen significant growth, but there is a lack of detailed review of its issues, approaches, and applications in the literature. To explore the potential application value of PECS, this paper provides a systematic review of intelligent platforms and architecture for PECSs. Specifically, an overview of the fundamental characteristics of PECSs is provided. Second, we classify intelligent platforms and architectures and analyze their implementation techniques and realization methods. Third, we discuss four specific application scenarios. Finally, promising future research directions are discussed. The findings of this research show that PECSs can effectively meet the requirements for low latency and privacy protection and are a fertile domain for further research.
AB - The development of cloud, fog, and edge computing has led to great advances in reducing latency and saving bandwidth, and these methods have therefore been broadly applied in various domains, including healthcare, transportation, and the Internet of Things (IoT). Traditional edge computing solutions have proven to be insufficient in fulfilling the demanding prerequisites of low latency and high data rates. Additionally, publicly available edge cloud solutions fail to meet the required standards for ensuring privacy protection. Consequently, Private Edge Cloud Systems (PECSs) have garnered attention as a prospective solution owing to their capacity to mitigate privacy risks and their significant computing capacity. PECS research has seen significant growth, but there is a lack of detailed review of its issues, approaches, and applications in the literature. To explore the potential application value of PECS, this paper provides a systematic review of intelligent platforms and architecture for PECSs. Specifically, an overview of the fundamental characteristics of PECSs is provided. Second, we classify intelligent platforms and architectures and analyze their implementation techniques and realization methods. Third, we discuss four specific application scenarios. Finally, promising future research directions are discussed. The findings of this research show that PECSs can effectively meet the requirements for low latency and privacy protection and are a fertile domain for further research.
U2 - 10.1016/j.future.2024.06.024
DO - 10.1016/j.future.2024.06.024
M3 - Journal article
VL - 160
SP - 457
EP - 471
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
SN - 0167-739X
ER -