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Resource optimization in edge and SDN-based edge computing: a comprehensive study

delete2024-02-08
delete5
PRE
AI
A
Ajay Nain
S
Sophiya Sheikh *
M
Mohammad Shahid
R
Rohit Malik
DOI:10.1007/s10586-023-04256-8delete
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摘要

摘要

En 中文
The proliferation of mobile devices and the increasing use of networked applications have generated enormous data that require real-time processing and low-latency responses. For real-time applications, Edge Computing (EC) gained a lot of attention which helps to overcome the challenges with traditional computing systems. There is a massive growth of data generated at the web edge, but its limited computing resources and boundary dynamics pose significant challenges. For proficient resource utilization and network management, Software-Defined Networks (SDN) integration with EC can provide control and programmability in edge networking management. However, the optimization of resources is a fundamental need and challenge of EC based on SDN. Besides, the utilization of SDN in EC deals with a centralized and distributed infrastructure further enables the processing of data in closer proximity to its origin and helps in the growing demand for efficient and high-performance computing systems. This study presents a systematic review of the current state-of-the-art pertaining to resource optimization in EC and its integration with SDN. The review of challenges, benefits, and various proposed methodologies for managing resources in Edge and SDN-based Edge environments are investigated. This paper offers valuable insights into the current state and future directions of Edge, SDN-based EC systems, which can assist organizations in designing and deploying more efficient resource consumption solutions
Keyword:
Resource optimization
Resource management
Edge computing
SDN-based edge computing
Dynamic environment

期刊

C
Cluster Computing-The Journal of Networks Software Tools and Applications
IF:
4.1
论文数:
5.1K
被引数:
7.5K

机构

L
lovely professional university
学者数:
5.1K
论文数: 4.1K
被引数: 5
A
aligarh muslim university
学者数:
5.6K
论文数: 5.2K
被引数: 4
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