logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

A Collaborative Service Deployment and Application Assignment Method for Regional Edge Computing Enabled IoT

delete2020-01-01
delete8
delete
OA
AI
陈
陈焰 (Yan Chen)
Y
Yanjing Sun *
T
Tianxin Feng
宋力 cover
宋力 (Song Li)
DOI：10.1109/ACCESS.2020.3002813delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Edge computing brings powerful computing ability to the proximity of IoT devices to guarantee latency constraints, making it one essential technology for supporting intelligent applications in future Internet of Things (IoT). Collaboration among edge computing servers (ECSs) with limited resources is an efficient solution to enhance the capability of edge network, and placement of ECSs and service functions (SFs) impose significant influences on system performance. This paper explores the collaboration among ECSs by considering the simultaneous and heterogeneous consumption of different computing resources. The service deployment and application assignment in regional edge computing enabled IoT (EdgeIoT) are investigated. A collaborative service deployment and application assignment (ColSDA) algorithm is proposed to render the final edge service deployment strategy, including the placement of ECSs and SFs as well as the assignment of applications to ECSs. In ColSDA, the minimum number of ECSs to be placed is obtained by the proposed minimum resource ration increase (MinRI) algorithm. Computing loads are then balanced by the load-balancing reassignment (LBRA) algorithm. After placing ECSs, a search and swap (SeSw) algorithm is proposed to further increase the number of tasks processed by locally deployed ECSs. Simulation results demonstrate that the number of required ECSs under the premise of guaranteeing the quality of service (QoS) can be significantly reduced by establishing collaboration among ECSs. Besides, the proposed ColSDA algorithm can provide the service deployment and application assignment strategy for a given region EdgeIoT as expected.
Keywords:
Task analysis
Collaboration
Edge computing
Quality of service
Servers
Cloud computing
Internet of Things
Edge computing
service deployment
application assignment
the~Internet of Things
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

No organization information available