JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Range Segmentation of Dynamic Offloading (RSDO) Algorithm by Correlation for Edge Computing |
| 영문제목(English Title) |
Range Segmentation of Dynamic Offloading (RSDO) Algorithm by Correlation for Edge Computing |
| 저자(Author) |
Jieun Kang
Svetlana Kim
Jae-Ho Kim
Nak-Myoung Sung
Yong-Ik Yoon
|
| 원문수록처(Citation) |
VOL 17 NO. 05 PP. 0905 ~ 0917 (2021. 10) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
In recent years, edge computing technology consists of several Internet of Things (IoT) devices with embedded sensors that have improved significantly for monitoring, detection, and management in an environment where big data is commercialized. The main focus of edge computing is data optimization or task offloading due to data and task-intensive application development. However, existing offloading approaches do not consider correlations and associations between data and tasks involving edge computing. The extent of collaborative offloading segmented without considering the interaction between data and task can lead to data loss and delays when moving from edge to edge. This article proposes a range segmentation of dynamic offloading (RSDO) algorithm that isolates the offload range and collaborative edge node around the edge node function to address the offloading issue. The RSDO algorithm groups highly correlated data and tasks according to the cause of the overload and dynamically distributes offloading ranges according to the state of cooperating nodes. The segmentation improves the overall performance of edge nodes, balances edge computing, and solves data loss and average latency. |
| 키워드(Keyword) |
Balancing
Collaboration Edge Computing
Context-Awareness
Data-Intensive Offloading
IoT
RSDO
Task-Intensive Offloading
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| 파일첨부 |
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