Coding Assisted Cloud-Edge Collaborative Computing

Cloud-edge collaborative computing has emerged as a promising solution to satisfy the demands for intensive computation and low latency. However, the straggler effect in cloud-edge collaborative computing systems is serious but has not been addressed. This can be mitigated by designing an effective computing scheme, with the assistance of cloud server. Moreover, the problem of transmission failure becomes more severe in cloud-edge collaborative computing systems. Specifically, the result downloaded from the edge nodes will be affected by poor channel conditions, while the result transmitted from the cloud to edge nodes will also suffer from packet loss. In this paper, we propose a coding assisted cloud-edge collaborative computing (CA-CECC) scheme to solve these problems. To make it more tractable, we separate the transmission phase from the computation phase, and decouple cooperative transmission from single-point transmission. By dividing the set of cooperative nodes into two sets, we further propose two simplified schemes of low complexity. Their latencies are established as upper bounds on the latency of CA-CECC. Numerical simulation results verify the superiority of our proposed scheme.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Communications
Published
2025-06-09
DOI
https://doi.org/10.1109/tcomm.2025.3577637
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Coding Assisted Cloud-Edge Collaborative Computing

Li Chen, Weidong Wang, Hongtao Zhu, Yunfei Chen
IEEE Transactions on Communications
Cognitive Computing and Networks
article

Coding Assisted Cloud-Edge Collaborative Computing

Li Chen, Weidong Wang, Hongtao Zhu, Yunfei Chen
article en

Abstract

Cloud-edge collaborative computing has emerged as a promising solution to satisfy the demands for intensive computation and low latency. However, the straggler effect in cloud-edge collaborative computing systems is serious but has not been addressed. This can be mitigated by designing an effective computing scheme, with the assistance of cloud server. Moreover, the problem of transmission failure becomes more severe in cloud-edge collaborative computing systems. Specifically, the result downloaded from the edge nodes will be affected by poor channel conditions, while the result transmitted from the cloud to edge nodes will also suffer from packet loss. In this paper, we propose a coding assisted cloud-edge collaborative computing (CA-CECC) scheme to solve these problems. To make it more tractable, we separate the transmission phase from the computation phase, and decouple cooperative transmission from single-point transmission. By dividing the set of cooperative nodes into two sets, we further propose two simplified schemes of low complexity. Their latencies are established as upper bounds on the latency of CA-CECC. Numerical simulation results verify the superiority of our proposed scheme.

IEEE Transactions on CommunicationsVol. 73(11)
University of Science and Technology of China (CN), Durham University (GB)
Openalex Percentile: Top 94%
Cognitive Computing and Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.