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Enabling Deterministic Tasks with Multi-Access Edge Computing in 5G Networks

Deterministic executions of computation-intensive and delay-sensitive tasks are vital for realizing Industry 4.0. Multi-access edge computing (MEC) enables critical tasks to be offloaded to the network edge for quickly responding and processing tasks locally. However, during workload peaks at the resource-limited edge, the best effort IP forwarding in the typical network architecture incurs long-tail latency at both the access and interconnection networks of MEC systems. The long-tail latency results in strict service level agreements (SLAs) unable to be guaranteed in end-to-end communication. In this article, we propose a task deterministic network (TDN) architecture that provides communication with bounded low latency and zero jitter for critical tasks among MEC systems. In TDN, the cross-domain collaboration mechanisms of the layer 2/layer 3 deterministic networking and 5G are jointly designed to eliminate the long-tail latency in typical MEC system networks. In addition, we design a seamless working scheme for the time-sensitive networking controller, the MEC orchestrator, and other coordinators to enable edge collaboration and global deterministic forwarding. Moreover, the main functions of TDN are detailed, including clock synchronization, network slicing, cycle mapping, and multi-layer collaboration. Finally, we present simulation results to substantiate the performance of TDN for accommodating critical service flows among MEC systems.

Ketersediaan

Informasi Detail

Judul Seri

IEEE COMMUNICATIONS MAGAZINE; Vol.60 No.8 August 2022

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 36-42

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

COMPUTER ARCHITECTURE
COLLABORATION
SYNCHRONIZATION
DELAYS
5G MOBILE COMMUNICATION
TASK ANALYSIS
SERVERS

Info Detail Spesifik

DOI: 10.1109/MCOM.001.2101073

Pernyataan Tanggungjawab

Guoyu Peng, Shuo Wang, Yudong Huang, Tao Huang, Yunjie Liu

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