Recent proliferation of mobile devices and edge servers (e.g., small base stations) strongly motivates distributed learning at the wireless edge. In this paper, we propose a fast and secure distributed learning framework that utilizes computing resources at edge servers as well as distributed computing devices in tiered wireless edge networks. A fundamental lower bound is derived on the computational load that perfectly tolerates Byzantine attacks at both tiers. TiBroco, a hierarchical coding framework achieving this theoretically minimum computational load is proposed, which guarantees secure distributed learning by combating Byzantines. A fast distributed learning is possible by precisely allocating loads to the computing devices and edge servers, and also utilizing the broadcast nature of wireless devices. Extensive experimental results on Amazon EC2 indicate that our TiBroco allows significantly faster distributed learning than existing methods while guaranteeing full tolerance against Byzantine attacks at both tiers.
|Title of host publication||INFOCOM 2021 - IEEE Conference on Computer Communications|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 2021 May 10|
|Event||40th IEEE Conference on Computer Communications, INFOCOM 2021 - Vancouver, Canada|
Duration: 2021 May 10 → 2021 May 13
|Name||Proceedings - IEEE INFOCOM|
|Conference||40th IEEE Conference on Computer Communications, INFOCOM 2021|
|Period||21/5/10 → 21/5/13|
Bibliographical noteFunding Information:
This work was supported by National Research Foundation of Korea (No. 2019R1I1A2A02061135).
© 2021 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Electrical and Electronic Engineering