Results

[International Journal]

1. Haneul Ko, Hyeonjae Jeong, Daeyoung Jung, and Sangheon Pack*, "Dynamic Split Computing Framework in Distributed Serverless Edge Clouds," IEEE Internet of Things Journal (IoT-J), vol. 11, no. 8, pp. 14523 - 14531, Apr. 2024. (0.5)

2. Hochan Lee, Jaewook Lee, Heewon Kim, and Sangheon Pack*, "Straggler-Aware In-Network Aggregation for Accelerating Distributed Deep Learning," IEEE Transactions on Service Computing, vol. 16, no. 6, pp. 4198-4204, Nov./Dec. 2023. (0.33)

3. Sol Han, Hochan Lee, Subin Han, Heewon Kim, and Sangheon Pack*, "Multi-Tenancy- and Redundancy-Aware In-Network Aggregation using Programmable Switches," IEEE Network, vol. 37, no. 3, pp. 94-100, May/Jun.e 2023. (0.5)

[International Conference]

1. Heewon Kim, Chanbin Bae, Seongyeon Yoon, Haneul Ko, Sangheon Pack, and Dongjin Lee, "Frequency-Aware and Item-Wise In-band Network Telemetry for Per-flow Measurement," in Proc. IEEE International Conference on Computer Communications (INFOCOM) 2024 (Poster), Vancouver, Canada, May 2024. (0.33)

2. Hochan Lee, Haneul Ko, Chanbin Bae, and Sangheon Pack,  "Accelerating Convolutional Neural Network Inference in Split Computing: An In-Network Computing Approach," in Proc. International Conference on Information Networking (ICOIN) 2024, Ho Chi Minh, Vietnam, Jan. 2024. (0.5)

3. Heewon Kim, Seonyeon Yoon, and Sangheon Pack, "Adaptive In-Network Inference using Early-Exits," in Proc. International Workshop on P4 in Europe (EuroP4) 2023, Paris, France, Dec. 2023. (0.5)

4. Hochan Lee, Heewon Kim, Chanbin Bae, Yujin Kim, and Sangheon Pack, "Quantization-Aware In-Network Aggregation for Minimizing Communication Overhead" in Proc. The 19th International Conference on emerging Networking EXperiments and Technologies (CoNEXT) 2023 (Poster), Paris, France, Dec. 2023. (0.5)

5. Heewon Kim, Hochan Lee, and Sangheon Pack, "Traffic-Aware In-Network Aggregation Placement for Multi-Tenant Distributed Machine Learning ," in Proc. International Conference on Computer Communications and Networks (ICCCN) 2023, HI, USA, Jul. 2023. (0.5)

[Domestic Journal/Conference]

1. 김의중, 김희원, 윤성연, 백상헌, "샘플링 기반의 인밴드 네트워크 텔레메트리 기법 연구 동향,"  JCCI 2023, 2023년 4월.  (0.5)

2. 김하은, 김희원, 배찬빈, 백상헌, "분산 머신러닝을 위한 인-네트워크 병합 기술 연구 동향," JCCI 2023, 2023년 4월.  (0.5)

[Patent]

1. 백상헌, 김희원, 윤성연, "프로그래밍 가능한 데이터 평면에서의 적응적 인-네트워크 추론 방법," 출원번호: 10-2023-0189484 (2023년 12월 22일) (0.5)

2. 백상헌, 이호찬,  "분산 학습을 위한 인-네트워크 파라미터 취합 장치 및 방법," 출원번호: 10-2023-0090518 (2023년 7월 12일) (1.0)

3. 백상헌, 김희원, 이호찬, 고한얼, "분산 기계 학습을 위한 인-네트워크 집약 기능 할당 방법," 출원번호: 10-2022-0175233 (2022년 12월 14일, 가출원) (0.5)

Acknowledgement

• This work was supported by Institute for Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2022-0-00531)

• 이 논문은 2022년도 정부(과학기술정보통신부)의 재원으로 정보통신기술진흥센터의 지원을 받아 수행된 연구임 (No. 2022-0-00531)