TY - GEN
T1 - Dependency-aware task allocation algorithm for distributed edge computing
AU - Lee, Jaewook
AU - Kim, Joonwoo
AU - Pack, Sangheon
AU - Ko, Haneul
N1 - Funding Information:
VII. ACKNOWLEDGEMENT This work was supported in part by Samsung Research in Samsung Electronics and in part by NRF of Korea Grant funded by the Korean Government (MSIP) (No. 2017R1E1A1A01073742).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - To overcome the limitation of standalone edge computing in terms of computing power and resource, a concept of distributed edge computing has been introduced, where application tasks are distributed to multiple edge clouds for collaborative processing. To maximize the effectiveness of the distributed edge computing, we formulate an optimization problem of task allocation minimizing the application completion time. To mitigate high complexity overhead in the formulated problem, we devise a low-complexity heuristic algorithm called dependency-aware task allocation algorithm (DATA). Evaluation results demonstrate that DATA can reduce the completion time up to by 18% compared to conventional dependency-unaware task allocation schemes.
AB - To overcome the limitation of standalone edge computing in terms of computing power and resource, a concept of distributed edge computing has been introduced, where application tasks are distributed to multiple edge clouds for collaborative processing. To maximize the effectiveness of the distributed edge computing, we formulate an optimization problem of task allocation minimizing the application completion time. To mitigate high complexity overhead in the formulated problem, we devise a low-complexity heuristic algorithm called dependency-aware task allocation algorithm (DATA). Evaluation results demonstrate that DATA can reduce the completion time up to by 18% compared to conventional dependency-unaware task allocation schemes.
KW - Distributed edge computing
KW - Heuristic algorithm
KW - Mixed integer non linear program (MINLP)
KW - Optimization
UR - http://www.scopus.com/inward/record.url?scp=85079048228&partnerID=8YFLogxK
U2 - 10.1109/INDIN41052.2019.8972185
DO - 10.1109/INDIN41052.2019.8972185
M3 - Conference contribution
AN - SCOPUS:85079048228
T3 - IEEE International Conference on Industrial Informatics (INDIN)
SP - 1511
EP - 1514
BT - Proceedings - 2019 IEEE 17th International Conference on Industrial Informatics, INDIN 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE International Conference on Industrial Informatics, INDIN 2019
Y2 - 22 July 2019 through 25 July 2019
ER -