文献
J-GLOBAL ID:202202250397612641
整理番号:22A1163611
深層強化学習による大規模モバイルエッジ計算のための効率的なオンライン計算オフローディングアプローチ【JST・京大機械翻訳】
An Efficient Online Computation Offloading Approach for Large-Scale Mobile Edge Computing via Deep Reinforcement Learning
著者 (7件):
Hu Zheyuan
(State Key Laboratory of Virtual Reality Technology and Systems, and Beijing Advanced Innovation Center for Big Data and Brain Computing, School of Computer Science and Engineering, Beihang University, Beijing, China)
,
Niu Jianwei
(State Key Laboratory of Virtual Reality Technology and Systems, and Beijing Advanced Innovation Center for Big Data and Brain Computing, School of Computer Science and Engineering, Beihang University, Beijing, China)
,
Ren Tao
(Hangzhou Innovation Institute, Beihang University, Hangzhou, China)
,
Dai Bin
(State Key Laboratory of Virtual Reality Technology and Systems, and Beijing Advanced Innovation Center for Big Data and Brain Computing, School of Computer Science and Engineering, Beihang University, Beijing, China)
,
Li Qingfeng
(Hangzhou Innovation Institute, Beihang University, Hangzhou, China)
,
Xu Mingliang
(School of Information Engineering, Zhengzhou University, Zhengzhou, China)
,
Das Sajal K.
(Department of Computer Science, Missouri University of Science and Technology, Rolla, MO, USA)
資料名:
IEEE Transactions on Services Computing
(IEEE Transactions on Services Computing)
巻:
15
号:
2
ページ:
669-683
発行年:
2022年
JST資料番号:
W2437A
ISSN:
1939-1374
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)