Coding-Based Large-Scale Task Assignment for Industrial Edge Intelligence
Coding-Based Large-Scale Task Assignment for Industrial Edge Intelligence
复制标题
基于编码的工业边缘智能大规模任务分配
DOI:
10.1109/tnse.2019.2942042
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发表时间:
2019-09
影响因子:
6.6
通讯作者:
Wang Xiaokang
中科院分区:
文献类型:
--
作者:
Ren Lei;Laili Yuanjun;Li Xiang;Wang Xiaokang
Industrial edge computing, combing various smart devices such as smart sensors, manufacturing equipment, and Internet of Things, has an ultimate goal to provide the industrial edge intelligence. Assigning large-scale tasks with multi-devices connection property for distributed edge servers is one of the main challenges to realize this goal. To address this question, a generative-coding group evolution algorithm, which involves a coding-based operator to approximate different sorts of evolutionary operators, is proposed in this paper. A simple grouping strategy is also introduced to accelerate the optimization process. Experimental results on three cases show that this algorithm is able to provide near-optimal solutions for large-scale tasks within a very short time compared with some traditional approaches.
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影响因子:
6.6
作者:
Kun Wang;Yun Shao;Lei Xie;Jie Wu;Song Guo
通讯作者:
Song Guo
DOI:
10.1109/icc.2018.8422274
发表时间:
2018-05
期刊:
2018 IEEE International Conference on Communications (ICC)
影响因子:
--
作者:
N. Ti;L. Le
通讯作者:
N. Ti;L. Le
DOI:
10.1007/978-3-030-05057-3_25
发表时间:
2018-11
期刊:
--
影响因子:
--
作者:
Lei He;Hongli Xu;Haibo Wang;Liusheng Huang;Jingyi Ma
通讯作者:
Lei He;Hongli Xu;Haibo Wang;Liusheng Huang;Jingyi Ma
影响因子:
9.3
作者:
Wang, Xiaokang;Yang, Laurence T.;Deen, M. Jamal
通讯作者:
Deen, M. Jamal
DOI:
10.1109/ucc.2014.19
发表时间:
2014-12
期刊:
2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing
影响因子:
--
作者:
Qiufen Xia;W. Liang;Zichuan Xu;B. Zhou
通讯作者:
Qiufen Xia;W. Liang;Zichuan Xu;B. Zhou