Privacy-aware Task Scheduling
Privacy-Aware Task Scheduling is a computational scheduling framework that, as a member of the task scheduling paradigms in edge computing, specifically incorporates privacy preservation as a core optimization criterion by dynamically allocating tasks to edge nodes while minimizing privacy exposure through data localization, access control, and anonymization mechanisms.
37
Publications
1.4K
Citations
145
Authors
82
Institutions
Publications per year
2017–2026
28
Parents
37
Privacy-Aware Offloading in Mobile-Edge Computing
Xiaofan He, Juan Liu, Richeng Jin et al. · 2017 · 109 citations
1–5 of 37
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Nanjing University of Information Science and Technology, China
2 publications · 134 citations
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82

Huazhong University of Science and Technology
Wuhan, China
3 h-index
10 publications
345 citations
Wuhan University
Wuhan, China
3 h-index
4 publications
173 citations
North Carolina State University
Raleigh, United States
2 h-index
4 publications
362 citations
University of California, Irvine
Irvine, United States
2 h-index
3 publications
77 citations

Xidian University
Xi'an, China
2 h-index
5 publications
178 citations

Shanghai Jiao Tong University
Shanghai, China
2 h-index
3 publications
67 citations
The University of Texas at Dallas
Richardson, United States
2 h-index
4 publications
106 citations

Nanjing University of Information Science and Technology
Nanjing, China
2 h-index
4 publications
226 citations
1–8 of 82
FGCS · 5 publications · 250 citations
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3 publications · 77 citations
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2 publications · 56 citations
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1 publications · 13 citations
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1 publications · 22 citations
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