Resource-aware Data Management
Resource-Aware Data Management is a data management paradigm that optimizes the collection, processing, storage, and transmission of IoT-generated data by explicitly accounting for the constraints and availability of computational, communication, and energy resources in heterogeneous and dynamic environments.
21
Publications
866
Citations
83
Authors
53
Institutions
Publications per year
2017–2026
9
Parents
21
1–5 of 21
83
2
h-index
1
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1
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1
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1–5 of 83
53
IBM (United States)
Armonk, United States
2 h-index
6 publications
98 citations
Queen's University
Kingston, Canada
2 h-index
2 publications
112 citations
Universitat Politècnica de Catalunya
Barcelona, Spain
1 h-index
1 publications
26 citations
Russian Academy of Sciences
Moscow, Russia
1 h-index
2 publications
38 citations

Barcelona Supercomputing Center
Barcelona, Spain
1 h-index
1 publications
26 citations

Brunswick (United States)
Lake Forest, United States
1 h-index
2 publications
166 citations

King Saud University
Riyadh, Saudi Arabia
1 h-index
1 publications
95 citations
Cogent (United Kingdom)
Newport, United Kingdom
1 h-index
1 publications
162 citations
1–8 of 53
JNCA · 1 publications · 31 citations
1
h-index
1 publications · 162 citations
1
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1 publications · 33 citations
1
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1 publications · 21 citations
1
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ITETBT · 1 publications · 95 citations
1
h-index
1–5