Abstract
In the IoT era, a massive number of smart sensors produce a variety of data at unprecedented scale. Edge storage has limited capacities posing a crucial challenge for maintaining only the most relevant IoT data for edge analytics. Currently, this problem is addressed mostly considering traditional cloud-based database perspectives, including storage optimization and resource elasticity, while separately investigating data analytics approaches and system operations. For better support of future edge analytics, in this work, we propose a novel, holistic approach for architecturing elastic edge storage services, featuring three aspects, namely, (i) data/system characterization (e.g., metrics, key properties), (ii) system operations (e.g., filtering, sampling), and (iii) data processing utilities (e.g., recovery, prediction). In this regard, we present seven engineering principles for the architecture design of edge data services.
Original language | English |
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Title of host publication | Software Architecture - 13th European Conference, ECSA 2019, Proceedings |
Editors | Tomas Bures, Laurence Duchien, Paola Inverardi |
Pages | 97-105 |
Number of pages | 9 |
DOIs | |
Publication status | Published - 1 Jan 2019 |
MoE publication type | A4 Article in a conference publication |
Event | European Conference on Software Architecture - Paris, France Duration: 9 Sep 2019 → 13 Sep 2019 Conference number: 13 https://ecsa2019.univ-lille.fr/home |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 11681 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | European Conference on Software Architecture |
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Abbreviated title | ECSA |
Country | France |
City | Paris |
Period | 09/09/2019 → 13/09/2019 |
Internet address |
Keywords
- Adaptation
- Architectural design
- Edge computing
- Edge data service
- Engineering
- IoT
- Service computing