Abstract
The emerging edge computing paradigm is enabling a series of real-time, location-aware applications. The data produced by applications like autonomous driving, collaborative machine learning, and real-time video processing is often only usable in a limited time- A nd space-window. Data placement, sharing, and computation need to happen with low latency and location awareness, using a heterogeneous infrastructure that is not on par with datacenter hardware. In this work we plan to design and implement Griffin, a distributed edge storage service that is aware of mobility, latency and consistency requirements of applications, and that can support storage function programmability for low-latency responses.
| Original language | English |
|---|---|
| Title of host publication | Middleware '20 Doctoral Symposium |
| Subtitle of host publication | Proceedings of the 21st International Middleware Conference Doctoral Symposium |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 19-21 |
| Number of pages | 3 |
| ISBN (Electronic) | 9781450382007 |
| DOIs | |
| Publication status | Published - 7 Dec 2020 |
| Event | 21st International Middleware Conference Doctoral Symposium, Middleware 2020 - Part of Middleware 2020 - Virtual, Online, Netherlands Duration: 7 Dec 2020 → 11 Dec 2020 |
Conference
| Conference | 21st International Middleware Conference Doctoral Symposium, Middleware 2020 - Part of Middleware 2020 |
|---|---|
| Country/Territory | Netherlands |
| City | Virtual, Online |
| Period | 7/12/20 → 11/12/20 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- distributes systems
- edge computing
- storage
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