IEEE Internet of Things Journal· 2016Q1· Review
Edge Computing: Vision and Challenges
- 8,026citations
- Q1SCImago
- 2016year
Short summary
Edge computing processes data near its source, addressing demands for faster response times, battery life, bandwidth savings, and data privacy.
AI-generated from the title and abstract; the full text is not read.
Key points
- Edge computing moves data processing closer to the data source.
- It aims to improve response times and save bandwidth.
- Key applications include smart homes, cities, and cloud offloading.
- The paper identifies challenges and opportunities in the field.
AI-generated from the title and abstract; the full text is not read.
Abstract
The proliferation of Internet of Things (IoT) and the success of rich cloud services have pushed the horizon of a new computing paradigm, edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this paper, we introduce the definition of edge computing, followed by several case studies, ranging from cloud offloading to smart home and city, as well as collaborative edge to materialize the concept of edge computing. Finally, we present several challenges and opportunities in the field of edge computing, and hope this paper will gain attention from the community and inspire more research in this direction.
The authors' abstract, as published at the source. IEEE Internet of Things Journal, 2016 · DOI ↗
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Field: Computer Networks and Communications
Computer Networks and CommunicationsComputer Science