Comparison of edge computing implementations: Fog computing, cloudlet and mobile edge computing
Abstract
When it comes to storage and computation of large scales of data, Cloud Computing has acted as the de-facto solution over the past decade. However, with the massive growth in intelligent and mobile devices coupled with technologies like Internet of Things (IoT), V2X Communications, Augmented Reality (AR), the focus has shifted towards gaining real-time responses along with support for context-awareness and mobility. Due to the delays induced on the Wide Area Network (WAN) and location agnostic provisioning of resources on the cloud, there is a need to bring the features of the cloud closer to the consumer devices. This led to the birth of the Edge Computing paradigm which aims to provide context aware storage and distributed Computing at the edge of the networks. In this paper, we discuss the three different implementations of Edge Computing namely Fog Computing, Cloudlet and Mobile Edge Computing in detail and compare their features. We define a set of parameters based on which one of these implementations can be chosen optimally given a particular use-case or application and present a decision tree for the selection of the optimal implementation.
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- Authors
- Dolui, K., & Datta, S. K.
- Affiliations
- Fondazione Bruno Kessler (IT)
- EURECOM (FR)
- Venue
- 2017 Global Internet of Things Summit (GIoTS)
- Publisher
- IEEE
- Published
- 2017-06
- Pages
- 1-6
- OpenAlex
- W2626074815
- Cited by
- 492
- References
- 25
- Citations by year
- 2026: 11 · 2025: 20 · 2024: 44 · 2023: 50 · 2022: 84 · 2021: 79 · 2020: 74 · 2019: 78 · 2018: 48 · 2017: 4
- FWCI
- 44.46
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Global Internet of Things Summit (GIoTS) (publishedVersion)
- Graduate School and Research Center in Digital Science (EURECOM) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Cloud Computing and Resource Management
- Physical Sciences › Computer Science › Hardware and Architecture › Energy Efficiency in Computing
- Keywords
- edge computing, fog computing, cloudlets, mobile edge computing, Internet of Things, real-time response, context awareness, decision tree, implementation selection, network latency, distributed computing
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