Edge Analytics in the Internet of Things

By Mahadev Satyanarayanan, Pieter Simoens, Yu Xiao, Padmanabhan Pillai, Zhuo Chen, Kiryong Ha, Wenlu Hu, Brandon Amos. IEEE pervasive computing, 2015

418 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/fa9a9c392adb56ba1143ade5174f94f702ef12d5

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Citations in the corpus

Edge Computing for the Internet of Things: A Case Study (2018, background): “Since the introduction of cloudlets, further research has proposed integrating cloudlets with femtocells, LTE base stations or even cars [13].”
Computation Offloading Toward Edge Computing (2019, background): “, recognized objects) are sent to the cloud [42].”
A Survey on Network Methodologies for Real-Time Analytics of Massive IoT Data and Open Research Issues (2017, methodology): “By employing the edge analytics network paradigm, the things that generate the data may be able to process the data themselves “locally” instead of transmitting the data to the data center [145].”
How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions (2017, methodology): “GigaSight [80] is a framework that is proposed to exploit Cloudlets at the edge of the network in order to prevent the congestion that may occur within MAN due to high-load traffic destined to the cloud.”
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications (2017, background): “Although it is a concept similar to MEC in some aspects, it distinguishes itself as more suitable for the context of IoT [22].”
Osmotic Computing: A New Paradigm for Edge/Cloud Integration (2016, methodology): “with the Fog Computing efforts involving Cloudlets (from Cisco), which involve ”small Clouds” which are geographically scattered across a network and act as ”small datacenters” at the Edge of the network [21].”
Orbital Edge Computing: Nanosatellite Constellations as a New Class of Computer System (2020, background): “cameras, lidar) proliferate, streaming all data to central cloud systems for processing becomes infeasible [78, 79, 97].”
A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms (2019, background): “In addition to provide timely service, this hierarchy enforces the privacy of its owners by denaturing the private data before releasing them to the cloud [131].”
Edge-computing-driven Internet of Things: A Survey (2022, background): “With the development of virtual reality (VR) and augmented reality (AR), humans can interact more naturally with the virtual world through the data that are collected by IoT devices [156].”
Online Resource Allocation for Arbitrary User Mobility in Distributed Edge Clouds (2017, background): “Pushing the cloud frontier to the Internet edge has attracted tremendous interest not only from cloud operators of the IT service/software industry but also from cellular carriers of the telecom industry [1].”
Toward Edge Intelligence: Multiaccess Edge Computing for 5G and Internet of Things (2020, background): “An example can be found in [133], where an architecture named GigaSight is introduced, which executes a video analytics service on an MEC platform, which is expected to be valuable for safety in an automotive environment. d) AR/VR/MR: The combination of AR and VR is referred to as MR. AR/VR/MR is a…”
Challenges and Opportunities in Edge Computing (2016, background): “Hence, there has been a need for looking ‘beyond the clouds’ towards the edge of the network as shown in Figure 1, referred to as edge computing [3], [4], but also known as fog computing [5], [6] or cloudlet computing [7], [8].”
On Multi-Access Edge Computing: A Survey of the Emerging 5G Network Edge Cloud Architecture and Orchestration (2017, neutral): “Video processing at the MEC platform can also assist in removing certain video content from data uploaded directly by users based on regulation policies [65].”