Edge Computing for the Internet of Things: A Case Study

By Gopika Premsankar, Mario Di Francesco, Tarik Taleb. IEEE Internet of Things Journal, 2018

563 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/6e4b075be3efeb6794c406f1302eee0a2bb8aa26

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Computer Vision and Pattern Recognition

Citations in the corpus

Edge-Assisted Hierarchical Federated Learning with Non-IID Data (2019, background): “According to [13], Lcloud ∼ (20, 100)ms, and Ledge ∼ (1, 10)ms are realistic values in real life.”
An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges (2018, background): “Recently, edge or fog computing is advocated, where IoT devices and gateways carry out computation and analysis in order to reduce latency for critical applications, reduce cost and promote QoS [35], [36].”
A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art (2019, unknown): “[154] Advocating edge computing for emerging IoT applications that leverage sensor streams to augment interactive applications.”
Toward Edge Intelligence: Multiaccess Edge Computing for 5G and Internet of Things (2020, background): “…[7], [84]; 2) it can prolong the battery life of the resource-constrained end devices because it avoids complex local processing at the end devices [85]; and 3) it enables different types of applications (e.g., mobile VR/AR, mobile gaming, mobile healthcare, etc.) to successfully run at the end…”
A Survey on IoT Security: Application Areas, Security Threats, and Solution Architectures (2019, background): “In fog computing there is some movement of data from a device to fog layer and adversaries can take advantage of this movement [188].”
Edge-Computing-Enabled Smart Cities: A Comprehensive Survey (2019, unknown): “In the smart city era, information and communication technologies are incorporated to enable smarter urban infrastructure management for improving overall user QoE.”
Client-Edge-Cloud Hierarchical Federated Learning (2019, background): “erent distributions. Let L cloud denote the latency of one round of edge-cloud communciation, L edgefor one round of client-edge communication, and L cfor one local update on the device. According to [13], L cloud˘(20;100)ms, and L edge˘(1;10)msare realistic values in real life. We thus set L cloud=”