Mobile Data Offloading: How Much Can WiFi Deliver?

By Kyunghan Lee, Joohyung Lee, Yung Yi, Injong Rhee, Song Chong. IEEE/ACM Transactions on Networking, 2013

917 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0e9108e4bf2e57b959ce4bca45b455389810d48f

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

1. Athanasios V. Vasilakos
2. Yong Li

In Electrical and Electronic Engineering

1. L. Su
2. Athanasios V. Vasilakos
3. Yong Niu
4. Yong Li
5. Depeng Jin

Citations in the corpus

• FetchSGD: Communication-Efficient Federated Learning with Sketching (2020, neutral): “First, communication-efficiency is a necessity when training on the edge (Li et al., 2018), since clients typically connect to the central aggregator over slow connections ( 1 Mbps) (Lee et al., 2010).”
• A survey of millimeter wave communications (mmWave) for 5G: opportunities and challenges (2015, background): “…kinds of networks become the key to explore the potential of heterogeneous networking to solve the problems of mobility management, vertical handover, mobile data offloading from macrocells to micro-cells [140], inter-cell interference management, etc. Qiao et al. [141] introduced an mmWave ?”
• Data Offloading Techniques in Cellular Networks: A Survey (2015, neutral): “It is measured as the ratio of the total traffic offloaded (transferred through alternative channels) to the total traffic generated [12], or as the ratio of the total load of traffic that flows on the cellular channel after the offloading process to the traffic on the infrastructure in the absence of any…”