The document discusses fog networking, which uses edge devices and clients to perform computing tasks rather than routing all information through data centers. It defines fog networking as using end-user devices for storage, communication, and management. Edge devices are becoming more powerful but still have limitations. The document argues fog networking can enable real-time processing at the local level along with pooling local resources. It presents client resource pooling as a case study and identifies research challenges in areas like trustworthiness, incentives for client participation, and managing interactions between fog and cloud systems.

1. FOG
NETWORKING
Name

2. Content
 Overview: From Cloud to Fog
 What is Fog?
 Client / Edge / IoT Devices
 Why Fog?
 Case: Client Resource Pooling
 Fog as a Network Architecture
 Cloud – Fog Interface & Hybrid Cloud
 Research Challenges

3. From Cloud to Fog
2000 – 2015 2015 – 2030 ?

4. What is “Fog Network”?
 A network architecture that uses one or a
collaborative multitude of end-user clients or
near-user edge devices to carry out a substantial
amount of storage (rather than stored primarily in
cloud data centers), communication (rather than
routed over backbone networks), and control,
configuration, measurement and management
(rather than controlled primarily by network
gateways such as those in LTE core).

5. Many Types of Clients & Edge
Devices

6. Contrast Them With…

7. Client/Edge/IoT Devices
 Are recently becoming
 Powerful (in sensing, storage, computing, control, comm.)
 Still limited (in battery, storage, computing, information)
 Maybe mobile
 Crowds of clients/edge devices are
 Dense
 Distributed
 Under-organized

8. It has become both feasible and
interesting to ask:
“Can ‘this’ be done at
clients/edge?”

9. Rather Than:
1. LTE Core (P-GW, S-GW, PCRF…)
2. Data Center
3. Wide area backbone

10. Traditional View
use

11. Fog View
are
(part of)

12. Why Fog?
 Brick vs. Click: Physical interaction &
real estate
 Rapid innovation and affordable scaling
 Real-time processing: right here and now
 Client-centric objectives/ privacy
 Pooling of local content/ BW/ storage/
processor
 Operate on encrypted and multipath
traffic

13. Case: Client Resource Pooling
Idle resources on the edge pooled but shared
unpredictably

14. Fog as a Network Architecture
EDD
Edge-Driven
Data-center
EDC
Edge-Driven
Control-plane
5G IoT Big Data

15. Cloud – Fog Interface &
Hybrid Cloud
Click
Massive storage
Heavy duty computation
Global coordination
Wide-area connectivity
Brick
Real time processing
Rapid innovation
Client-centric
Edge resource pooling

16. Research Challenges
 Trustworthiness / verification of client/edge software &
hardware
 Incentivization of client participation
 Interactions w. client/IoT OS and definition of network
service APIs
 Interfaces: Cloud-to-cloud and cloud-to-fog
 Oscillation/divergence and global configuration
consistency during the interactions of local actions
 Tradeoff of Local vs. Global architecture, Distributed vs.
Centralized

17. THANK YOU