1. Speaker: Jin-Wei Lin Advisor: Dr. Ho-Ting Wu
Fog computing: A cloud to the ground support for smart things and machine-to-machine networks
Speaker: Jin-Wei Lin
Advisor: Dr. Ho-Ting Wu

2. Outline INTRODUCTION SCENARIOS LITERATURE REVIEW ON FOG COMPUTING
CLOUDLETS
NEW CHALLENGES IN IOT REQUIRES NEW ARCHITECTURE
FOG USE CASE STUDIES

3. INTRODUCTION
Fog devices are positioned between cloud and smart devices
smart grid , connected vehicles , wireless sensor , actuator networks

4. Both cloud and fog provide
data, compute, storage, and application
services to end-users
Fog provides
low latency, location awareness, and
improves QoS for streaming and real-time applications and supports heterogeneity
cyber-physical systems

5. SCENARIOS Fog computing in smart grid energy load balancing
collectors at the edge process the data
filter the data
intelligence analytics

6. smarter traffic lights and connected vehicles
Intelligent lighting turns on once a
sensor identifies movement and
switches off as traffic passes.
Neighboring smart lights (fog devices)
coordinate to create green traffic wave.

7. LITERATURE REVIEW ON FOG COMPUTING
Mobile Fog
Fog computing approach reduces latency and network traffic
placement and migration method for cloud and fog
latency restrictions and reduces the network utilization
Virtual Machines
An opportunistic spatio-temporal event processing system that uses prediction-based continuous query
predicts future query regions for moving consumers
Just-in-time
parallel
不保證information 、 最佳路由

8. Existing methods for web optimization
unique knowledge that is only available at the edge (fog) nodes
network status , device’s computing load
mobile cloud concept
heterogeneous resources (CPUs, bandwidth, content)
framework for heterogeneous resource
mapped to “time” resources

9. CLOUDLETS
intermediate layers located between the cloud and each mobile device
“data centers in a box” aimed to bring the cloud closer
instantiate custom VM

14. NEW CHALLENGES IN IOT REQUIRES NEW ARCHITECTURE
Stringent Latency Requirements
Network Bandwidth Constraints
Resource-Constrained Devices
Cyber-Physical Systems
Uninterrupted Services With Intermittent Connectivity to the Cloud

15. New Security Challenges
Keeping Security Credentials and Software up to Date on Large Number of Devices
Protecting Resource-Constrained Devices
Assessing the Security Status of Large Distributed Systems in Trustworthy Manner
Responding to Security Compromises Without Causing Intolerable Disruptions

16. FOG - three dimensions Carry out a substantial amount of data storage
Carry out a substantial amount of computing and control functions
Carry out a substantial amount of communication and networking

17. Fog and cloud complement each other
Fog Enables a Service Continuum
Fog and Cloud Are Interdependent
Fog and Cloud Are Mutually Beneficial

19. FOG USE CASE STUDIES
data plane
control plane

20. data plane of Fog
pooling of clients idle computing/storage/ bandwidth resources and local content
content caching at the edge and bandwidth management at home
client-driven distributed beam-forming
client-to-client direct communications (e.g., FlashLinQ, LTE direct, WiFi direct, and Air Drop)
cloudlets and micro data-centers

21. Control Plane of Fog over the top (OTT) content management
fog-RAN: Fog driven RAN
client-based HetNets control
client-controlled cloud storage
session management and signaling load at the edge
crowd-sensing inference of network states
edge analytics and real-time stream-mining

22. FOG USE CASE STUDIES
Crowd-Sensing LTE States (in Commercial Deployment)
OTT Network Provisioning and Smart Data Pricing (in Commercial Deployment)
Client-Based HetNets Control (in 3GPP Standards)
“Shred and Spread” Client-Controlled Cloud Storage (in Beta Trial)
Real-Time Stream Mining for Embedded AI (in Beta Trial)
Borrowing Bandwidth From Neighbors in D4D (in Beta Trial)
Bandwidth Management at Home Gateway (in Beta Trial)
Distributed Beam-Forming (in Laboratory Demonstration)

25. REFERENCES
 I. Stojmenovic, "Fog computing: A cloud to the ground support for smart things and machine-to-machine networks", 2014 Australasian Telecommunication Networks and Applications Conference (ATNAC), pp , 2014.
M. Chiang, T. Zhang, "Fog and IoT: An Overview of Research Opportunities", IEEE Internet of Things J., vol. 3, no. 6, pp ,