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

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

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

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

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

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.

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

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

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

https://www.akamai.com/cn/zh/products/web-performance/cloudlets/

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

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

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

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

FOG USE CASE STUDIES data plane control plane

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

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

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)

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. 117-122, 2014. M. Chiang, T. Zhang, "Fog and IoT: An Overview of Research Opportunities", IEEE Internet of Things J., vol. 3, no. 6, pp. 854-64, 2016.