Fog Computing: Challenges and Solutions

Transcription

1 Fog Computing: Challenges and Solutions Maria

2 My Background (1/2) Participating in GHC since 2012 Baltimore 12 Phoenix 14 Houston 15, 16 Helping organize GHC since 2015 Co-chair, Internet of Things and Wearable Tech Track 2 panels, 2 hands-on workshops, 12 presentations PAGE 2 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

3 My Background (2/2) Associate Research Scholar PhD: Columbia University Industry experience PAGE 3 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

4 Fog: Descended Cloud o ? An architecture that uses one or a collaborative multitude of end-user clients or near-user edge devices to carry out a substantial amount of computation, storage, communication, and control PAGE 4 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

5 Cloud Computing: Computing in Datacenters Cloud AWS: 44 locations, Azure: 30 locations For emerging applications: latency, bandwidth limitations PAGE 5 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

6 Fog: Computing Closer to the Users Fog Distribute computation, storage, communication and control services immersively closer to end-users along the Cloud-to- Things (C2T) continuum Data processing, business logic, decision-making at multiple points in the hierarchy Smart city fog deployment: computing in buildings, neighborhoods, regions PAGE 6 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

7 Enabling Futuristic Applications Helps computing-heavy emerging applications Local computing Local content processing Local storage Autonomous cars Drones Augmented and virtual reality PAGE 7 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

8 Actively Developing Field Descending intelligence from the cloud Amazon 16 Adding intelligence to local nodes Microsoft 17 Dell 17 Ensuring interoperability AT&T 17 PAGE 8 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

9 OpenFog Consortium: Accelerating Fog Goals: Technology Industry-wide collaboration Education Est. February members headquartered in 16 countries PAGE 9 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

10 OpenFog Consortium A growing, global ecosystem Founders Affiliations Contributing Members Reference architecture, whitepaper on autonomous driving Co-chair, Communications Working Group PAGE 10 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

11 Security Scalability Openness Autonomy OpenFog Reference Architecture: Storage Core Pillars Network Compute Control Accelerators Reliability, availability, and serviceability Agility Hierarchy Programmability Requirements to every part of the supply chain Available at: PAGE 11 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

12 Differentiating Principle: Hierarchy Hyper-local Local Regional Global Heterogeneity Decision-making at all levels of the hierarchy PAGE 12 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

13 Senior collaborators: Hazer Inaltekin, Liang Zheng, Mung Chiang (lab lead) Student collaborators: Surin Ahn, Litian Liu, Edward Chang, Chege Gitau Allocating functionality in fog: who does what, and how to put it all back together? PAGE 13 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

14 Characterizing Fog (1/2) Local execution AWS EC2, λ Server-, consumer- grade OR VA Tokyo, JP On, off campus Stressing different elements Compute, networking, storage Measure: communications, computing 100+ hours of measurements PAGE 14 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

15 F(x) Characterizing Fog (2/2) Understand properties of execution points and options Informs task placement algorithms and approaches Statistical characterizations Response time CDFs Exper., G.E.V., 1 Exper., 2 G.E.V., Time (s) Other observations: e.g., different behavior on and off campus Code, data will be publicly available 1 PAGE 15 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

16 Restructuring Computing for Fog Hyper-local Local Regional Global Different levels of hierarchy working together Responsive applications: multi-level operation Data processing: decomposed analytics Non-traditional control, optimization, machine learning techniques User Local device node In-the-loop response Out-of-the loop update PAGE 16 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017 Cloud

17 Testing Fog-Specific Decompositions Sensors Gateways $ Cloud $ $ Video: princetonedge Linear regression decomposition: 70% reduction in data transmission Demos: NYC Media Lab Summit 17, IEEE FWC 17, ACM SenSys 17 channel PAGE 17 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

18 Summary and Future Work Fog computing: enabler of futuristic applications Emerging architecture with unique characteristics Hierarchical Heterogeneous Agile Accelerating fog Requires non-traditional approaches PAGE 18 GRACE HOPPER CELEBRATION FOR WOMEN IN COMPUTING 2017

19 Thank you FEEDBACK? RATE AND REVIEW THE SESSION ON OUR MOBILE APP Download the GHC 17 app at or search GHC 2017 in the app store