Problem Statement of Edge Computing beyond Access Network for Industrial IoT

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Lesley Barton
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1 Problem Statement of Edge Computing beyond Access Network for Industrial IoT draft-geng-iiot-edge-computing-problem-statement-00 Liang Geng, China Mobile Mingui Zhang, Mike McBride (Presenter), Bing Liu, Huawei Technologies

2 Background Focus on use cases and problem statement, related work in other SDOs and gap analysis. Create research discussion and standardization work for: Protocol for east-west comm between multiple BEC gateways Common API across various BEC platform. User mobility: Edge to Edge Edge device config/mgmt (both device-level and virtual-resource-level) Light-weight virtualization technologies (container/unikernel) Local edge security draft-geng-iiot-edge-computing-problem-statement-00 Netslices at OPSWG, IETF 100 2

What is Beyond Edge Computing (BEC) Cloudification Resource Pooling Clustered Computing Common Hardware Centralized Deployment Edgification Real-time and low latency Dedicated computing Diversity of

3 What is Beyond Edge Computing (BEC) Cloudification Resource Pooling Clustered Computing Common Hardware Centralized Deployment Edgification Real-time and low latency Dedicated computing Diversity of hardware Decentralized deployment Orch. Ctroller BRAS-CP 5G-CP IMS EPC Core DC Backbone BRAS-CP 5G-CP CDN Regional DC Metro 5G-UP CDN MEC APP AP Access Network Beyond Edge Computing Data Encryp. Data Collect. Pre-process Vertical APP Real-time Ctrl Access Ctrl Local Network Inference Traffic Offload Manufacturing Residential Health Care Mining Public Sector Logistics Retail Energy BEC takes care of the first hop where the service of a particular industrial vertical connects to the network T2TRG, IETF 100 3

4 Capabilities of BEC(1/2) Heterogeneous IoT device compatibility Various IoT interface including Zigbee, WIFI, tens of Field Buses and etc. Low and deterministic service latency Various mission-critical services (Motion control etc.) Data pre-processing and traffic offloading Reduce WAN bandwidth and increase the effectiveness of data System resource isolation Support multi-tenancy situation which is a norm for IoT ecosystem Offline processing Robustness even in unlikely circumstances T2TRG, IETF 100 4

5 Capabilities of BEC(2/2) End-to-end security Security provided right from customer premises Distributed artificial intelligence Making use of GPU/TPUs for AI applications (Graphic/Inferences) Real-time operation Real-time operating system(i.e. Industrial Linux) for spontaneous events Unified API for multi-ecosystem edge application API to expose Software/Hardware capabilities for application ecosystem Service isolation for network slicing Mapping services to specific network slice for E2E service guarantee T2TRG, IETF 100 5

6 Architecture BEC Management Platform Application management (Lifecycle, verification, publishing, Devops etc.) Device-level management + System resource management SDN platform control and optimization for BEC network Interfaces Management interface Lightweight interface for device configuration/monitoring and virtual resource management Data interface Unified but flexible for interoperation in data plane (i.e. MQTT, OPC-UA and others) Distributed BEC platform Lightweight virtualization technology for resource isolation and fast application deployment Heterogeneous but modularized southbound interface Comprehensive and unified API for capability exposure T2TRG, IETF 100 6

Cloud Collaboration Industry-grade design 17+ industrial interfaces Voice, Wireless, VPN in one box Data aggregation:

7 Example of E2E BEC system RS232 RS485 Predix Machine App1 App n CAN FXS... Linux container Edge computing Predix Cloud BEC Gateway Flexible industrial access Pre-analysis of local data Edge and Cloud Collaboration Industry-grade design 17+ industrial interfaces Voice, Wireless, VPN in one box Data aggregation: industrial data analysis Data filtering: saving WAN traffic Data security: encryption Predix and apps at edge Edge: real-time and reliability Could: unified policies and Big Data

Machine Tools Tool Engineering Machinery

8 Use case -Connected Elevator Testbed Market Segment Buildings & Facilities : Elevators This testbed may also be applicable to other verticals such as Machine Tools Engineering Machines Industrial Washers Elevators Machine Machine Tools Tool Engineering Machinery Industrial Washers Location The OpenLab in Nanjing, China OpenLab 8

9 Gap Analysis in IETF Multiple Virtualization Technologies Coexistence/Coordination Interface/Model required for selection between various virtualization technologies for specific vertical use cases/requirements Light weight Device-level management and virtual resource Massive number of isolated resource pool need much lighter interface for management Netconf+YANG for VIM? Framework and APIs for multi-ecosystems Unified and modularized APIs across multiple compiling environment for maximum flexibility and friendly ecosystem Runtime Updates Energy efficient software/firmware update without service break-down

10 Conclusion BEC methodology Distributes as much as you can, centralized only if you must (i.e. massive computing/storage). Research interest very popular topic across the industry (IIC, ECC, EdgeXFoundry, OpenFog, OPENIL, RIOT and etc.) IETF and IRTF Architecture and framework for RG, interface/api deliverables might be for WG (see SUIT BoF) Further Bar BoF Thursday 20:00-21:30 Hullet T2TRG, IETF

draft-netslices-usecases-02 draft-geng-coms-problem-statement-01 draft-defoy-coms-subnet-interconnection-01

draft-netslices-usecases-02 draft-geng-coms-problem-statement-01 draft-defoy-coms-subnet-interconnection-01 I. Problem Statement of Supervised Heterogeneous Network Slicing (NS) II. NS Use Cases III. NS Information Model IV. NS Interconnection V. NS Next Steps towards IETF101 draft-geng-coms-problem-statement-01