The Three Software Stacks Required for IoT. Benjamin Cabé Eclipse

Transcription

1 The Three Software Stacks Required for IoT Benjamin Cabé Eclipse

2 IoT? Applications Collect, exchange & analyze data

3 IoT? Applications Collect, exchange & analyze data Sensing / Actuating Interact with the physical world

4 IoT? Applications Collect, exchange & analyze data Networking & Data Communications Bridge the physical world to the Internet Sensing / Actuating Interact with the physical world

5 Typical IoT Architecture telemetry telemetry commands commands Gateways Devices (sensors & actuators) IoT Cloud Platform Applications

6 Role & Characteristics DEVICE GATEWAY / SMART OBJECT CLOUD PLATFORM constrained connectivity scale out low-power messaging integration specialized edge computing data analytics

7 Asset Tracking

8 The solution

9 The 3 IoT Software Stacks SECURITY ONTOLOGIES Hardware Abstraction Layer (HAL) OS / RTOS CONSTRAINED DEVICES Event Management, Analytics & UI IoT protocols Network Management Application Runtime OS / RTOS GATEWAYS AND SMART DEVICES Message Routing Connectivity Connectivity Application Enablement Remote Management IoT protocols Remote Management Field protocols Data Management & Messaging Field protocols Communication TOOLS & SDKs Data Management Device Management Device Registry OS / PaaS IOT CLOUD PLATFORM

10 Characteristics of Open IoT Stacks loosely coupled modular platform-independant based on open standards API

11 Eclipse IoT

12 Eclipse IoT Community million lines of code projects K developers monthly visitors

13 Eclipse IoT from building blocks to stacks

14 The 3 IoT Software Stacks SECURITY ONTOLOGIES Hardware Abstraction Layer (HAL) OS / RTOS CONSTRAINED DEVICES Event Management, Analytics & UI IoT protocols Network Management Application Runtime OS / RTOS GATEWAYS AND SMART DEVICES Message Routing Connectivity Connectivity Application Enablement Remote Management IoT protocols Remote Management Field protocols Data Management & Messaging Field protocols Communication TOOLS & SDKs Data Management Device Management Device Registry OS / PaaS IOT CLOUD PLATFORM

15 OS Stack for IoT Devices C implementation of OMA LWM2M Portable on any POSIX-compliant system Field protocols IoT protocols Hardware Abstraction Layer (HAL) Remote Management Communication C implementation of MQTT < 2,000 lines of C ANSI code OS / RTOS JAVA API for MCUs CONSTRAINED DEVICES Android for IoT

16 OS Stack for IoT Gateways Data Management & Messaging Field protocols IoT protocols Network Management Application Runtime Remote Management Connectivity Native support for MQTT Serial, RS-485, BLE, MODBUS, OPC-UA, CAN Bus, Milo NAT, firewall, modem configuration, Remote Management over MQTT OS / RTOS OSGi implementation GATEWAYS AND SMART DEVICES

17 OS Stack for Home Automation Data Management & Messaging Field protocols IoT protocols Network Management Application Runtime Remote Management Connectivity Rule engine to orchestrate things Home automation protocols such as Belkin WeMo, LIFX, Philips Hue, Remote firmware update through the GW Web UI and API for remote control OS / RTOS OSGi implementation GATEWAYS AND SMART DEVICES

18 OS Stack for IoT Cloud

19 OS Stack for IoT Cloud OMA LWM2M implementation in Java built on top of Eclipse Californium (CoAP) Device Management Device Registry Manage software upgrade campaigns independently of the actual DM protocol IOT CLOUD PLATFORM

20 Eclipse hawkbit

21 OS Stack for IoT Cloud Platform An Integration Platform for IoT Services Message Routing Connectivity Application Enablement REST API / Digital Twin Event Management, Analytics & UI Abstract the actual communication protocols via protocol adapters Data Management Device Management Device Registry NoSQL data store OS / PaaS Deploy on: IOT CLOUD PLATFORM

22 Eclipse hono

23 Eclipse IoT Adoption

24 Eclipse IoT Programs Virtual IoT Open IoT Challenge IoT Marketplace Testbeds

25 One more thing

26 Eclipse Enterprise for Java (EE4J) Moving Java EE to Eclipse Foundation Technology Sponsorship

27 Eclipse Enterprise for Java (EE4J) Project Overview

28 Eclipse Deeplearning4j Java-based Machine Learning Framework Toolkit for building, training and deploying Neural Networks Distributed training GPU or Hadoop/Spark Use cases: network intrusion detection, predictive maintenance, recommender systems in e-commerce, image recognition,

29 Join us! * K million lines of code projects developers monthly visitors * and counting!

30 Join us! Check out the projects Contribute ideas, bug fixes, use cases Participate on the mailing lists Virtual IoT Meetup Propose your project!

31 IoT Developer Survey

32 Thank