Small-scale Radio Networkskoreatest.or.kr/sub08/data/김성륜(연세대).pdf · 2016-10-19 ·...

RAdio resource Management and Optimization Yonsei University 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea Phone : +82-2-2123-7774 E-mail : [email protected] Homepage : http://hertz.yonsei.ac.kr School of EEE, Yonsei University

Small-scale Radio Networks

김성륜 무선자원최적화연구실, 전파연구센터 (RRC)

연세대학교 전기전자공학부

[email protected] http://web.yonsei.ac.kr/slkim

mailto:[email protected]

http://web.yonsei.ac.kr/slkim


1. 무선 데이터 사용 폭증

Robotic and Mobile Networks LaboratoryYONSEI UNIVERSITY

Cellular Data Usage

국내스마트폰사용자의한달평균데이터사용량이사상최초로5GB(기가바이트)를넘었다.

2일미래창조과학부에따르면지난7월말기준4세대이동통신(LTE)스마트폰가입자1명당트래픽이5.11GB(5235MB)로집계됐다.

LTE가입자의한달데이터사용량은2012년12월1.79GB(1836MB)에서2014년8월3GB(3123MB)을돌파했고,지난해10월4GB(4147MB)선도넘어섰다.1GB는1024MB(메가바이트)다.

이처럼트래픽이빠르게증가하는가장큰이유는동영상소비가늘면서다.

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RAdio resource Management and OptimizationYONSEI UNIVERSITY

Cellular Data Usage (미래부, 16년 9월)

• 국내 스마트폰 사용자의 한 달 평균 데이터 사용량이 5GB (기가바이트)를 상회. • 4세대 이동통신(LTE) 스마트폰 가입자 1명당 트래픽이 5.11GB로 집계. • LTE 가입자의 한 달 데이터 사용량은 2012년 12월 1.79GB에서 2014년 8월

3GB을 돌파했고, 지난해 10월 4GB선 상회.

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주로 정지중에 동영상 감상이 원인일 것으로 추정더 늘어날 가능성은?

RAdio resource Management and OptimizationYONSEI UNIVERSITY 5

스마트폰 데이터 사용 실험 (2012/2015)

1. Total traffic volume increase (3.04 times, 47.66 → 145.05 MB/day).

2. Moving (walking/vehicular) user traffic increase (2.64 times,14.74 → 38.93%).

3. Vehicular heavy user traffic increase (2.83 times, 10.35 → 29.29%).

T. Shim, J. Park, S.-W. Ko, S.-L. Kim, B. H. Lee, and J. G. Choi, "Traffic Convexity Aware Cellular Networks: A Vehicular Heavy User Perspective," IEEE Wireless Communications, Vol 23 (1), pp. 88-94, 2016.



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Mobility Impact over Passive Wireless Machines

An experimental example of a movement trace and the corresponding data usage of a typical user in 2012.

The corresponding data usage indicates that the user in stationary and nomadic mobility states consume more data than during the walking state.

User traffic pattern over speed?

Spe

ed

T. Shim, J. Park, S.-W. Ko, S.-L. Kim, B. H. Lee, and J. G. Choi, "Traffic Convexity Aware Cellular Networks: A Vehicular Heavy User Perspective," IEEE Wireless Communications, Vol 23 (1), pp. 88-94, 2016.


Stationary Walking Vagabond0

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40

50

60

70

80

90

100

Tra

ffic

Vo

lum

e (

MB

/da

y)

2015

2012

2.35

User Convexity: 3.04

Nomadic

Traffic Volume over User Speed: User Convexity

Def. User convexity: the traffic volume ratio of nomadic users to walking users

User convexity increase: 1.29 times (2.35 → 3.04)



2. 무선 단말기 숫자 폭증


Moore의 법칙 (1965-2015)

• 대규모 직접회로에서 트랜지스터의 개수는 약 2년 (18개월)마다, 2배씩 증가한다

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무선 단말기의 숫자

Small-scale radio network

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• 단위면적당 무선 단말기의 숫자는 약 5년마다, 10배씩 증가한다?

웨어러블 디바이스의 숫자는 2018년에 1억 3천만개

(Transparency Market Research)


“Transport” Capacity

11

meters/secbit×


Transport Capacity

12

bits/sec log

)(nn

cWn =λ

• Gupta & Kumar, “The Capacity of Wireless Networks ,” IEEE Trans. Information Theory (2000).

• 단위면적당 무선 단말의 숫자가 증가하면, 송수신기간의 거리는 단말기 숫자의 루트에 비례해서 감소한다 (오늘날 IoT의 모습).


3. IoT..to..MTC


IoT의 변천

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“Internet of Things in Industries: A Survey,” IEEE Trans Industrial informatics, Vol 10 (4) 4, 2014.


IoT 약간 구체적인 설명

• Dynamic global network infrastructure with self-configuring capabilities based on standard and interoperable communication protocols where physical and virtual ‘Things’ have identities, physical attributes, and virtual personalities and use intelligent interfaces, and are seamlessly integrated into the information network.

R. van Kranenburg, The Internet of Things: A Critique of Ambient Technology and the All-Seeing Network of RFID. Amsterdam, The Netherlands: Institute of Network Cultures, 2007.

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YONSEI UNIVERSITYRobotic And MObile network Lab.

용어 정의

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▪ M2M (ETSI): 인간의 직접적인 개입이 꼭 필요하지 않은 둘 혹은 그 이상의 객체 간에 일어나는 통신

▪ M2M (IEEE): 가입자 장치(Subscriber station)와 기지국(Base station)을 거쳐 코어-네트워크에 위치하는 서버 간의 정보 교환 혹은 가입자 장치 간 인간의 개입 없이 발생하는 정보 교환

▪ MTC (3GPP): 인간의 개입이 꼭 필요하지 않는 하나 혹은 그 이상의 객체가 관여하는 데이터 통신의 형태

▪ IoT (ITU-T): 모든 사물에까지 네트워크 연결을 제공하는 네트워크의 네트워크▪ IoT (CASAGRAS): 데이터 수집과 통신기능을 통하여 물리적 객체와 가상의 객체를 연결해주는 글로벌 네트워크 기반구조

▪ MOC (ITU-T): 인간의 직접적인 개입이 최소한으로 요구되거나, 혹은 요구되지 않는 둘 혹은 그 이상의 객체 간의 통신

▪ USN-Ubiquitous Sensor Network (ITU-T): 센서가 수집한 정보를 상황인식 기능에 의하여 처리 한 후 때와 장소, 대상을 불문하고 지식 서비스를 제공하는 현존하는 물리적 네트워크 상의 개념적인 네트워크


IoT applications - Libelium Smart World

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Libelium: 50 Sensor Applications for a Smarter World


IoT applications – Busan Smart City

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IoT 한눈에 보기

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User Experience

IoT

ConnectivityClouds


IoT의 범위

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• 전통적인 IT기기 이외에 인터넷에 접속을 하는 모든 “thing” 들이 IoT의 범주에 들어감

• IoT는 공학적, 사업적 측면에서 “혼란”의 상태 – 공통적으로 사용되는 플랫폼 (통신, OS, 서비스)이 없음 – 공학적인 접근 방법 (Layering) 에 대한 표준이 아직은 없음

기회!


통일된 플랫폼의 필요성, 그러나 가능할지?

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PlatformApp

App

App

AppApp

통일된 플랫폼Apps


IoT Landscape 2016 – A Fragmented Ecosystem

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INTERNET OF THINGS TECTONICS

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IoT Alliance and Consortium (1/4)

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▪ Technology Architecture Focused – Core / Communication / Messaging

• IEEE (Link/Comms Focused) – RFID Consortium – NFC Forum – Dash 7 Alliance – Bluetooth SIG – Wifi Alliance – Zigbee Alliance – The ULE Alliance – Wi-SUN Alliance – World Wide Web Consortium (W3C)

– Long Range • LoRa Alliance

– Founding Members: – Actility, Cisco, Eolane, IBM, Kerlink, IMST, MultiTech, Sagemcom, Semtech, Microchip Technology, Bouygues

Telecom, KPN, SingTel, Proximus, Swisscom, and FastNet (part of Telkom South Africa) – Data Rates: Range from 0.3 kbps to 50 kbps. – Distance: 100 km (62 miles) in favorable environments – Battery: Sensors can run for 10 years or more on a single AA battery – Security: – Unique Network key (EUI64) and ensure security on network level – Unique Application key (EUI64) ensure end to end security on application level – Device specific key (EUI128)



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▪ Technology Architecture Focused – Long Range

• LoRa Alliance • Weightless SIG

– Designed to operate in Industrial, Scientific and Medical (ISM) spectrum. These sub-1GHz frequency bands - 868MHz in Europe, 900MHz in the US

– Frequency hopping to provide best in class interference tolerance – Data Rates: Range from 100 kbps to 16 Mbps – Security: – Weightless has adopted the shared secret key regime. – This requires that a 'secret number' be held securely in both a Weightless controlled central server and in the

edge device.

• Internet Engineering Task Force – DTLS - Datagram Transport Layer Security – UDP - User Datagram Protocol – IPv6 - Internet Protocol, Version 6 – CoRE is providing a framework for resource-oriented applications

intended to run on constrained IP networks. – ROLL - Routing Over Low power and Lossy networks – CoAP - Constrained Application Protocol – 6LoWPAN - IPv6 over Low power Wireless Personal Area Networks – XMPP - Extensible Messaging and Presence Protocol - XMPP IoT – HTTP - Hypertext Transfer Protocol



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▪ Technology Architecture Focused – Long Range

• LoRa Alliance • Weightless SIG • Internet Engineering Task Force • ISO (International Organization for Standardization)

– Members: » ISO is an independent, non-governmental organization made up of members from the national standards

bodies of 163 countries. – ISO/IEC JTC 1/SWG 5 – ISO/AWI 18575 - Internet of Things (IoT) in the supply chain

▪ Multilayer / Stack Initiatives • Open Interconnect Consortium

– Founding Members: Atmel, Dell, Intel, Samsung, Wind River – Platform Support: RTOS, iOS, Windows 8, Linux, Arduino, Android, Tizen, Yocto

• oneM2M – There are two key elements at the core of oneM2M: providing an interworking framework and enabling re-use

of what is already available as much as possible.



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▪ Vertical/Industry Focused – Connected Body

• Continua Alliance

– Connected Home • Thread Group

– Founding Members: Arm, Nest, Somfy, Big Ass Fans, Samsung, Tyco, Freescale, Silicon Labs, Yale – Tech Coverage – Addressing: DHCPv6 – Message Routing – Security: Encryption (AES128) – Interoperability: Transport Layer Support: 6LoWPAN as the foundation, Requires just a software enhancement

for 802.15.4 products. – Application Layer Support: CoAP and Smart Objects, Zigbee Smart Energy 2.0, Echonet Lite

• Apple Homekit • Z-Wave Alliance • HomePlug Alliance • Home Gateway Initiative


IoT 플랫폼 표준 사례 – oneM2M (1/2)

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IoT 플랫폼 표준 사례 – oneM2M (2/2)

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IoT 플랫폼 표준 동향 – OCF (OIC)

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▪ 2014년 7월 OIC (Open Interconnect Consortium)가 삼성, 인텔 등을 중심으로 시작해서 2015년 12월 스마트 홈의 대표적 국제표준단체인 UPnP포럼을 통합 흡수, 회원사가 100개 이상으로 성장하였고 2016년 2월에 마이크로소프트, 퀄컴 등이 합류하여 확대된 기업 표준화 단체

▪ OCF (Open Connectivity Foundation)는 사물인터넷을 구현 시 REST 구조 기반으로 경량형 CoAP 프로토콜로 사물인터넷 장치들을 연결하고 장치에 존재하는 자원들을 상호제어 할 수 있게 하는 표준 플랫폼 기술

▪ OCF 주축 기업들로 MS, 시스코, 일렉트로룩스, GE, 인텔, 퀄컴, 삼성전자, 아리스, 케이블랩스 등


LoRaWAN (1/4)

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▪ Semtech와 IBM 리서치 개발▪ CDMA, DSSS CDMA 기술 활용

LoRa Device Developer Guide - Orange Partner


LoRaWAN (2/4)

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A technical overview of LoRa® and LoRaWAN™ Technical Marketing Workgroup 1.0


LoRaWAN (3/4)

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LoRaWAN (4/4)

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LoRa 요금제 (SKT)

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NETMANIAS: http://www.netmanias.com/ko/post/operator_news/10129 2016.07.04


LTE MTC (Machine Type Communication)/NB-IoT

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Qualcomm Technologies. Inc. 2016: paving-the-path-to-narrowband-5g-with-lte-iot



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LTE Cat-1(Today)

LTE Cat-M1(Rel-13)

LTE Cat-NB1(Rel-13)

Peak data rate DL: 10 MbpsUL: 5 Mbps

DL: 1 MbpsUL: 1 Mbps

DL: ~20 kbpsUL: ~60 kbps

Bandwidth 20MHz 1.4MHz 200kHz

Rx antenna MIMO Single Rx Single Rx

Duplex mode Full duplexFDD/TDD

Supports half duplex FDD/TDD

Half duplexFDD only

Transmit Power 23 dBm 20 dBm 20 dBm



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▪ Reduced complexity – Usually do not require the wideband operation of LTE

▪ Low cost ▪ Network Longevity

– LTE has become one of the fastest growing wireless technologies providing a solid foundation for many years to come

▪ Network efficiency ▪ Multi-year battery life

– Enhanced power save modes and more efficient signaling ▪ Deeper coverage

– with established networks serving ~2.7 Billion 3G/4G connections worldwide ▪ Coexistence with today’s mobile broadband services


IoT에서 문제점

• 엄청나게 많은 Thing들의 동시 접속에 따른 무선 통신 시스템의 혼란• Things 내부의 OS 취약으로 통신 및 제어에 많은 지연 발생

표준화의 필요성!

(OneM2M, 3GPP….)

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MTC 단말의 급증에 따른 LTE 망의 혼란 (Lee & Kim, 11)

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비효율적인 OS에 따른 지연

One bot Three bots

S.-L. Kim et al., “Massive Robotic Networks over Bluetooth Low Energy: An Experimental Study,” submitted for publication, 2015.


• FIT IoT-LAB Operating Systems; https://www.iot-lab.info/operating-systems/ • Internet-of-Things Software Guide; http://postscapes.com/internet-of-things-software-guide

System Overview Programming Model Language Link

Tiny OS An open source, BSD-licensed operating system designed for low-power wireless devices, e.g.) those used in sensor networks, ubiquitous computing, personal area networks, smart buildings, and smart meters. A worldwide community from academia and industry use, develop, and support the operating system as well as its associated tools, averaging 35,000 downloads a year.

Event Driven, support for TOS threads

NesC http://www.tinyos.net/

Contiki Contiki is an open source, highly portable, multi-tasking operating system for memory-efficient networked embedded systems and wireless sensor networks. Contiki has been used is a variety of projects, such as road tunnel fire monitoring, intrusion detection, wildlife monitoring, and in surveillance networks.Contiki is designed for microcontrollers with small amounts of memory. A typical Contiki configuration is 2 kilobytes of RAM and 40 kilobytes of ROM.

Protothreads and events

C http://www.contiki-os.org/

Mantis The MANTIS Group at CU Boulder has developed an open source, multi-threaded operating system written in C for wireless sensor networking platforms. Some key features of MANTIS OS (MOS): Developer friendly C API with Linux and Windows development environments Automatic preemptive time slicing for fast prototyping Diverse platform support including MICA2, MICAz, and TELOS motes Energy-efficient scheduler for duty-cycle sleeping of sensor nodeSmall footprint (less than 500B RAM, 14KB flash)

Threads C http://mantisos.org/index/tiki-index.php%3Fpage=HomePage.html

Nano-RK Nano-RK is a fully preemptive reservation-based real-time operating system (RTOS) from Carnegie Mellon University with multi-hop networking support for use in wireless sensor networks. Nano-RK currently runs on the FireFly Sensor Networking Platform as well as the MicaZ motes. It includes a light-weight embedded resource kernel (RK) with rich functionality and timing support using less than 2KB of RAM and 18KB of ROM. Nano-RK supports fixed-priority preemptive multitasking for ensuring that task deadlines are met, along with support for CPU, network, as well as, sensor and actuator reservations. Tasks can specify their resource demands and the operating system provides timely, guaranteed and controlled access to CPU cycles and network packets. Together these resources form virtual energy reservations that allows the OS to enforce system and task level energy budgets.

Threads C http://www.nanork.org/

LiteOS LiteOS is an open source, interactive, UNIX-like operating system designed for wireless sensor networks. With the tools that come with LiteOS, you can operate one or more wireless sensor networks in a Unix-like manner, transferring data, installing programs, retrieving results, or configuring sensors. You can also develop programs for nodes, and wirelessly distribute such programs to sensor nodes.

Threads and Events

LiteC++ http://www.liteos.net/

FreeRTOS FreeRTOS is a real-time operating system for embedded devices, being ported to several microcontrollers. It is distributed under the GPL with an optional exception.

- C http://www.freertos.org/

IoT를 위한 Operating Systems

https://www.iot-lab.info/operating-systems/

http://postscapes.com/internet-of-things-software-guide

http://postscapes.com/internet-of-things-software-guide

http://www.tinyos.net/

http://www.contiki-os.org/

http://mantisos.org/index/tiki-index.php?page=HomePage.html

http://www.nanork.org/

http://www.liteos.net/

http://www.freertos.org/


4. Robotic Social Networks


IoT의 미래

• 쇼셜네트워크와 IoT와 결합 (SIoT)

L. Atzori, A. Iera, G. Morabito, and M. Nitti, “The social internet of things (SIoT)-when social networks meet the internet of things: Concept, architecture and network characterization,” Comput. Netw., vol. 56, no. 16, pp. 3594–3608, 2012.

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machine 2

Interesting information

machine 1

Searching map

“self-configuration, self-optimization, self-protection, and selfhealing”


소셜네트워크의 진화

• Phase 1 (1960s – 2000s) – Human social networks as the field of study in social sciences – Milgram’s “small world experiment”

• “Six degrees of separation”

• Phase 2 (2000s – 2010s) – ICT-enabled human social networks – An unprecedented source of data on human behaviour

• Facebook, Twitter, etc…

• Phase 3 (2010s – 2020s) – Machine social networks

• Continuation of rapid improvements in computing and communication technologies will induce the formation of mchine social networks

• Based on web of IoT, …

I. Bojic, T. Lipic, and V. Podobnik, “Bio-inspired clustering and data diffuision in machine social networks,” a part of book, A. Abraham Ed., “Computational social networks: mining and visualization,” 2012.

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!

BS

Internet + cloud server

Machine social

networks

Human social

networks

machine

machine

smartphone

machine

connected car

laptop

machine machine

desktop

smartphone

machine

쇼셜네트워크의 미래


RAMO – Test bed

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D. M. Kim, Y. J. Hwang, S.-L. Kim and G.-J. Jin, "Testbed Results of an Opportunistic Routing for Multi-Robot Wireless Networks," Elsevier Computer Communications, Vol 34 (18), pp. 2174-2183, December 2011.

J. H. Jung, S. Park and S.-L. Kim, “Multi-robot Path-finding with Wireless Multihop Communications,” IEEE Communications Magazine, Vol. 48 (7), pp. 126-132, 2010.

Mobility in Radom Wireless Networks Multi-robot Path finding

BR Routing과 Zigbee를 사용한 다중 로봇의 군집 제어


RAMO – Test bed

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Maze

AP #1

AP #2

AP #3

AP #4

Machine #3 Machine #1Machine

#2

Making the map of Maze!!!

Making chat server: WiFi server (AP mode?)

Sharing info.

Connecting the chat server.


RAMO – Test bed

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Bluetooth 기반의 다중 로봇 군집 제어

이경섭, 심태형, 김성륜 “사물 간 상호 신뢰도 평가 알고리즘을 통한 오작동 탐지 및 회복 네트워크", 한국통신학회 추계학술대회. 2014.

Trust-based Distributed Algorithm for Robot Network

Multi-Robot Path-Finding with Malicious Bots in Wireless Networks

S. Park, S. Kim, D.-E. Kang, J. Kim and S.-L. Kim, "Multi-Robot Path-Finding with Malicious Bots in Wireless Networks" in Proc. the 10th Int'l Conference on Future Internet Technologies (CFI), Seoul, Korea, 2015.


RAMO – Espresso robot

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Robot Appearance

Small & Ultra Low Power• Espresso capsule size robot (3cm * 3cm)• Ultra low power ARM Cortex-M0 Core

Bluetooth 4.1• Communicate with Nordic nrf51822• Supports both BLE Central and BLE Peripheral roles

Mobility• Two vibration motors and three legs• Simple mobility : right / left turn, straight



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Robot Components

Battery 3.7v / 110mAh Lithium Ion Battery

Body 3D Printing

BLE Nano nRF51822

LED RGB LED

Motors Two Vibration Motrs



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Communications

▪ Nordic nrf51822 : Bluetooth 4.1 with microcontroller ▪ 1:1 communication by BLE ▪ BLE central (master) and peripheral (slave) role change ▪ Master can choose its slaves by reading slaves’ profileZ

Slave (Peripheral)

Master (Central)

ID Profile

Advertising

Connection request



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Control


Q&A

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