di per I’Internet of Things: di – IEIIT - ANITEC · Tecnologie di comunicazione per I’Internet of Things: ... MIMO relay network for 5G communications Some key features of 5G

CNR IEIIT – Wireless Communications GroupConferenza del Dipartimento DIITET 26 e 27 maggio 2014

Tecnologie di comunicazione per I’Internet of Things:sistemi, architetture di rete, applicazioni e test‐bed

Marco Fiore – IEIITBarbara M. Masini – IEIITAlessandro Nordio – IEIITAndrea Passarella ‐ IITAlberto Zanella – IEIIT

Consiglio Nazionale delle Ricerche

Dipartimento di Ingegneria, ICT e Tecnologie per l’Energia e i Trasporti (DIITET)

Internet of things e Manufacturing 4.03 Maggio, 2016Consiglio Nazionale delle Ricerche, Aula MarconiPiazzale Aldo Moro, 7 ‐ Roma

CNR IEIIT – Wireless Communications GroupInternet of things e Manufacturing 4.0 DIITET-CNR

“Everything that computes connects” [A. Evans, Intel’s Corporate]

• By 2020, 50 billion “things” will be connected: cars, smart city sensor systems, savvy home appliances, industrial automation systems, connected health innovations, drones, robots, …

• All of these things will need to connect wirelessly to the internet

• Transformation of the way we communicate and interact with the world

• Gartner released research forecasting 6.4 billion “connectedthings” in 2016. Next year, 5.5 million new IoT connectionswill be made daily

Alberto Zanella, IEIIT-CNR, [email protected]


Connected Things as Enabler of New Applications

Source:www.theregister.co.uk

Internet of Vehicles

Healthcare

Smart Buildings Smart Energy Industry automation



Connected Things as Enabler of New Applications

Source:www.theregister.co.uk

Internet of Vehicles

Healthcare

Smart Buildings Smart Energy Industry automation


CNR IEIIT – Wireless Communications Group

How these “Things” connect

• Short range (NFC, Zigbee, Bluetooth, …)• Medium range (Wi‐Fi, …)• Long range (4G, 5G, LTE‐M, …)

Internet of things e Manufacturing 4.0 DIITET-CNRAlberto Zanella, IEIIT-CNR, [email protected]


Outline

• Transmission technologies• Networking• Examples of test bed and field test

Internet of things e Manufacturing 4.0 DIITET-CNRAlberto Zanella, IEIIT-CNR, [email protected]


Transmission technologies

Internet of things e Manufacturing 4.0 DIITET-CNR

• Energy and Data Rate Fairness in Wireless Networks of Things

• MIMO relay network for 5G communications • Signal and data processing for IoT (Interreg project)

Alessandro Nordio, IEIIT-CNR, [email protected]


Energy and Data Rate Fairness in Wireless Networks of Things

Optimal multi‐hop communication strategy achieving high data rate providing fairness in the node

power consumption and data rates

reducing the interference due to simultaneous transmissions

taking into account power required by CPU amplifiers, memory and radiated power



MIMO relay network for 5G communications

Some key features of 5G networks• support high user densities• high data rates• low energy consumptions

Proposed solutions• smaller cells • device‐to‐device communications• relay networks

Performance of communications over MIMO relay channels



MIMO relay network for 5G communications

Performance of communications over MIMO relay channels

Problems under study Achievable rate depending on the

channel condition and system parameters

Outage probability (Quality of Service) Multiple scattering channels Optimal user scheduling Performance of linear receivers

Impact on levels 1 and 2 of the ISO OSI stack



"energy is consumed by people rather than by buildings"

EXPECTED OUTCOMES Risen awareness on energy efficiency and saving IT tools (mobile apps, dashboards, …) to support behavioral

change in energy users Draft policies for energy efficiency and spatial development Set up of Co‐Creation Labs

FOCUSBehavioral changes of energy users necessary to reduce energy consumption in the Alpine spaces.



Networking

• Network requirements and technologicalchallenges for IoT scenarios

• Examples of CNR research activities in the field

Internet of things e Manufacturing 4.0 DIITET-CNRBarbara Masini, IEIIT-CNR, [email protected]


Network Requirements

13Internet of things e Manufacturing 4.0 DIITET-CNR

Low latency & High reliabilityEven in mobility

Networking in dense environmentswith QoE & QoS

Barbara Masini, IEIIT-CNR, [email protected]


Integration of Heterogeneous Things

Integration of different types of ‐ Devices:

‐ wearable, personal, smartphones, home appliance, industrial machines, vehicles, roads, buildings, energy..

‐ Tiny, big, wearable, fixed, …‐ Technologies

‐ Zigbee, Bluetooth, Wi‐Fi, LTE‐A, Li‐Fi, mmWave, …‐ M‐MIMO, energy harvesting, non othogonal multiple access, full duplex, cognitive,

... ‐ Different features in terms of data rate, reliability, computational power, storage

power, availability of energy, flexibility in handling different technologies, mobility, …

‐ Services‐ Uncountable: from vehicular application, to smart buildings, smart energy, M2M,

industrial automation, ...‐ Support a variety of applications even with extremely diverse requirements of

bandwidth, latency, reliability, …

14Internet of things e Manufacturing 4.0 DIITET-CNRBarbara Masini, IEIIT-CNR, [email protected]

CNR IEIIT – Wireless Communications Group15

•Integration of different wirelss technologies, e.g. WAVE/IEEE 802.11p at 5.9 GHz and LTE‐A with D2D capabilities at 2 GHz or 5.9 GHz•V2I (Vehicle‐to‐Infrastructure) and V2V(Vehicle‐to‐Vehicle) Communication Support•Broadcast of beacon messages with information such asposition, speed, direction,…•Best hop selection


Network ArchitecturesExample application: Internet of Vehicles


Tools to Evaluate Complex IoT Performance and examples of research activities of CNR

• Complete simulation toolstaking into account– Scenario (position, mobility, maps, …)

– Network characteristics(PHY, MAC, upper layers)

– Services and Applications (what and when transmit)

– Propagation– …

• Simulation platforms for realistic IoT scenarios

• Network optimization • Device2Device networking• Hybrid networking for

connected networks• Traffic data analytics

16Internet of things e Manufacturing 4.0 DIITET-CNRBarbara Masini, IEIIT-CNR, [email protected]

CNR IEIIT – Wireless Communications Group 17

Users managementTransport protocols (TCP, UDP), routing

(CRRM)

e.g. Wi‐Fi

t

Client 1

e.g. LTE

t

Client N

ULS: Sim

ulatore

Livelli Sup

eriori

LLS: Sim

ulatore

Livelli Inferio

ri

Sessions Files, Mobility Files, Activity Files

SHINE(Simulation platform for Heterogeneous

Interworking Networks)

Server

APP

PRES

SESS

TRANSP

NET

DL

...

wireless

wired

Mobileterminal

Node‐B / AP

ExternalSource / Dest.

PHY


SHINE: simulation platform for heterogeneous interworking networks


(Even) external input: Mobility, traffic flows, maps



Application

Presentation

Session

Transport

Network

Data Link

Physical






Application

Presentation

Session

Transport

Network

Data Link

PhysicalConnectivity degree in different traffic conditions

for a given routingalgorithm

55%






Application

Presentation

Session

Transport

Network

Data Link

Physical

IEEE 802.11p to offloadCellular networks

Internet of things e Manufacturing 4.0

Connectivity degree in different traffic conditions

for a given routingalgorithm

55%



Context: Optimisation of local network resources in 5G

• 5G: heterogeneous mix of long‐range and short‐range network technologies

• Local networking– Optimisation of network resources

at the edge

• Pushed by (among others)– Exponential growth of IoT devices– Proximity services

• Social interaction, Local advertising, Public safety– Local data management

• E.g., due to confidentiality constraints

• Standardisation– IETF/ETSI for IoT– LTE‐D2D (ProSe) for cellular

Andrea Passarella, IIT-CNR, [email protected]


IoT local network optimisation• Optimisation of the IETF IoT stack

– Experimental analysis of RPLinefficiencies

– Definition of improved protocolsdecreasing packet loss

• With operational testbeds

• Information Centric Networking for IoT– “access to data, irrespective of the specific devices

where it is stored”– Current ICN Internet drafts for content‐centric

Internet• Limited to the core of the network

– Extension of the ICN standards toIoT devices

• Low‐resource devices• Mobility

– ICN compliant stack for IoT networksimplemented in CCN‐lite

• ICN‐standards ready

INTERNET



Device2Device networks in 5G

• Why Device2Device communications inIndustry 4.0

– Support local data management– Efficient use of local IT resources

• Mobile devices– Context‐aware services between users nearby

• Local advertising

• Self‐organising networks– Build ad hoc “P2P” networks among

co‐located mobile devices

• Integration of ad hoc networks with cellular and WiFi infra

– Exploit additional capacity of ad hoc networks– Coordinated with edge infrastructure devices

• Provide local network management tools– To optimally configure the local network inside the owner’s

premises• Including users’ mobile devices

– Integrated with services provided externally by telco providers

% of trafficmanaged locally



Hybrid networking for connected vehicles• Offloading of cellular FCD traffic via D2D communication

• HDSA/LTE not designed to manage uplink FCD• Our approach

• Combines D2D (DSRC / LTE‐A) & traditional cellular communications• Achieves up to 75% reduction of FCD load on cellular radio access

–75%

Marco Fiore, IEIIT-CNR, [email protected]


Traffic data analytics for 5G cognitive networks• Big data analytics for network‐wide mobile traffic

A. Temporal perspective – at which time instants does mobile traffic shows comparable dynamics? When do unexpected behaviors emerge? And why?

2. Outliers



Traffic data analytics for 5G cognitive networks• Big data analytics for network‐wide mobile traffic

B. Spatial perspective – at which locations does mobile traffic follow similardynamics? How do such dynamics look like? And what induces them?



Examples of test bed and field test


‐ Visible light communication (VLC) test bed

‐ Safety real‐time applications for connected vehicles (virtualtraffic light) field test



Useful in dense RF environments


6 m

Hybrid communication with new wireless accesse.g., Visible Light Communication (VLC)


CNR IEIIT – Wireless Communications Group 2929Internet of things e Manufacturing 4.0 DIITET-CNR

Traffic Light with no physical infrastructure, devices on vehiclescommunicate with each other to define the priorities at the crossingwith a distributed control

Why is VTL important?‐ Only 0.5% of over 50 millions of crossing points in USA are equipped with traffic lights‐ Operative costs (per year) for traffic lights : 780 milions of dollars‐ It is impossibile to have all crossing points equipped by traffic lights

Virtual Traffic Light (VTL) service application

VTL equipmentKey‐characteristics:wireless, efficient,low cost

Basic rule:ony one car at a time can pass the crossing point



Virtual Traffic Light: Field test

30Internet of things e Manufacturing 4.0 DIITET-CNRAlberto Zanella, IEIIT-CNR, [email protected]


References/1• 1. Nordio, Chiasserini, Tarable, "Bounds to Fair Rate Allocation and Communication Strategies in Source/Relay Wireless Networks", IEEE

Transactions on Wireless Communications, 2014.• 2. Nordio, Chiasserini, Tarable, "Optimization of Source/Relay Wireless Networks With Multiuser Nodes" IEEE Transactions on Wireless

Communications, 2014.• Zhou, Alfano, Chiasserini, Nordio, "MIMO Relay Network With Precoding", IEEE Communications Letters, 2016.• Zhou, Alfano, Nordio, Chiasserini, "Ergodic Capacity Analysis of MIMO Relay Network Over Rayleigh‐Rician Channels", IEEE Communications Letters,

2015.• Bazzi, A. Zanella, B. M. Masini, “An OFDMA Based MAC Protocol for Next Generation VANETs”, IEEE Transactions on Vehicular Technology, 2015• Bazzi, Barbara M. Masini, Alberto Zanella, Gianni Pasolini, IEEE 802.11p for cellular offloading in vehicular sensor networks, Computer

Communications, 2015• Bazzi, A.; Masini, B.M.; Zanella, A., "Performance Analysis of V2V Beaconing Using LTE in Direct Mode With Full Duplex Radios," in Wireless

Communications Letters, 2015• Bazzi, B. M. Masini, A. Zanella, D. Dardari, "Performance evaluation of softer vertical handovers in multiuser heterogeneous wireless networks",

2015• Emilio Ancillotti, Raffaele Bruno, Marco Conti “Reliable Data Delivery With the IETF Routing Protocol for Low‐Power and Lossy Networks”, IEEE

Trans. Industrial Informatics 10(3): 1864‐1877 (2014)• Emilio Ancillotti, Raffaele Bruno, Marco Conti, Enzo Mingozzi, Carlo Vallati, “Trickle‐L2: Lightweight link quality estimation through Trickle in RPL

networks”. WoWMoM 2014: 1‐9• Emilio Ancillotti, Raffaele Bruno, Marco Conti “The role of the RPL routing protocol for smart grid communications”. IEEE Communications

Magazine 51(1): 75‐83 (2013)• Emilio Ancillotti, Raffaele Bruno, Marco Conti “On the interplay between RPL and address autoconfiguration protocols in LLNs”. IWCMC 2013:

1275‐1282• Emilio Ancillotti, Raffaele Bruno, Marco Conti:RPL routing protocol in advanced metering infrastructures: An analysis of the unreliability problems.

SustainIT 2012: 1‐10• Lorenzo Valerio, Raffaele Bruno, Andrea Passarella, “Cellular traffic offloading via opportunistic networking with reinforcement learning”.

Computer Communications 71: 129‐141 (2015)• Filippo Rebecchi, Lorenzo Valerio, Raffaele Bruno, Vania Conan, Marcelo Dias de Amorim, Andrea Passarella, ”A joint multicast/D2D learning‐based

approach to LTE traffic offloading”. Computer Communications 72: 26‐37 (2015)• Raffaele Bruno, Antonino Masaracchia, Andrea Passarella, “Offloading through Opportunistic Networks with Dynamic Content Requests”, IEEE

CARTOON 2014: 586‐593


References/2• L. Valerio, F. Ben Abdesslem, A. Lindgren, R. Bruno, A. Passarella, M. Luoto “Offloading cellular traffic with opportunistic networks: a feasibility

study”. Med‐Hoc‐Net 2015: 1‐8• Lorenzo Valerio, Andrea Passarella,. Marco Conti, Elena Pagani, “Scalable data dissemination in opportunistic networks through cognitive

methods”. Pervasive and Mobile Computing 16: 115‐135 (2015).• Matteo Mordacchini, Andrea Passarella, Marco Conti, “Social Cognitive Heuristics for adaptive data dissemination in Opportunistic Networks”.

WOWMOM 2015: 1‐9. • R. Stanica, M. Fiore, F. Malandrino, Offloading Floating Car Data, IEEE WoWMoM 2013, Madrid, Spain, June 2013• S. Ancona, R. Stanica, M. Fiore, Performance Boundaries of Massive Floating Car Data Offloading, Invited paper, WONS 2014, Obergurgl, Austria,

April 2014• S. Uppoor, M. Fiore, Characterizing pervasive vehicular access to the cellular RAN infrastructure: an urban case study, IEEE Transactions on

Vehicular Technology, Vol.64, No.6, June 2015• D. Naboulsi, R. Stanica, M. Fiore, Classifying Call Profiles in Large‐scale Mobile Traffic Datasets, IEEE INFOCOM 2014, Toronto, Canada, April 2014• A. Furno, D. Naboulsi, R. Stanica, M. Fiore, Mobile Demand Profiling for Cellular Cognitive Networking, IEEE Transactions on Mobile Computing, to

appear• A. Furno, R. Stanica, M. Fiore, A Comparative Evaluation of Urban Fabric Detection Techniques Based on Mobile Traffic Data, ACM/IEEE ASONAM,

Paris, France, August 2015


Thank you!

• Marco Fiore – IEIIT• Barbara M. Masini – IEIIT• Alessandro Nordio – IEIIT• Andrea Passarella ‐ IIT• Alberto Zanella – IEIIT

email: [email protected]

Documents

di per I’Internet of Things: di – IEIIT - ANITEC · Tecnologie di comunicazione per I’Internet of Things: ... MIMO relay network for 5G communications Some key features of 5G