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WINLAB Summary
Dec 2014
Rutgers, The State University of New Jersey
www.winlab.rutgers.edu
Contact: Professor D. Raychaudhuri, Director
WINLAB
WINLAB
WINLAB Summary: Mission & Resources WINLAB founded in 1989 as a collaborative industry-university research
center with specialized focus on wireless networking Mission is to advance both research and education in the area of wireless technology (… a topic of
fast growing importance across the entire information technology field!)
Research scope includes information theory, radio technology, wireless networks, mobile computing
and pervasive systems
Participation in several major federal research initiatives in the wireless and networking fields -
cognitive radio/spectrum, future Internet architecture (FIA), GENI
Unique SOE resource with local, national and international recognition and impact
WINLAB resources in brief: ~25 faculty/staff, most from the ECE and CS departments at Rutgers
~40-50 grad students (80% PhD, 20% MS) – ~50 PhD’s graduated since 2005; ~20 UG internships
~$5M/yr research funding (80% federal, 20% industry); ~15 corporate sponsors from all over the world
~20,000 sq-ft facility, mostly at the Rt 1 Technology Center building (see photo)
Unique experimental capabilities including ORBIT testbed (see photo) and WiNC2R cognitive radio
ORBIT Radio Grid Testbed WINLAB Tech Center Facility
WINLAB 3
WINLAB Summary: Research Vision Radio everywhere from ~1B wireless devices in 2005 to
~10B in 2010 100B in 2020! Fundamental capacity and scale limits
Overcoming spectrum scarcity
New technology foundation – cognitive radios
Wireless – Internet convergence into a single global network as mobile terminals replace PC’s Architectural implications of mobility, disconnection, location, …
Wireless “network-of-networks” with heterogeneous radios, multi-hop, etc.
Clean-slate protocol architecture centered around mobility & context
From basic voice/data communications pervasive computing Wireless as the glue for integrating the Internet with the physical world
Importance of geographic location as a key attribute
Security and privacy
Various application domains – transportation, healthcare, security, industrial automation, …
WINLAB 4
WINLAB Summary: Research Topics
12/14
Networking
cluster
Mobile Computing &
Pervasive cluster
Radio/PHY
& Spectrum
White Space
Backhaul
Spectrum Sensing
DSA Protocols &
Algorithms (SAVANT)
Software Defined Radio
Platforms (WISER)
Cognitive Radio
Algorithms
Cognitive Radio
Algorithms
Radar Spectrum
Sharing
Massive MIMO,
Network MIMO
Open Base Station/
Software LTE
Cloud Extensions
To ORBIT
Optical/Wireless
Integration
Wireless SDN
Network Coding
Prospect Theory for
Data Network Pricing
MobilityFirst Future
Internet Architecture
5G Mobile
Wireless Network
Virtualization
DSRC V2V
Simulator
GENI Project
Wireless Network
Security
Updating Systems
& Networks
Transmit Only
Green Communication
JUNO Mobile
Cloud CPS
Visual MIMO
SDN Spectrum
Management
Automotive
Inforverse
Capacitive
Touch-Screen
Crowdsourcing of
Physical World Tasks
Mobile User
Privacy Guardian Angel
Safety Systems
Content Delivery
Networks IoT Networking &
Software Platform
LTE/WiFi
Coexistence
Location Privacy via
De-Idenfication
Ad Hoc Mobile
Cloud
GNRS
EIR
V2V MCDN M-homing….
Router
design
MF-VN
WINLAB 5
WINLAB Summary: Selected Govt
Funded Projects 12/14 Govt funded projects at WINLAB ..update
ORBIT CRI: major equipment upgrade for radio grid testbed (NSF CRI, ‘10-14)
GENI Spiral III projects – Open WiMAX enhancements & kit (BBN GENI ‘11-’14)
MobilityFirst Future Internet Architecture – Next Phase (NSF, 2014-16)
Visual MIMO (NSF, 2011-15)
Spectrum Cooperation (SAVANT) & Optical Sensing Platform (NSF EARS, 2013-16)
WISER Wideband Software Defined Radio Platform (NSF, 2013-16)
End-user Behavior and Prospect Pricing (NSF, 2014-17)
SDN Framework for Opportunistic Networking and Spectrum (ONR, 2014-17)
Status Updating Systems and Networks (NSF, 2014-17)
Multi-layer Approach to Reliable Cognitive Radio Networks (NSF, 2014-17)
Transmit Only: Cloud Enabled Green Communications (NSF, 2014-17)
Crowdsourcing of Physical-World Tasks with Myrmex (NSF SoCS 2012-15)
Guardian Angel Safety Systems (NSF, 2014-2017)
Mobile Privacy Projects (NSF TWC 2012-15)
Vehicle Safety Messaging (CAMP, 2013-14)
Virtual Mobile Cloud Network (NSF JUNO, 2014-17)
WINLAB 6
Status Update: Industry Sponsors 12/14
*
*Research Partners
InPoint
Semandex
Zipreel
*
*
*
US Army CECOM
*
~~
*
*
WINLAB 7
WINLAB Summary: Industry Research
Topics Ongoing topics/collaborations with sponsors:
Verizon: Multi-antenna dense deployment, WiFi integration, stadium
deployment at Rutgers,
InterDigital: ICN architecture, content network models, ..
Qualcomm: vehicular networking including smartphone integration, 5G
network architecture
Ericsson: 5G architecture (EC METIS-II), dynamic spectrum, wireless
SDN
DoCoMo; dense small cells, 5G architecture, integrated scheduling &
control of 5G macro/small cell
Huawei: internet-of-things (IoT) architecture, 5G mobile network, white-
space backhaul
NEC: SDN for wireless; mobile WiFi evaluation
WINLAB
WINLAB Summary: People
Dipankar
Raychaudhuri Roy Yates Narayan Mandayam Chris Rose Wade Trappe Predrag Spasojevic Yanyong Zhang Marco Gruteser Ivan Seskar
Athina Petropulu Larry Greenstein Dick Frenkiel Rich Howard Richard Martin
Yicheng Lu
Melissa Gelfman Noreen DeCarlo Janice
Campanella Elaine Connors
Shridatt
Sugrim ~40-PhD & MS
Students as of 2014
(see www.winlab.rutgers.edu for photos)
Kiran Nagaraja Kishore Ramachandran
Ilya Chigivev
Hui Xiong
Silvija
Kokalj-Filipovic
Janne Lindqvist
~~
Thu Nguyen
9
Research Highlights
WINLAB
Generic Scenario : E.g. Wichita, KS
• Area: 423 square km2
• Population: 385,577 (2012 Census) [1]
• Available white space for fixed devices [2]
57 79 85 491 527 533 671
Location
(MHz)
WINLAB
LTE-U based Backhaul with Local WiFi
Access
WiFi Coverage Area
WiFi Coverage Area
WiFi Coverage Area
WiFi Coverage Area
WiFi Coverage Area
Backhaul Tower with
WS Radio and WiFi AP for
local distribution
Backhaul Tower with
WS Radio and WiFi AP for
local distribution
WiFi Coverage Area
WiFi Coverage Area
Tower with Fiber Access
LTE-U Link
BS 5
BS 1
BS 2 BS 3
BS 4
BS 6
BS 7
LTE-U BS 1 Coverage
Area
LTE-U BS 6 Coverage Area
WiFi Coverage Area
BS 8
LTE-U BS 4 Coverage
Area
WINLAB
MaxMin Rate Backhaul using NC-OFDMA
A1
A2
A3
E.g. 4 COs, 9 cells can serve 81 sq km
WINLAB
ICN Pricing: System Modelb
( )
0
( )
0
1
1
c
A A A B B o
c
B B B A A o
p p p
p p p
User’s demand
How much to cache?
How much to charge (price)?
WINLAB
ICN Pricing: Game Theoretic Modeling
and Analysis
Utility Functions
Caching Costs
Static and Dynamic
Strategies
)c()p()c(U AABBCAAAA (s)
A,AOUTA,AAA, ppαpα
},{ },{ },,,{
)(
C),(CC)(K, )(pα)(pαBAK BAK KMOBAM
s
MMKKCKC pcU
(c)
o
},{
(s)
o),( p)()(p BA
BAK
oOKKO cU
WINLAB
ICN Pricing: Summary of results Content Agnostic Case result in 0-1 strategies:
Degenerate case (no need for transit network) when transit ICN
price is greater than access ICNs caching price
C-dominant case (transit ICN cache all the demands) when
transit ICN price is greater than access ICNs caching price and
transit C caching cost is less than content provider caching cost
O-dominant case (content provider caches all the demands)
when transit ICN price is greater than access ICNs caching
price and transit C caching cost is less than content provider
caching cost
Current work includes models on content popularity
15
WINLAB
SAVANT: Inter-network Spectrum
Coordination
Underlying Network Infrastructure
(Internet)
AP
Spectrum
Gateway (SG) Spectrum
Gateway (SG)
Leverage the fact that Internet connects almost all interfering devices!
• Communication over the back-end is virtually free
• Precise view of the traffic is readily available
• Works across technologies (WiFi/cellular/others)
Key Advantages:
WINLAB
SAVANT: Algorithms
Non-adaptive parameter selection (NAPS)
Explicit query-response only on initialization
Intended for low-cost devices with simple radios
Adaptive Parameter Selection (APS)
Initialization procedure same as NAPS
Additional periodic spectrum usage updates
provided by its radio neighbors
Global Coordinated Resource Packing (GCRP)
Provisions direct exchange of coordination messages
between different devices in radio range
Leads to iterative algorithm for globally
optimal resource packing between co-existing radios
WINLAB
100:075:2550:5025:750:1000
0.2
0.4
0.6
0.8
1
Ratio of Non-cooperative vs. Cooperative APs
Me
an
No
rma
lize
d T
hro
ug
hp
ut
50 APs/sq. km.
100 APs/sq. km.
150 APs/sq. km.
200 APs/sq. km.
SAVANT: Cooperative Channel Assignment
Full Cooperation
Role of cooperation for Wi-Fi channel assignment
Dense Wi-Fi network simulations with realistic modeling of
the normalized throughput given 3 channels
No Cooperation
100:075:2550:5025:750:100-10
0
10
20
30
40
50
Ratio of Non-cooperative vs. Cooperative APs
Pe
rce
nta
ge
of sta
rve
d A
Ps
50 APs/sq. km.
100 APs/sq. km.
150 APs/sq. km.
200 APs/sq. km.
WINLAB
WiFi/LTE Co-Existence:
Experimental Setup
Experimental setup when both w1 and
interference operated on the same channel in
2.4 GHz
UE-AP dist
(fixed) = 0.25m Inter-AP dist
(variable) range =
[1,20]m
Interferin
g AP
WiFi
AP
Associated
WiFi UE
w1
Parameter Value
Frequency 2.462 GHz (WiFi
channel 11)
WiFi
bandwidth
20 MHz
LTE bandwidth {5, 10} MHz
WiFi nodes 802.11g, Atheros
AR928X, AP:
hostapd, data traffic:
full buffer UDP
LTE nodes USRP B210
WINLAB
WiFi/LTE Experimental Results
0 5 10 15 200
5
10
15
20
25
Distance[m]T
hro
ug
hp
ut[
Mb
ps]
WiFi Interference
LTE 5MHz Interference
LTE 10MHz Interference
No interference Wi-Fi throughput
0 5 10 15 20
0
5
10
15
20
25
Distance[m]
Th
rou
gh
put[
Mb
ps]
Exp Errorbar
Experimental Throughput
Analytical Throughput
Comparison of Wi-Fi throughput observed
by experiments and computed by analytical
model as a function of distance(LTE HeNB,
Wi-Fi link)
LTE: 5 MHz, lightly loaded
Comparison of Wi-Fi throughput observed by
experiments in the presence of different
sources of interference – (1)Wi-Fi, (2) LTE
(fully loaded): 5 MHz BW, and (3) LTE (fully
loaded): 10 MHz BW
WINLAB
Network Cooperation &
Logically Centralized DSA
21
Logically
central
optimization
Approaches
1) Power control at Wi-Fi APs
and LTE-U HeNB
2) Channel access time
division
• Orthogonal channel
access for WiFi and LTE
Location, channel gain,
frequency
Known Parameters
Maximize System Throughput
(bits/sec/km2)
Min data rate at user
Constraints
WINLAB
LTE/WiFi Coordination
Results – Performance of LTE
22
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
No coordination Power control optimization Time division channel access
optimization
WINLAB
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
Coordination Results:
Performance of WiFi
23
20 40 60 80 100-100
-50
0
50
100
AP-UE dist [m]
Inte
rfering A
P-U
E d
ist [m
]
10
20
30
40
50
60
Performance of Wi-Fi link in the presence of interfering LTE AP (HeNB)
No coordination Power control optimization Time division channel access
optimization
WINLAB
ICN-IoT System Architecture
…
…...
Sensors/Actuator/Smart devices
Data signal generation
Key predistribution
Energy mgmt
IoT Aggregator (e.g. Raspberry Pi, Smart
Phone) Data collection
Data filtering, grouping and formatting
Device/Service Discovery Service
Device local naming service
Local Service Gateway Subscribe to the formatted sensor data
Context data Processing& storage
Name Assignment Service
Local/Global ID translation
Sensor data access policy enforcement
ICN Network
IoT Server:
Pub/Sub
Management,
System Monitoring
APP—Website, Mobile
APP:
ICN Data Consumer
Radio-specific Interface
Adaptation ICN
Adaptor
ZigBee, TO,
6LoWPAN, BLE,etc
ICN Non-
ICN
ICN
ICN-
UNI
Edge
Service
Router
Service Controller
Edge
Service
Router
Service
Provider
ICN-NNI
ICN/Non
-ICN Heterogeneous Collector Cluster (e.g., Mote/Receiver/Sensor
Router, Nest) Context-supervised sensor discovery & clustering
Data relay with security
Data
Center
V2V-ICN
ICN
IoT
Aggregators
(e.g. RSU)
WINLAB
IoT Functionalities
FIA Optional: In-network Computing
(Data Aggregation/Fusion)
Network Service
( Unicast, Multicast, Anycast, etc)
Pub/Sub Management
Device/Network Service
Discovery Service
Device/App Naming Service
Name-based Routing
Sensor
Actuator
Gateway
Data Aggregation
Producer Consumer
Service
App
Context processing & storage
Smart Things
Mobility & Security
Secu
rity
IoT Middleware
Differentiate function comp
App Service Discovery
Self Clustering/Organization
WINLAB
Three Components Protocol
Stack
ICN_lite
MAC
802.15.
4
Applicatio
n
ICN
MAC
802.15.4/B
LE/802.11/
Cellular
Application
ICN
MAC
802.11/802.
3
Embedded Device IoT Aggregator
Local Service
Gateway Network
Service
Discovery
Self-Clustering
Device local
naming
service
Network
Service
Discovery
Data-
collection
Device/Servic
e Discovery
Service
Device local
naming
service
Subscribe to
the formatted
sensor data
Context data
Processing&
storage
Name
Assignment
Service
Local/Global
ID translation
Sensor data
access policy
enforcement
WINLAB
Device and Service Discovery
Workflow
Device broadcasts its manufacture
information with discovery message
”sensor gateway service
request”
Start
Aggregator receives broadcast
message
Aggregator registers the device and
generates local ICN name for the
device
Aggregator sends local ICN name to
the device
Gateway
service name
match?
Stop
Y
N
Request Aggregator broadcasts its
discovery message” Well-known
name service request”
Start
Target Aggregator receives
broadcast message
Target Aggregator processes the
service request and generates an
ACK message
Target Aggregator sends the ACK to
the requested Aggregator
Service name
match?
Stop
Y
N
Device
Discovery Service
Discovery
WINLAB
IoT Evaluation
A. Static Sensor Network B. Mobile Sensor On Vehicle
WINLAB
WiSER Cognitive Radio Platform
Abstract lower level design
complexities from Users
INNOVATION CYCLE
Live system runs
Focus on Creativity, not Engineering Complexity :
Split Baseband in two domain spaces : • Dynamic – Swappable
Communication APPs (creative problem)
• Static - Open-sourced System-on-Chip (complex engineering problem)
CRKIT = make real-time and wide-tuning radio a viable solution for large scale experiments.
WDR from Radio Technology Solutions
FSoC Features
Access to lower level resources thru APIs
VITA radio transport protocol for radio control
Networking capable node
Support up to four dynamic APPs
Library of Open-sourced Communication APPs
Static Framework utilization level < 15% for
V5SX95, even less for newer technologies, for ex.
Virtex7 .
Transparent to underlying FPGA technology.
Can be ported to future HW platforms and newer
FPGA technologies.
Pis: Ivan Seskar, D. Raychaudhuri
WINLAB
WiSER Programming Model
Network
HOST CRKIT
Application
development
CRKIT
development
Comm.
APP
Embedded
SW GUI Algorithm
System
Debugging
System
Test
HW
Configuration
IP
Networking
Mathworks
Simulink CR DSA
Host
CMD Parsing
VHDL/
Verilog
DHCP/ARP ETH/VITA Lookup Tables/
RF
Java, C# C C
WINLAB
WiSER Baseline Hardware ZedBoard baseboard (Zynq
XC7Z020 device)
Dual-core ARM® Cortex™-A9
256 KB on-chip RAM
Gigabit Ethernet, 2x
SD/SDIO, USB,CAN, SPI,
UART,I2C
512 MB DDR3, 256 Mb QSPI
Flash
85K Logic Cells, 106K FF
220 Programmable DSP
Slices (18x25 MACCs)
Zynq-7000 SoC / Analog Devices Software-Defined Radio Kit
Analog Devices FMC RF Front-end
Software tunable across wide frequency range (400MHz to 4GHz) with 125MHz
channel bandwidth (250MSPS ADC, 1GSPS DAC)
RF section bypass for baseband sampling
Phase and frequency synchronization on both transmit and receive paths
WINLAB
WiSER Framework Architecture
1. Dual-core ARM processors
• Linux support
• Dual AXI bus architecture
• Independent Data and Control
traffic
2. Independent APP sampling rates
• Support Multirate and Multi-APP
systems
• Decoupling of APP clock domains
from overall Framework.
• Permits Spectrum Sensing APP +
Communication APP in same
architecture
3. Applications
• Reuse previously designed APPs
• NC-OFDM
• Spectrum Sensing
4. RF
• 400MHz to 4GHz tuning range
• 125MHz Channel Bandwidth
(250MSPS ADC, 1GSPS DAC)
• Full-duplex
WINLAB
SDN Wireless Research Current scope of WINLAB activities on SDN:
– GENI campus network (OpenFlow)
– GENI Open Base station
– ORBIT SDN sandbox
– MobilityFirst Prototype
– OpenFlow extensions for WiFI, etc.
– SDN control plane and application to DSA
– Cellular/mobile network
WINLAB
ORBIT NP: Massive MIMO with Radio
Cloud
WINLAB
Future Networks: Broad Trends
Content-Centric
Network
New possibilities in networking enabled by changing
technology platforms & architectural concepts
Technology
Platforms
Network
Realizations
Router/Switch
Hardware
WCDMA & LTE
Radio Access
OpenFlow (SDN)
Switch
Virtual
Machine (VM)
SDN Mobile/
Cloud RAN
Open LTE
Base Station
Software-Defined
Radio (SDR) WiFi Radio
1G/10G Ethernet
WiFi Radio
Inc. 60 Ghz
3GPP mobile
network IP inter-network
Ad Hoc
Mesh
Customizable
Wide-Area Networks
(e.g. CDN, cloud)
100M/1G Ethernet
SDN Enterprise:
Ethernet + WiFi
Click Software
Router
Veh Net, Ad Hoc, etc.
Programmable Router
Architecture
IP
Cellular Mobility-
Centric Internet
“Fog” Computing, etc.
Circa 2010 Circa 2020
60 Ghz 802.11ad
WINLAB
SDN Wireless: Future Cellular/5G Arch
Radio Resources
(LTE BS, WiFi AP, etc.)
also, general purpose
Adaptive SDR devices
Standardized
Control API’s
Resource Domain
Distributed Control Plane (..resource discovery,
Bootstrapping, topology control, routing)
Wired + ad hoc wireless connectivity
Service Applications on
Cloud or Operator Machines
Internet
Backbone
Mobility
RRM
Virtual Net
Service Mgmt
WINLAB
SDN Wireless: LTE Open BTS
OpenVSwitch
RF/ePC Aggregate Manager
eth2
eth
0.v
l1e
th0.v
l2e
th0
.vln
X2,S
1-U
,S1-M
ME
,...
WINLAB
SDN Wireless: Open BTS + network
Ad
apta
tio
n/H
and
off
Co
ntr
olle
r
OPEN BS2 OPEN BS3
...SDN Datapah Complex
Gen
eric
Res
ou
rce
Co
ntr
olle
r
...
WINLAB
SDN Wireless: Control Plane Concept
Network OS with wireless abstractions
MobilityMgmt.
WirelessAccessControl
Wired + Wireless Network
QoSControl
ChannelAssign-ment
Tx PowerControl
Inter-Network
Coordination
Data Plane Apps Control Plane Apps
Through extension of OpenFlow Match/Action Fields
Through the ControlSwitch
framework
Introducing flexibility in the wireless control plane by
leveraging software defined networking techniques
Inter-network cooperation translates to inter-controller
interactions and setting of flow-rules
WINLAB
SDN Wireless: Basic Design Interpret wireless control
messages as flows
BS/AP uses
Match/Action rules to
forward incoming and
outgoing control-flows
Control traffic can be
forwarded to/from other
BSs or central controller
Local SDN based
controller for low latency
actions
Msg Type Parameters IP Port …
Set Channel Forward to Port 1
Report Beacons Forward to IP1,IP2
Match FieldsAction
Control Messages
BS HW
Insert Flow Rules
Controller
Local Controller
Control
Datapath
WINLAB
SDN Wireless: Distributed Control Extension of traditional Enterprise Controller:
Multiple copies of wireless controllers (WC) with mechanisms to
cooperate, scattered throughout SDN based control plane
Reduced distance between device and a controller – reduced flow setup
times (reduced control latency)
BS/AP Control Network (data
plane)
Wireless
Controller
Wireless
Controller
Shared State
Control
WINLAB
SDN Wireless: Hierarchical Control Example: Pair of enterprises with heterogeneous
decomposed controllers
BS/AP Control Network
(data plane)
BS/AP Control Network
(data plane)
AI
1 AI
1
H2 H1
Tier 1
Tier 2
H3 H2 H1
Authentication/Interference
Handoff
WINLAB
GENI Wireless Deployment
Wayne State
Clemson
U Michigan
Columbia
UMass U Wisconsin
Madison
U Colorado Boulder
UCLA
Stanford
Rutgers
Temple
Drexel
NYU
WINLAB
FLEX
Open and highly
configurable LTE
platforms
Interaction of the user
with the
real 4G world.
Commercial and Open
Source
equipment
44
Courtesy: FLEX Consortium
WINLAB
CREW Testbed as a Service with Ontology Repository (TaaSOR)
Community focused WEB based tool
• Grounding by team consensus on
shared ontologies
• Knowledge reuse by including
complementing networking ont.
(NOVI, NDL, NDL-OWL)
• Generated ontologies instantly
available online and published as
Linked Data as well as SPARQL
endpoint
WINLAB
CREW (cont’d)
46
Spectrum Sensing Semantic
WINLAB
WiSHFUL
Courtesy: Ingrid Moerman, iMinds
Objectives:
• Reduce threshold for
experimentation
• build open, flexible &
adaptive software
platforms with unified
programming interfaces
for intelligent radio and
network control
• Increase the realism of
experimentation
• Offer portable testbeds
that can be deployed at
any location allowing
validation in the real
world and involving real
users
WINLAB
METIS-II Project Objectives:
1. Develop the overall 5G RAN design
2. Provide the 5G collaboration framework within 5G-PPP
for a common evaluation of 5G RAN concepts
3. Prepare concerted action towards regulatory and
standardisation bodies
Key Innovation Pillars: Holistic spectrum management architecture
Holistic air interface harmonisation framework
Agile Resource Management (RM) framework
Cross-layer and cross-air-interface system access and mobility framework
Common control and user plane framework
Courtesy: METIS-II Consortium
WINLAB
METIS-II Consortium
Courtesy: METIS-II Consortium
WINLAB
Mobile Cloud: High-Level Goals
Goal: efficient support of cloud services for mobile devices Improve mobile computation speed & latency
Balance between remote data center and edge cloud
Dynamic migration, geo-replication and geo-elasticity
Identify MF protocol enhancements for improved cloud performance
Virtual networks for resource isolation and application-specific topology/routing
Support for peer-to-peer mode among mobiles
50
GLOBAL NETWORK
EDGE CLOUD
Mobility
REMOTE DATA CENTER
PEER NETWORK
WINLAB
Mobile Cloud: Virtual Mobile Cloud Network (mVCN) (..joint project with NICT under NSF-Japan
collaboration)
Technical Approach: MF service Addressability via GUID, anycast, virtual networks, ..
WINLAB
Mobile Cloud: Virtual Networks in MF
MF architecture provides integrated support for virtual networks (VN) GUID provides a unique naming mechanism for VN and constituent resources
GNRS gives fast mapping between VN’s GUID and attachment NAs
Routers can be designed to execute application specific routing (ASR) for each VNID
R1
R2
R3
R4
R5
San Fran Chicago
R6
Berlin
Tokyo
AT&T Verizon
Virtual network - service provider - NetFlix
AT&T Interface
Verizon Interface Netflix - coordinator
Physical substrate - infrastructure provider - AT&T
Physical substrate - infrastructure provider - Verizon
R7
GNRS
VN Specific
Routing
(ASR)
Core
MF
Routing
WINLAB
The Automotive Infoverse Parking Availability
Estimation
Wireless
Service
Valid Parking
Spot Map
Rangefinde
r
+ GPS
WINLAB
Detection of Vehicles Emitting GPS
Interference
• RF sources from vehicles can
interfere with critical infrastructure
• Identifying a source vehicle is
currently a manual process with
handheld devices
• Demonstrated an automated
system that uses multiple roadside
monitoring points
WINLAB
Completed Development of a V2V
Scalability Simulator
Develops a Dedicated Short Range Communications (DSRC) simulator for the Crash Avoidance Metrics Partnership Vehicle Safety Communications 3 consortium
Uses field test data from hundreds of DSRC equipped vehicles to develop and calibrate simulation models
Aims to accurately predict V2V communication performance in very dense, interference-limited scenarios.
WINLAB
Mobile Safety Services Phone driver
distraction contributed to 995 fatalities in 2009 (NHTSA)
Goal: Develop toolkit and platform to facilitate mobile safety service development
Allow crowdsourcing of reliability data and adaptation of interventions
WINLAB
Pedestrian Safety Services
• Can devices warn distracted pedestrians to
look up as they walk off from a sidewalk into
the street
• Profiles the surface gradient using shoe
mounted inertial sensors
• Uses the ground profiles to detect transitions
from sidewalk to street via ramps and curbs
New York City
WINLAB
Wifi Activity Sensing
0
0.2
0.4
0.6
0.8
1
a b f g h i j o
Single WiFi device
Mult. WiFi device
0
0.1
0.2
0.3
0.4
a b f g h i j o
Single WiFi device
Mult. WiFi device
2-bedroom apartment
Activity types
Activity types
FN
R
TP
R
2-bedroom apartment
• Tracking human activities can
support a variety of assisted
living and context applications
• Measure fine-grained channel
properties (amplitude and
phase per subcarrier) from
802.11n Wifi devices
• Demonstrated device-free
distinguishing of key locations
and activities with two Wifi
links
MobilityFirst Update
WINLAB
MobilityFirst Project: Background
MobilityFirst project started in 2010 under NSF FIA,
continuing under FIA-NP
Project team: Rutgers, UMass, Michigan, Wisconsin,
Duke, MIT, Nebraska
Clean-slate architecture motivated by fundamental shift
of Internet services to mobile platforms ~10B in 2020!
Use cases:
Mobile Data
(cellular, hetnet)
Vehicular Networks Content Delivery
Cloud Services
Internet-of-Things Emergency Networks
WINLAB
MobilityFirst Concepts: Architecture Summary
Routers with Integrated
Storage & Computing Heterogeneous
Wireless Access
End-Point mobility
with multi-homing In-network
content cache
Network Mobility &
Disconnected Mode
Hop-by-hop
file transport Edge-aware
Inter-domain
routing
Named devices, content,
and context
11001101011100100…0011
Public Key Based
Global Identifier (GUID)
Storage-aware
Intra-domain
routing
Service API with
unicast, multi-homing,
mcast, anycast, content
query, etc.
Strong authentication, privacy
Ad-hoc p2p
mode
Human-readable
name
Connectionless Packet Switched Network
with hybrid name/address routing
MobilityFirst Protocol Design Goals: - 10B+ mobile/wireless devices
- Mobility as a basic service
- BW variation & disconnection tolerance
- Ad-hoc edge networks & network mobility
- Multihoming, multipath, multicast
- Content & context-aware services
- Strong security/trust and privacy model
Global Name
Resolution Service
WINLAB
MobilityFirst Concepts: Protocol Stack
IP
Hop-by-Hop Block Transfer
Link Layer 1
(802.11)
Link Layer 2
(LTE)
Link Layer 3
(Ethernet)
Link Layer 4
(SONET)
Link Layer 5
(etc.)
GSTAR Routing MF Inter-Domain
E2E TP1 E2E TP2 E2E TP3 E2E TP4
App 1 App 2 App 3 App 4
GUID Service Layer Narrow Waist GNRS
MF Routing
Control Protocol
NCS Name
Certification
& Assignment
Service
Global Name
Resolution
Service
Data Plane Control Plane
Socket API
Switching
Option
Optional Compute
Layer
Plug-In A
WINLAB
MobilityFirst Concepts: Name-Address
Separation GUIDs Separation of names (ID) from
network addresses (NA)
Globally unique name (GUID)
for network attached objects User name, device ID, content, context,
AS name, and so on
Multiple domain-specific naming
services
Global Name Resolution Service
for GUID NA mappings
Hybrid GUID/NA approach Both name/address headers in PDU
“Fast path” when NA is available
GUID resolution, late binding option
Globally Unique Flat Identifier (GUID)
John’s _laptop_1
Sue’s_mobile_2
Server_1234
Sensor@XYZ
Media File_ABC
Host
Naming
Service
Network
Sensor
Naming
Service
Content
Naming
Service
Global Name Resolution Service
Network address
Net1.local_ID
Net2.local_ID
Context
Naming
Service
Taxis in NB
WINLAB
MobilityFirst Concepts: GUID Service
Example
MobilityFirst Network
(Data Plane)
GNRS
Register “John Smith22’s devices” with NCS
GUID lookup
from directory
GUID assigned
GUID = 11011..011
Represents network
object with 2 devices
Send (GUID = 11011..011, SID=01, data)
Send (GUID = 11011..011, SID=01, NA99, NA32, data)
GUID <-> NA lookup
NA99
NA32
GNRS update
(after link-layer association)
DATA
SID
NAs
Packet sent out by host
GNRS query
GUID
Service API capabilities:
- send (GUID, options, data)
Options = anycast, mcast, time, ..
- get (content_GUID, options)
Options = nearest, all, ..
Name Certification
Services (NCS)
WINLAB
GMap Design -- Latency GlobalGNRSServerMap
R1 R2 R3
L1 L2 L3 L1 L2 L3 L1 L2
LapA (GUID=10)
Update GUID=10
Local Replica Regional Replica 1st Global Replica 2nd Global Replica
LapB
Lookup GUID=10
GUID10
R..L..SID10;R..L..SID11
R2..SID29
R2L2SID80
global
regional
local
GUID to SID Mapping
Server/Router
1st level geo-partition
2nd level geo-partition
GUID10
R..L..SID10;R..L..SID11
R2..SID29
R2L2SID80
global
regional
local
GUID to SID Mapping
WINLAB
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 20 40 60 80 100 120 140 160 180
CDF of Lookup Queries
Query latency (ms)(L2R6G2)
g
l+g
r+g
l+r+g
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 20 40 60 80 100 120 140 160 180
CDF of Lookup Queries
Query latency (ms)(L2R2G6)
g
l+g
r+g
l+r+g
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 20 40 60 80 100 120 140 160 180
CDF of Lookup Queries
Query latency(ms)(L6R2G2)
g
l+g
r+g
l+r+g
Lookup Query Latency improvement:
g: deployment of 5 global replicas,
g+r: on regional addition to 5 global replicas
g+r+l: one local, one regional and 5 global
replicas
L: local locality (query majorly from same
metro as the GUID)
R: regional locality (query majorly from the
same country as the GUID)
G: global locality (query uniformly from
worldwide)
L6R2G2: 60% L, 20% R, 20% G
Locality and Mobility
Synchronized
WINLAB
Content Service in MF: In-Network Caching
with Mobility Prediction (GNRS Assisted)
0.2 0.4 0.6 0.8 1 1.2 1.4 1.60
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Zipf exponent parameter
Cache H
it R
atio
LRU
popCache
popCache+userPredict
popCache+netPredict
MF Network with content cache at routers
Popularity based caching with mobility
prediction
GNRS used to provide supplementary
mobility information
Significant improvement in cache-hit ratio…
WINLAB
EIR Design Features 1. Aggregation nodes (aNodes) and virtual links (vLinks)
Aggregation of intra-network
topology
aNode 21
aNode 22
aNode 23
aNode 24
aNode 25
aNode 411
Routers aggregated into a virtual aNode topology
Intra-domain vLink
Inter-domain vLink
R2 R3
R4 R1
aNode 02
AS 144AS 14
aNode 23
AS 314
aNode 411
AS 214
• aNodes and vLinks as abstractions
to expose internal network topology
of an AS
• Aggregated information of a
collection of routers and links
• Flexible aggregation granularity
68
2. Network state dissemination
• Network-wide propagation of state packets (nSPs) containing:
• aNode and vLink connectivity info
• vLink properties (Mbps, % avail, estimated time of transmission (ETT), functional parameters, etc.)
WINLAB
Border routers determine cut-through paths based on transit and local policies
Route injection packets are pushed by border routers to inject label info in fast path forwarding table
Transit traffic at the ingress border router is ‘marked’ transit and appended with the label
No inter-domain routing/policy info required at the internal routers 69
5. Fast path for transit
traffic
R2R2 R3R3 R5R5 R7R7
R6R6
R8R8 BR2BR2
BR3BR3
aNode 1 aNode 2aNode 3
aNode 4
aNode 5
AS-1
R4R4
R1R1BR1BR1
Fast Path Table
AS-2
BRyBRy
AS-3
Label based path injection from the border router
#L1 R1 R4 R5 R7 R8 BR2
#L2 R1 R2 R4 BR3
BR2#L1
R7#L5
R7#Lx
......
Next hopLabel
BRxBRx
EIR Design Features
WINLAB
Evaluations
Edge network mobility (SFO bus
traces)
Bus ID1 2 3 4 5 6 7 8 9
Da
ta u
nd
erg
oin
g r
ebin
din
g/s
tora
ge
(%
)
0
0.5
1
1.5
2
2.5
3
3.5
A=4A=6A=8
Packet delivery rate for different values of telescopic function using realistic
network mobility scenario
• End host mobility
• Probabilistic mobility
model of end hosts
• Caida based topology of
aNodes and vLinks
• Late binding of data at an
intermediate aNode for
faster delivery
Path stretch with and without late binding
• Routing table size
Fraction of aggregation
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
An
ode
ta
ble
siz
e (#o
f e
ntrie
s)
# 105
0
2
4
6
8
10
12
aNode table sizeactive BGP entries(BGP)• Internet scale topology
from Caida
• Varying levels of router
aggregation into aNodes
Routing table size of EIR vs. BGP
• Network overhead
Settling time (secs)0 2000 4000 6000 8000 10000 12000 14000
Ne
two
rk o
ve
rhe
ad
(G
bp
s)
0
10
20
30
40
50
60
70
80
90
100
A=6,alpha=2A=6,alpha=4A=8,alpha=2A=8,alpha=4A=10,alpha=2A=10,alpha=4A=12,alpha=2A=12,alpha=4
• Network overhead vs.
settling time for 40,000 +
AS topology
• Different values of
telescopic function
WINLAB
MobilityFirst Router Implementation
71
Click Forwarding Engine
Routing Name
Resolution Mgmt.
Service Classifier
Rx Q Tx Q
To/From Host
Host Rx Q Host Tx Q
Content Cache Service
Rsrc Control
User-level Processes
Next-hop Look up
Block Aggregator
Block Segmentor
Forwarding Table
To Next-hop Lookup
Hold buffer
x86 hardware and runtime
Wir
ed a
nd
wir
eles
s i/
f Wired
and
wireless i/f
DMap – DiHT
Locality-Aware DNS
GSTAR
R3
Compute Services
Inter-Domain
PacketCloud Framework
Packet Classifier
Integrate
Early Dev.
WINLAB
MobilityFirst Host Protocol Stack
72
Network API
E2E Transport
GUID Services
Routing
‘Hop’ Link Transport
Interface Manager
WiFi WiMAX
App-1 App-2
Security
‘Socket’ API open send send_to recv recv_from close
Network Layer
User policies
Linux PC/laptop with WiMAX & WiFi
Android device with WiMAX & WiFi
Device: HTC Evo 4G, Android v2.3 (rooted), NDK (C++ dev)
Integrate
Early Dev.
Context API
App-3
Context Services
Sensors
WINLAB
Evaluation Strategy for MobilityFirst Architecture
Degree of Realism
Scale
Math models
Network Science
Opnet or ns Simulator
WINLAB ORBIT Radio Grid Emulator
GENI Open Cellular
Campus Testbeds
GENI Core
Network
3rd Gen CR Platforms USRP2
USRP/GNU Radio
SDN/SDR Sandbox in ORBIT
1
2
3
4
3
Routing & GNRS
Validation
OpenFlow MF
Controller
Service demos &
Real World Users
Wide Area
MF Network
Early Adopter
Trials (MF-NP)
WINLAB
MobilityFirst Deployment on GENI
Salt Lake, UT
Cambridge,
MA
N. Brunswick,
NJ
Ann Arbor, MI Madison, WI
Tokyo, Japan
Lincoln, NE
Los Angeles,
CA Clemson,
SC
Long-term (non-
GENI)
MobilityFirst Access
Net
Short-term
Wide Area ProtoGENI
Palo Alto, CA
ProtoGENI
MobilityFirst
Routing and Name
Resolution
Service Sites
I2
NLR
Atlanta, GA
Long running MF “slice” in GENI to validate routing and name resolution and
to run real-world applications on mobile devices (in wireless coverage areas)
WINLAB
GEC-12 Demo: Named Content Delivery in MF
75
WiMAX BTS WiMAX BTS
WiFi AP
WiFi AP
Rutgers Wireless Edge BBN Wireless Edge
I2 path using VLANs 3715, 3745(BBN), 3798 (Clemson)
GUID=1
GUID=2
GUID=3
Bridge
GUID=4
GUID=5
GUID=6
GUID=7
NLR path using VLANs 3716, 3799 (Clemson)
ProtoGENI host running MF Router, GNRS Server
GUID=101
GUID=201
Content Publisher
Content Subscriber
GUID & SID
DATA
NA
DATA
ProtoGENI Backbone
WINLAB
GEC-13 Demo: Mobility & Multi-Homing in MF
76
WiMAX BTS
WiFi AP pc1@BBN
pg51@Rutgers
Rutgers Wireless Edge
pc11@BBN
pg50@Rutgers pg33@GeorgiaTech
WiMAX coverage
WiFi coverage MobilityFirst Router hosted on Protogeni node
GENI Mesoscale
Mobile, Multi-homed device (WiMAX + WiFi)
WINLAB
GENI 18 Demo: Wide-Area Deployment of MF
MF Routing and Naming Services deployed at 5 GENI rack sites with Internet2’s AL2S providing cross-site layer-2 connectivity
Rutgers and NYU Poly (with rack at NYU) routers connected to WiFi and WiMAX access networks
Android phones with WiFi/WiMAX connectivity ran MF stack and demo application (Drop It)
6/12/2015 WINLAB, Rutgers University 77
Wisconsin
GENI rack
Utah
GEN
I
rack
BBN
GENI
rack GENI Internet2
Core
GENI
Edge
GENI
Edge
WiMAX
BTS
WiMAX
BTS
MobilityFirst
Software Router
with GNRS
instance Dual interface
Android phone
with WiFi/WiMAX
with MF protocol
stack
ORBIT radio
node with WiFi
as MF Access
point
WINLAB 78
User1
User2
Internet
Media transcoding
via MF compute layer
Original source
Sample “mobile cloud” service scenario:
Adaptive media transcoding via MF compute layer
Name-based anycast service via MF routing
HD
Mid Mid
Low Res
GEC-21 Demo: In-Network Computing
Feature in MF
WINLAB
NE Trials: 5Nines Network, Madison
NE1: Mobile Data Service Trial with 5Nines (ISP) in Madison, WI
WINLAB
5nines access network
Other sites
Internet
WiMAX
Base station
Compute
resource
WiFi
AP
Compute
resource
UW enterprise network
5nines data
center and NAP
User devices
Vehicular
clients
Logical structure of the various WiMAX and WiFi infrastructure to be used in experiments
Central ASN and Radius service
NE Trials: 5Nines Network Topology
WINLAB
NE Trials: PBS/WHYY Content
Service Trial in PA
NE2: Content Services Trial with PennREN/PBS in PA
WINLAB
NE Trials: CASA Emergency Network
NE3: Context-Aware Emergency Notification System (CASA)
WINLAB 83
Web Sites for More Information:
WINLAB: www.winlab.rutgers.edu
ORBIT: www.orbit-lab.org
MobilityFirst: http:
mobilityfirst.winlab.rutgers.edu
