Transcript WINLAB IAB Meeting May 2014 WINLAB Rutgers, The State University of New Jersey www.winlab.rutgers.edu Contact: Professor D.

WINLAB IAB Meeting
May 2014
WINLAB
Rutgers, The State University of New Jersey
www.winlab.rutgers.edu
Contact: Professor D. Raychaudhuri, Director
[email protected]
1
STATUS UPDATE
2
Status Update: General News

WINLAB’s overall activity level remained stable in FY 2013-14

External research funding for FY14 ~$6M total
 Follow-on $5M (~$2.3M at Rutgers) “MobilityFirst” FIA-NP project
 Other recent grants include NSF Wideband SDR (300K), DARPA Spectrum
Challenge (450K), NSF JUNO (300K), NSF Automotive Infoverse ($100K), …

Faculty and visitor appointments during 2013-14
Prof. Hana Godrich, WINLAB/ECE – expertise in smart grids & control
 Dr. Yi Hu, Post Doctoral Associate for Future Internet research
 Dr. K.K. Ramakrishnan (ex-AT&T), Adjunct Prof on MobilityFirst project
 Prof. Larry Greenstein retiring after 12 years of service
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Some highlights
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DARPA spectrum challenge completed successfully – IEEE Spectrum Article
Global-scale MobilityFirst protocol & application demos at GEC-17,18
2014 IEEE Donald J. Fink Award for IEEE Proceedings paper on future of wireless
2014 ECEDHA Innovative Program Award to WINLAB
Best paper award for MobilityFirst service API at ACM MobiArch 2013
Conducted benchmark simulations on 802.11p for auto industry consortium (CAMP)
WINLAB
3
Status Update: WINLAB Research Targets
Mobile web
services
IP Routing +
Cellular Mobility
Content- and context-aware protocols, M2M
Programmable networks, cloud services,
ContentPrivacy, HCI, mobile social networks
and contextaware pervasive
services
Storage-aware routing, global name
resolution, location, vehicular nets,
privacy/security, ad hoc/DTN routing, …
Cooperative relay, cross-layer,
beam switching, software MAC,..
Static MAC
Protocols
Mobility-Centric
Internet Arch
Flexible &
Adaptive MAC
Network MIMO, network coding,
interference alignment, 60 Ghz,
Next-Gen
Gigabit PHY
Single User
MIMO/OFDM
Spectrum sensing, NC-OFDM,
Spectrum server, cognitive algorithms,
Coordination protocols, ..
Static Spectrum
Assignment
Dynamic Spectrum
Assignment
~10x eficiency
WINLAB
Status Update: Research Topics

Current research themes at WINLAB (..not an exhaustive list):
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Radio/PHY
cluster
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Networking
cluster
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Pervasive
cluster
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Cognitive radio hardware (Seskar, Spasojevic)
Collaborative PHY (Spasojevic, Petropulu)
Spectrum sensing and DSA algorithms (Mandayam, Spasojevic, Seskar)
White space backhaul (Mandayam, Seskar)
Network coding (Mandayam, Spasojevic)
Rechargeable wireless networks (Yates)
Error coding techniques for mmWave 5G (Spasojevic)
Sensor networks and M2M/IoT (Zhang, Trappe, Howard, Li, Martin)
Network-assisted DSA and SDN implementation (Raychaudhuri, Seskar)
Experimental platforms: ORBIT, SDR, GENI WiMax/LTE, OpenFlow… (Seskar, Raychaudhuri)
Future Internet architecture (Raychaudhuri, Zhang, Yates, Trappe, Martin, Nagaraja)
Mobile cloud computing (Zhang, Raychaudhuri, Seskar, Nagaraja)
Vehicular networks – wireless and optical V2V (Gruteser)
Security and privacy in wireless networks (Trappe, Gruteser, Zhang, Lindqvist)
Mobile content caching delivery (Yates, Zhang, Gruteser)
Context-aware mobile applications (Martin, Zhang, Gruteser, Lindqvist, Howard)
Mobile social networks (Lindqvist, Gruteser)
WINLAB
5
Status Update: Selected Govt
Funded Projects 5/14

Govt funded projects at WINLAB
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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, 2011-14)
Bandwidth Exchange (NRL, 2011-14)
Spectrum Cooperation (SAVANT) & Optical Sensing Platform (NSF EARS, 2013-16)
Mobile Ad Hoc Network (ARMY, 2012-14)
Spectrum Challenge (DARPA, 2013-)
WISER Wideband Software Defined Radio Platform (NSF, 2013-16)
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Location privacy via de-identification (NSF Career 2009-14)
Crowdsourcing of Physical-World Tasks with Myrmex (NSF SoCS 2012-15)
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: Pending Proposals 5/14
2013-14 continued to be active year for medium/large federal proposals to
NSF, NRL, DARPA, Army and other federal agencies.
Several pending govt proposals including:
RF Equipment for Dynamic Spectrum Access (ONR, $248K)
Computing Backend for Data Analysis of Wireless & Network Data (ARO, 129K)
SciWiNet: Science Wireless Network for Research Community (NSF, 100K)
Dependable Context Sensing for Mobile Safety (NSF CSR, 537K)
Cloud Processing Extensions to ORBIT ($2M)
Security for Body Communications (NSF TWC, 250K)
Status Updating Systems and Networks (NSF CIF, 476K)
Redesigning Web Browsers for Privacy (NSF TWC, 250K)
Robust Gesture Based Authentication (NSF TWC, 399K)
Transmit Only: Cloud Enabled Green Comm (NSF NeTS, 498K)
End User Behavior and Prospect Pricing in Wireless Data Networks (NSF NeTS, 500K)
Software Defined Scientific Data Networks (NSF CC*IIE, 1000K)
Green Architecture for Rural Backhaul using TVWS and Solar (NSF EARS, 744K)
Coexistence in Spectrum: Coalitions, Machine Learning and Distributed Strategies (NSF
EARS, 749K)
…+ others
WINLAB
7
Status Update: Major Future Research
Themes

Dynamic spectrum: measurement, backhaul, small cell, etc.

“Cloud RAN” architecture & key technologies
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Software defined wireless/mobile systems (SDN + SDR)
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“Edge cloud” for mobile and real-time CPS services

“Big Data” architecture/privacy/applications for mobile
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Passive sensing & localization for in-building context
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…other
WINLAB
8
Status Update: Industry Research
Topics (cont.)

Some previous inputs from sponsors:
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Verizon: Multi-antenna dense deployment, WiFi integration, stadium
deployment at Rutgers,
InterDigital: ICN architecture, content network models, ..
Qualcomm: vehicular networking including smartphone integration, 60
Ghz WLAN, application concepts
Ericsson: 5G cellular technologies, dynamic spectrum, future Internet
DoCoMo; dense small cells, 5G architecture, integrated scheduling &
control of 5G macro/small cell
Huawei: internet-of-things (IoT) architecture, 5G mobile network, whitespace backhaul
NEC: SDN for wireless
WINLAB
9
~~
Status Update: Industry Sponsors 5/14
US Army CECOM
*
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*
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InPoint
Semandex
Zipreel
*
*
*Research Partners
WINLAB
10
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WINLAB Summary: People
Dipankar
Raychaudhuri
Yicheng Lu
Melissa Gelfman
Hui Xiong
Roy Yates
Narayan Mandayam
Chris Rose
Athina Petropulu
Larry Greenstein
Dick Frenkiel
Noreen DeCarlo
Janice
Campanella
Thu Nguyen
Silvija
Kokalj-Filipovic
Elaine Connors
K.K. Ramakrishnan
Wade Trappe
Predrag Spasojevic
Rich Howard
Richard Martin
Shridatt
Sugrim
Ilya Chigivev
Yanyong Zhang
Marco Gruteser
Kiran Nagaraja Kishore Ramachandran
Khanh Le
Ivan Seskar
Janne Lindqvist
~40-PhD & MS
Students as of 2011
(see www.winlab.rutgers.edu for photos)
WINLAB
Research Highlights
12
SAVANT: Inter-network Spectrum
Coordination
Leverage the fact that Internet connects almost all interfering devices!
Key Advantages: • Communication over the back-end is virtually free
• Precise view of the traffic is readily available
• Works across technologies (WiFi/cellular/others)
Underlying Network Infrastructure
(Internet)
Spectrum
Gateway (SG)
Spectrum
Gateway (SG)
AP
WINLAB
SAVANT: Architecture
Architecture involves two protocol interface levels between
independent wireless domains:
• Lower layer for sharing aggregate radio map using technology neutral
parameters
• Higher layer for negotiating spectrum use policy, radio resource
management (RRM) algorithms, and controller delegation
WINLAB
SAVANT: The Protocol
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Internetwork Spectrum Coordination Protocol (ISCP)
S-Interface for radio map

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Contains network identifier, network parameters (such as location,
technology type, etc.) and a summary radio map
M-Interface for algorithm and policy

Contains network identifier, type of action, e.g., information
exchange, policy query, policy query response, controller delegation
request, controller delegation response
WINLAB
SAVANT: Radio Map
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
A fundamental research problem: How to best describe a
radio environment?
A pragmatic approach
Per-Transceiver Information
Frequency Domain Power Spectral Density Mask: Start-stop frequencies & corresponding
Tx power level
Time Domain
Avg. Duty Cycle | Scheduled/Random Access
Physical
Characteristics
X, Y, Z Coordinates | Outdoor/Indoor | Antenna Height | No. of
Antennas | Antenna Directionality
Receiver
Characteristics
Rx Sensitivity in dB |
Adaptation Logic
Freq. Change Algorithm | Rate Control Algorithm
Aggregate Information
Estimated aggregate interference power map: dBm v/s location & frequency table
Estimated spectrum occupancy ranking: Ordered list of most-free frequencies
WINLAB
SAVANT: Algorithms

Non-adaptive parameter selection (NAPS)

Explicit query-response only on initialization
 Intended for low-cost devices with simple radios
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Adaptive Parameter Selection (APS)
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Initialization procedure same as NAPS
 Additional periodic spectrum usage updates
provided by its radio neighbors
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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
SAVANT: Quantifying The Value of Cooperation
AP 4
AP 1
AP 2
AP 3
30
AP 4
20
AP 1
10
0
AP 2
AP 3
Throughput(Mbps)

ORBIT experiments show local observations are not enough
In all cases AP1 makes the same local observation but its
throughput widely varies based on how other nodes are
connected:
Throughput(Mbps)

AP 1 AP 2 AP 3 AP 4
30
20
10
0
AP 1 AP 2 AP 3 AP 4
AP 2
AP 3
AP 1
30
AP 2
20
10
0
AP 1 AP 2 AP 3 AP 4
AP 4
AP 3
Throughput(Mbps)
AP 1
Throughput(Mbps)
AP 4
30
20
10
0
AP 1 AP 2 AP 3 AP 4
WINLAB
SAVANT: Cooperative Association Control
Simulation study to find the potential gains from cooperation
for Wi-Fi client-AP association optimization problem (i.e.
given several APs in range, which one to connect to)
10 percentile client throughput
2
Mean client throughput
Throughput (Mbps)
0.6
Throughput (Mbps)

0.4
0.2
0
N=2 N=3 N=4
Least Distance
1.5
1
0.5
0
N=2 N=3 N=4
Intra-network Optim.
Cooperative Optim.
WINLAB
SAVANT: Cooperative Channel Assignment

Role of cooperation for Wi-Fi channel assignment
Dense Wi-Fi network simulations with realistic modeling of
the normalized throughput given 3 channels
Full Cooperation
Mean Normalized Throughput
No
Cooperation
1
0.8
0.6
0.4
50 APs/sq. km.
100 APs/sq. km.
150 APs/sq. km.
200 APs/sq. km.
0.2
0
0:100
25:75
50:50
75:25
50
Percentage of starved APs
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100:0
Ratio of Non-cooperative vs. Cooperative APs
50 APs/sq. km.
100 APs/sq. km.
150 APs/sq. km.
200 APs/sq. km.
40
30
20
10
0
-10
0:100
25:75
50:50
75:25
100:0
Ratio of Non-cooperative vs. Cooperative APs
WINLAB
SAVANT: Implementation
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Inter-network cooperation requires more than just a communication link
Needs integration with the way control plane is implemented in wireless
networks
We leverage Software Defined Networking (SDN) techniques for
introducing flexibility in the wireless control plane
Data Plane Apps
Mobility
Mgmt.
Wireless
Access
Control
QoS
Control
Control Plane Apps
Channel
Assignment
Tx
Power
Control
InterNetwork
Coordination
Network OS with wireless abstractions
Through extension
of OpenFlow
Match/Action Fields
Through the
ControlSwitch
framework
Wired + Wireless Network
WINLAB
SAVANT: ORBIT Two-Network Experiment
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Application: Load-dependent channel assignment
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Each client demands between 5-45 Mbps UDP uniformly
randomly, controllers need to select best channel
2 Networks with 4 APs/4 clients each, random topology
Controller A
ap.py
Wireless
Link
AP1
AP2
AP3
AP4
Cl1
Cl2
Cl3
Cl4
CSMA
Topology
ORBIT
Nodes
1
8
controller.py
Inter-network
Spectrum
Coordination
API
3
5
6
4
7
2
Cl5
Cl6
Cl7
Cl8
AP5
AP6
AP7
AP8
controller.py
ap.py
Controller B
WINLAB
SAVANT: ORBIT Two-Network Experiment
Results
•
Showing results for a particular topology
• Initially, each network sets the channels of its own APs
• At t=25 secs, Controller B provides information about AP loads
to Controller A and hands over control
• Controller A re-computes channels for all APs, conveys it to
APs which have to change
35
8
3
30
5
6
2
7
4
1
2
3
4
5
6
7
8
Load(Mbps
40 41 9 7 12 40 9 22
)
Initial Ch. 1 1 1 11 1 11 11 1
Throughput (Mbps)
1
1
1
1 11 11 11 11 11
6
2
25
20
15
8
1
5
10
3
7
4
5
0
Final Ch.
1
2
3
4
5
6
7
8
10
20
30
40
50
Time (seconds)WINLAB
60
Rechargeable Networks: Optimal Retransmission
Policies
PI: Roy Yates
Picture Courtesy of S. Roundy, UC Berkeley

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Energy replenishment rate is stochastic and environment-constrained
Rechargeable battery has a long life but its energy should not be abused
Message transmission carries different rewards
Our goal is to maximize the average reward rate by selective transmission .
WINLAB
Rechargeable Networks: Continuous-Time
Markov Model for Battery with Capacity N=5
Hybrid Energy Replenishment Modeled by Poisson Process
PI: Roy Yates
Battery replacement at rate α
Energy
Level
high
Battery
recharging
at rate β



 
low
0
λ 5,1
3
2
1
λ 5,2
λ 5,3
55
4
λ 5,4
λ 5,5

Characterizing a transmission policy by a set of state-dependent (energy and
capacity aware) thresholds {τ*N,i }, i=1, 2, … N

Determining “optimal” thresholds by invoking the “termination rule’’ of
Howard’s policy improvement algorithm
WINLAB
Network Coding: DE Framework for
Cross-layer Resource Allocation in RNC
PI: Narayan Mandayam
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Model RNC as a dynamical system:
Packet reception
rate
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Innovative packet
probability
Hyperarc capacity of

Tx rate at node i
Reception probability
(A pkt from i can be
recvd by at least 1 node
in K )
MAC
PHY
DE framework
closely models
rank evolution of
RNC
in terms of
PHY and MAC
parameters
Cross-layer Design problems
Solving systems differential
of equations
Appropriate boundary
conditions
WINLAB
26
Network Coding Aware
Power Control
PI: Narayan Mandayam
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Without Power Control (PC),
throughput is a constant
With PC： the instant
throughput is improved
compared with no PC case
With PC: throughput
Converges around t=60ms
Each node Tx at 1pkt/ms, min
cut between. src. and dst. is 1
pkt/ms
5
1
3
4
RNC with PC achieves
optimal throughput!
WINLAB
27
Bandwidth Exchange: Framework for Enhancing
Approach and Accomplishments
Performance of CR Networks  Proved
the convexity/concavity of the
optimization problem formulations
0
0
 Compared the performance of
bandwidth exchange with direct
transmission scenario
1
1
2
Direct transmission
2
Bandwidth exchanged based
cooperative forwarding
Technical Significance
 Use of transmission bandwidth as a flexible resource in cooperative forwarding
 Allows dynamic and opportunistic assignment of non-contiguous portions of spectrum to nodes
•
 Provided a distributed cooperative
pair selection algorithm using graph
theory
Alternate use in transmission time slot
exchange
 Implemented time exchange algorithm
in software defined radio (USRP2)
nodes of the ORBIT testbed.
In Progress:
 Joint resource allocation, scheduling
and routing in cognitive radio enabled
multi-hop wireless backhaul
Office of Naval Research Grant
PI: Narayan Mandayam
Impacts
 Trades off between –
• Throughput gain
• Power savings
• Coverage extension
WINLAB
Testbed Results of Time Exchange
PI: Narayan Mandayam
3
10m
0
9m
12m
17m
20m
5m
2
1
• Pick 4 USRP nodes of ORBIT
• 1,2 & 3 are users. Node 0 is the base station.
• Assign 1s orthogonal time slot to each node
• ORBIT is used as the global control plane
• Node 1 & 3 get selected as the optimal
cooperative pair through maximum
matching
• Node 1 & 3 cooperate and improve goodput
through proportional fair objective
• Node 2 transmits with the
same goodput
WINLAB
29
EDMAC: An Enhanced Directional MAC Protocol
for 60GHz Networks
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•
In 60GHz networks, transmitters and
receivers employ directional antennas
and point their main beams toward
each other to overcome high
propagation losses and achieve high
data rates
•
•
Problems can be solved if nodes do not employ exponential backoff
mechanism and use the same fixed contention window if they send to
the same receiver.
For a network with n senders and one receiver, from analysis we
obtain the channel throughput S
where
, Ttransmit, TRTS , Tdata are constant system
parameter and is the packet arrival rate of each node. The maximum
channel throughput is achieved when
Since we
, we can find the optimal contention window W is
only related with n
CSMA based directional MAC (DMAC) protocols suffer from the
“deafness” problem which causes unfairness and low channel utilization.
PI: Roy Yates
WINLAB
EDMAC: An Enhanced Directional MAC Protocol
for 60GHz Networks

Throughput model validation using ns-2
n=2
•
Performance evaluation using ns-2
Scenario 1: Two hops scenario: A UDP flow from node S to node D via
relay node R.
n=9
Scenario 2: Multi-hops scenario: A TCP or UDPflow from node S to node D via
EDMAC: Receiver calculates W based on number of senders n and inform its
multiple relay nodes
sender. Sender store W in its neighbor tables which guarantees nodes send to
the same receiver use same contention window size W
PI: Roy Yates
Example of a neighbor table
WINLAB
Study of Coexistence of Mobile-Fixed AP
Basic Idea
• Study of mobile WLAN hotspot which
provides cellular-WiFi tethering services to
personal devices.
Objectives of the study
• Heterogeneous traffic condition analysis
to model coexisting fixed and mobile
WLAN hotspot with saturated-unsaturated
traffic conditions due to limited backhaul
capacity at mobile WLAN
• Proposal of Adaptive Channel
Assignment (ACA) technique to mitigate
interference and increase the data
throughput at mobile APs.
• Study of effect of mobile speed to further
enhance throughput performance due to
ACA
Fig. Co-existence scenario of
fixed and mobile AP where a
user travelling with mobile
WLAN from point A to B can be
in the range of number of fixed
WLAN.
WINLAB
Coexistence of Mobile Access Points
Automatic Channel Assignment (ACA) algorithm: Mobile AP scans WiFi
channels every few seconds and selects the channel which is least
crowded in the carrier sense range
Fig. Throughput at mobile AP as
function of number of fixed APs
Note: With application of ACA,
maximum gain in throughput is 1.24
Mbps achieving up to 42% of
percentage throughput gain
Fig. Throughput at mobile AP (Mbps)
as a function ACA scanning period
when no. of fix AP = 50 and assuming
channel load is determined in total
time 200ms.
Note: Performance is evaluated for
mobility speed s = {10, 20, 40, 60} mph
WINLAB
Sensor-assisted anomaly detection for detecting
manipulation and exploitation
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Network Structure for Anomaly
Detection
 Primary (authorized) transmitter is
stationary
 Distributed detection by a network
of sensors that collaborate locally.
Significance Testing

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Test statistic T: a measure of observed
data
 Acceptance Region Ω: we accept the
null hypothesis if T Ω
 Significance level  : probability of false
alarm
When a channel is dedicated to a single
authorized user we can try to distinguish
between single and multiple transmissions
 Formulate a decision statistic that
captures the characteristics of the
received power in the normal case
[34]
[34]
WINLAB
PI: Wade Trappe
Detecting jamming against the collected system is
complicated by normal interference

Normal Interference in Mobile Networks
JamRX
Experiments have shown that the hidden
terminal problem remains in spite of MAClayer collision-avoidance (e.g. a transmitter
outside of the physical carrier sensing
range can still cause interference).
 It is equivalent to a low-power jamming
attack.

Other jamming attacks, such as reactive
attacks, require different detection
mechanism

Sender-oriented detection of jamming can utilize
network ACKs and signal levels to detect
jamming
AER-RSS signal space consists of three regions
 Interference-free: no hidden terminal
 Normal interference: caused by legitimate
hidden terminals
 Intentional interference: malicious jamming
[35]
[35]
ACK Missing Rate


PI: Wade Trappe
1
RandTX w/P
0.8
ReactTX w/P
RandTX
0.6
ReactTX
0.4
No Jam
0.2
0
0
0
0.5
0.5
ACK Block Rate
1 1
ACK Error Rate
WINLAB
Non-quantum photonic secret key establishment



Secret key establishment is
fundamental to supporting
cryptographic services
(confidentiality & authentication)
The photonic layer can be a rich
source for establishing keys
between two entities
 Quantum Cryptography is
the standard example, but
this poses serious
engineering challenges
 Can one optically establish
keys without resorting to
PI: Wade Trappe
quantum physics?
 Result:
Answer: Yes
– Alice and Bob create correlated sources,
while Eve is uncorrelated
 Prototype design using
large-scale Mach Zehnder
– Distillation and privacy amplification finalize
interferometer
the process, creating reliable crypto keys!
WINLAB
DARPA: RadioMAP Task 2, Management of RF Network
and Tasking Infrastructure (MARTI)
PI: Wade Trappe
Proposal Team: Applied Communication Sciences
WINLAB, Rutgers University
Carnegie Mellon University
Research Goals: A distributed system executing on
participating RF devices that performs reception,
transmission and local processing tasks on behalf of
RadioMap applications:
Without manual intervention
Subject to available resources and limited impact on
the primary mission of the device.
Software that intelligently assigns tasks to RF devices and
collects results on behalf of applications.
Trading off probability of success and overhead
Provides standardized mechanisms for tasking
Provides standardized reporting mechanisms and
formats
Modularity and Layering
Any RF device should be able to perform tasks for any
application without customizing
MARTI infrastructure
RF Devices,
Applications.
[37]
WINLAB
WINLAB is part of RCS3 (DARPA-SSPARC) team,
addressing S-band RADAR-Comms Interference
The RCS3 SSPARC Team is developing a
cognitive control system with multiple systemlevel and device-level spectrum separation
techniques to address Radar-Comms
interference:

Scalability through separating global
control from multiple local control systems,
with the environment partitioned
intelligently via RF propagation analysis
and geospatial reasoning,

Development and characterization of a
range of spectrum sharing techniques
leveraging closed-loop information sharing
between the radar and communications
systems,

High-level management of the cognitive
control system by a spectrum sharing
priority "dial" that can be used to rebalance
[38]
[38]
resources to meet evolving mission needs.
RF Coupling Map Map Understanding
Global Controller
Requested Map Information (Slow)
Information Sharing Subsystem
WINLAB
EARS: Collaborative Research: Big Bandwidth: Finding
Anomalous Needles in the Spectrum Haystack
PI: Wade Trappe
Potential Payoffs: Spectrum is a valuable resource that, if
properly used, will spur economic growth, but if used
improperly could hinder economic growth. The proposed
project, if successful, will have the following payoffs:
Provide mechanisms by which the government can
ensure spectrum is used properly by those who
have negotiated access rights.
Provide algorithms for mapping spectral activity
across a large time, frequency and spatial domain.
New algorithms and hardware will advance
knowledge in sampling ultra-wide bandwidth,
allowing for a comparison between state-of-the-art
in sub-Nyquist and RF photonics.
Impact education as the project is inherently multidisciplinary, and will lead to new curricular efforts
between security, wireless and photonics.
Proposal Title: EARS: Collaborative Research: Big
Bandwidth: Finding Anomalous Needles in the
Spectrum Haystack
Proposal Numbers: 1247864 & 1247298
PI Names: Wade Trappe (Rutgers)
Larry Greenstein (Rutgers)
Paul Prucnal (Princeton)
Research Goals: The goal behind the project is to develop a
suite of tools that can facilitate the detection of improper
usage of radio spectrum. To accomplish this, the project
involves the following research goals
Develop Algorithms and Hardware for a SingleScanner. The project explores how a single scanner:
Should allocate its scanning strategy to best
detect an unknown signal.
Develop sub-Nyquist techniques that allow
digital scanning of wide bandwidths
Develop RF photonic scanning that allows for
scanning of wide bandwidths
Develop Algorithms for Multiple-Scanners. Multiple
sensors allows for coordinated scanning. The project
will examine how scanning should be allocated
across sensors to detect anomalous transmissions.
Frequency
[39]
WINLAB
Pipsqueak and Owl Platform
PIs: Rich Martin, Rich Howard &
Yanyong Zhang
Owl Platform Software Stack




Scalable, distributed
software architecture

10+ year ultra-low
energy wireless
sensor
Reliable delivery in
challenging radio
environments
Multiple sensing
capabilities
IoT software stack
targeting data streams
from wireless sensors
WINLAB
TO – comparing wireless sensor boards
PIs: Rich Martin, Rich Howard &
Yanyong Zhang
Classic
Transmit-Only
TelosB (2004)
TO-PIP(2013)
Antenna
Radio
Micro controller
Battery
41
WINLAB
WINLAB and InPoint Systems
PIs: Rich Martin, Rich Howard &
Yanyong Zhang



Foundational research
enabled by access to
WINLAB faculty and staff
NSF I-Corps recipient
Interaction with other
university units



SBIR/STTR permit
exploration of
commercial opportunities
Start-up matures the
technology and Rutgers
receives upside
First customer received
delivery this week Rutgers Comparative
Medicine Resources
WINLAB
Owl Platform @ Rutgers CMR
PIs: Rich Martin, Rich Howard &
Yanyong Zhang





9-month installation
Improved staff
workflow
Reduced problem
response times
Supportive CMR
management and
faculty
Product
requirements
developed WINLAB
WiSER Cognitive Radio Platform
Focus on Creativity, not Engineering
Complexity :
Split Baseband in two domain spaces :
•
Dynamic – Swappable
INNOVATION CYCLE
•
Communication APPs (creative
problem)
Static - Open-sourced System-onChip (complex engineering problem)
Abstract lower level design
complexities from Users
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.
CRKIT = make real-time and widetuning radio a viable
solution for large scale
experiments.
Live system runs
Pis: Ivan Seskar, D. Raychaudhuri
WDR from Radio Technology Solutions
WINLAB
WiSER Programming Model
Network
CRKIT
HOST
CRKIT
development
Application
development
Java, C#
C
GUI
System
Debugging
C
Comm.
APP
Algorithm
System
Test
CR
DSA
VHDL/
Verilog
Mathworks
Simulink
Embedded
SW
IP
Networking
HW
Configuration
Host
CMD Parsing
DHCP/ARP
Lookup Tables/
RF
ETH/VITA
WINLAB
WiSER Baseline Hardware

Zynq-7000 SoC / Analog Devices Software-Defined Radio Kit
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)
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
SDN Wireless: OPEN BTS Concept
GENI Project – Open WiMAX BTS
 Exposed all controllable parameters through API
 Removed all default IP routing, simplified ASN controller*
 All switching purely based on MAC addresses
 Implemented the datapath virtualization and VNTS shaping
mechanism in click/openvswitch for slice isolation
Ongoing work – Open LTE BTS
 Exposed all controllable parameters through the same
REST based API
 Implemented the datapath with openvswitch
 Current development: ePC replacement with open source
aggregate manager (i.e. simplification/elimination of LTE
control protocols)
WINLAB
SDN Wireless: WiMAX Open BTS
eth0
eth0.vl1
eth0.vln
eth0.vl2
Traffic Scheduler/Shaper
eth2
RF Aggregate
Manager
OpenVSwitch
eth1
control
data
WINLAB
SDN Wireless: LTE Open BTS
eth2
eth0.vl1
RF/ePC Aggregate Manager
eth0.vl2
X2,S1-U,S1-MME,...
eth
WINLAB
SDN Wireless: Open BTS + network
SDN Datapah Complex
Adaptation/Handoff Controller
Generic Resource Controller
...
OPEN BS2
...
OPEN BS3
WINLAB
SDN Wireless: Open API
features








Radio Resource Management (RRM)
Set of MCS
ARQ/HARQ
Handoff
Admission Control
Frequency planning
Interference Management
Data Collection/Reporting…
WINLAB
SDN Wireless: Control Plane Concept


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
Data Plane Apps
Mobility
Mgmt.
Wireless
Access
Control
QoS
Control
Control Plane Apps
Channel
Assignment
Tx
Power
Control
InterNetwork
Coordination
Network OS with wireless abstractions
Through extension
of OpenFlow
Match/Action Fields
Wired + Wireless Network
Through the
ControlSwitch
framework
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
Controller
Insert Flow
Rules
BS
HW
Control
Messages
Local
Controller
Control
Datapath
Match Fields
Msg Type Parameters IP Port …
Action
Set
Channel
Forward to Port 1
Report
Beacons
Forward to IP1,IP2
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)
Shared State
Wireless
Controller
Wireless
Controller
Control
BS/AP Control Network (data
plane)
WINLAB
SDN Wireless: Hierarchical Control

Example: Pair of enterprises with heterogeneous
decomposed controllers
Authentication/Interference
Tier 2
AI
1
AI
1
Handoff
Tier 1
H1
H2
BS/AP Control Network
(data plane)
H1
H3
H2
BS/AP Control Network
(data plane)
WINLAB
Seeded by an NSF I-Corps grant
- Early stage incubation at WINLAB
ZipReel Inc.
Cloud video processing
INPUT: High volume,
pro-generated video
Pis: Kishore Ramachandran,
D. Raychaudhuri
OUTPUT: Fast delivery of highquality, multi-format processed video
“Processing”
Transcoding
Format conversion
Object search
Feature insertion
Networks
Delivery via
CDNs
Linear scaling with
compute units
Professional-grade
quality
Contact: [email protected]
Zipreel cloud transcoding applications
Netflix Encodes Every Movie 120 Different
Ways…streams to 900 different types of devices…
- gizmodo.com
Broadcasters (e.g. ESPN) + Cable/Telco operators
(e.g. Comcast) want to replicate tech. but
buy-rather-than-build approach
Critical for
Mobile /
Internet
streaming
2-3 days to generate 120 formats for one video!
- Netflix @ AWS Re-invent
Content owners lose significant ad-revenues for
each additional day of processing
Pain point: how to process high video volumes fast?
59
WINLAB
Zipreel Cloud Video Technology
Before
•
•
•
After
Approach: process videos on commodity clusters in software
Challenge: making the cluster interconnection network scale
Solution: hierarchical network topology design and/or efficient
use of multicasting
60
WINLAB
JUNO: Virtual Mobile Cloud Network (mVCN)
(..joint project with NICT under NSF-Japan collab)
Project concept: Dynamic Cloud Migration for Fast Response Real-Time Services
Key Technologies: Virtual Network built on MobilityFirst GUID Foundation, Cloud Migration
Strategies, etc.
WINLAB
JUNO: Virtual Mobile Cloud Network (mVCN)
(..joint project with NICT under NSF-Japan collab)
Technical Approach: MF service Addressability via GUID, anycast, virtual networks, ..
WINLAB
The Automotive Infoverse
PI: Marco Gruteser
Parking Availability
Estimation
Rangefinde
r
+ GPS
Wireless
Service
Valid Parking
Spot Map
MobiSys 2010
BestWINLAB
Paper
Development of a V2V Scalability
Simulator
PI: Marco Gruteser



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, interferencelimited scenarios.
WINLAB
Distinguishing Users with Capacitive
Communications
PI: Marco Gruteser

Need for better user
identification and
authentication
techniques on post-pc
devices
Approach: a wearable
token can transmit
short codes of data
through capacitive
touch screens
100
2 bits
3 bits
4 bits
5 bits
80
Detection Rate (%)

60
40
20
0
4 bits/s
5 bits/s
WINLAB
Visual MIMO Networks
Transmitter Array

PI: Marco Gruteser
Receiver Array
Explores MIMO free space
optical communications
with camera receivers
(e.g., download billboard
adds by pointing phone
camera at it)
WINLAB
Augmented Tags
PI: Marco Gruteser
WINLAB
Smart Meter Privacy and Security
PI: Marco Gruteser

Analyzed existing
meters with USRP
software radio


Meters broadcast every 30s
Able to spoof readings and
eavesdrop on hundreds of
meters
WINLAB
Reducing Driver Distraction



Phone driver
distraction
contributed to 995
fatalities in 2009
(NHTSA)
Goal: Make phone
aware of driver
use and design
interfaces that
reduce
distractions
Key challenge:
Distinguishing
driver and
passengers
PI: Marco Gruteser
• Idea: leverage car
speakers for audio
localization of cell phone
WINLAB
Mobile Safety Services



PI: Marco Gruteser
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
Elastic Pathing: Speed is
Enough to Track You
Ground Trut h
PI: Janne Lindqvist
Predict ed Pat h
Lat it ude
1 Mile
2 km
Longit ude
WINLAB
Crowdsourcing for
Privacy (w/CMU)

PI: Janne Lindqvist
Almost nobody reads
privacy policies
We want to install the app
 Reading policies not part of
main task
 Complexity of reading these
policies (boring!!!!!)
 Clear cost (my time) for unclear
benefit



Crowdsourcing can
mitigate these problems
But what to crowdsource
here?

Our idea: expectations and
misconceptions
95% users were surprised this app
sent their approximate location
to mobile ads providers.
95% users were surprised this app
sent their phone’s unique ID to
mobile ads providers.
90% users were surprised this app
sent their precise location to
mobile ads providers.
0% users were surprised this app
can control camera flashlight.
See all
WINLAB
Effective Location Privacy
Disclosures
PI: Janne Lindqvist
WINLAB
User-Generated Free-Form Gestures
for Authentication
PI: Janne Lindqvist




Measuring the
security and
memorability of usergenerated free-form
gestures
No visual reference
Multitouch: Single or
multiple fingers
To appear in
MobiSys’14
WINLAB
Password Security
PI: Janne Lindqvist
all passwords

How people generate
passwords and recall
them on different
devices?
Novel ways to
measure password
security.
75
Password strength/bits

recalled only
Type of metric
50
●
●
●
●
●
●
N−gram strength
Random entropy
NIST entropy
●
25
0
p
La
t
t
top hone able
top hone able
p
a
T
T
P
P
L
Terminal type
WINLAB
Local Community Crowdsourcing of
Physical-World Tasks with Myrmex

Approach:
Opportunistically
offering locationconstrained tasks to
people


PI: Janne Lindqvist
“Mechanical turk for the
real-world”
Results in:


Stronger communities
Everybody saves
WINLAB
Motivations and Experiences of the
On-Demand Mobile Workforce
PI: Janne Lindqvist


The main motivations for
joining on-demand mobile
workforce involve desires for
monetary compensation and
personal control over one’s
schedule and freedom to opt
into or out of tasks
Situational factors such as the
day of the week and weather
conditions influence worker’s
task selection practices.
Convenient physical locations
and unambiguous profile
information of task requesters
also influence task selection
practices as well.
WINLAB
MobilityFirst Update
FIA NP Projects Announced 5/14:
WINLAB
MobilityFirst Design: Architecture Features
Named devices, content,
and context
Strong authentication, privacy
11001101011100100…0011
Public Key Based
Global Identifier (GUID)
Human-readable
name
Heterogeneous
Wireless Access
Service API with
unicast, multi-homing,
mcast, anycast, content
query, etc.
Routers with Integrated
Storage & Computing
End-Point mobility
with multi-homing
In-network
content cache
Storage-aware
Intra-domain
routing
Edge-aware
Inter-domain
routing
Hop-by-hop
file transport
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
Connectionless Packet Switched Network
with hybrid name/address routing
Network Mobility &
Disconnected Mode
Ad-hoc p2p
mode
WINLAB
MF Design: Protocol Stack
App 1
App 2
App 3
App 4
E2E TP3
E2E TP4
Socket API
Name
Certification
& Assignment
Service
NCS
E2E TP1
E2E TP2
Optional Compute
Layer
Plug-In A
Global Name
Resolution
Service
GNRS
MF Routing
Control Protocol
GUID Service Layer
GSTAR Routing
MF Inter-Domain
Hop-by-Hop Block Transfer
Link Layer 1
(802.11)
Link Layer 2
(LTE)
Narrow Waist
Link Layer 3
(Ethernet)
IP
Switching
Option
Link Layer 4
(SONET)
Link Layer 5
(etc.)
Control Plane
Data Plane
WINLAB
MF Design: Name-Address Separation
 GUIDs

Separation of names (ID) from
network addresses (NA)
Globally unique name (GUID)
for network attached objects
Sue’s_mobile_2





User name, device ID, content, context,
AS name, and so on
Multiple domain-specific naming
services
Server_1234
John’s _laptop_1
Host
Naming
Service
Media File_ABC Taxis in NB
Sensor@XYZ
Sensor
Naming
Service
Content
Naming
Service
Context
Naming
Service
Globally Unique Flat Identifier (GUID)
Global Name Resolution Service
for GUID  NA mappings
Global Name Resolution Service
Network
Hybrid GUID/NA approach

Both name/address headers in PDU
 “Fast path” when NA is available
 GUID resolution, late binding option
Network address
Net1.local_ID
Net2.local_ID
WINLAB
MF Protocol Example: Mobility Service via
Name Resolution at Device End-Points
Service API capabilities:
- send (GUID, options, data)
Options = anycast, mcast, time, ..
- get (content_GUID, options)
Options = nearest, all, ..
Register “John Smith22’s devices” with NCS
Name Certification
Services (NCS)
GUID assigned
GUID lookup
from directory
NA99
MobilityFirst Network
(Data Plane)
Send (GUID = 11011..011, SID=01, data)
GNRS update
(after link-layer association)
NA32
GNRS
GUID <-> NA lookup
GNRS query
Send (GUID = 11011..011, SID=01, NA99, NA32, data)
GUID = 11011..011
Represents network
object with 2 devices
DATA
GUID
SID
NAs
Packet sent out by host
WINLAB
MF Protocol Design: Global Name
Resolution Service (GNRS)

Fast GNRS implementation based on DHT between routers

GNRS entries (GUID <-> NA) stored at Router Addr = hash(GUID)
 Results in distributed in-network directory with fast access (~100 ms)
Internet Scale Simulation Results
Using DIMES database
WINLAB
MF Protocol Design: Storage-Aware
Intra-Domain Routing (GSTAR)



Storage aware (CNF, generalized DTN) routing exploits in-network
storage to deal with varying link quality and disconnection
Routing algorithm adapts seamlessly adapts from switching (good
path) to store-and-forward (poor link BW/short disconnection) to
DTN (longer disconnections)
Storage has benefits for wired networks as well..
Temporary
Storage at
Router
Initial Routing Path
Low BW
cellular link
Re-routed path
For delivery
Mobile
Device
trajectory
PDU
Storage
Router
High BW
WiFi link
Sample CNF routing result
WINLAB
MF Protocol Design: Edge-Aware InterDomain Routing

MF architecture uses a new “edge-aware” inter-domain
routing protocol based on link-state and “pathlet” concepts


Telescopic link state protocol for dissemination of NSPs


Aggregation nodes (aNode) and virtual link(vLink)
NSP contains aNode, vLink state including AS internal topology and
aggregate edge network quality info; NSP update rate decreases with distance
“Late binding” from name-to-address at routers

Router has capability of rebinding <GUID=>Address> for packets in transit
1 NSP/sec
0.5 NSP/sec
0.1 NSP/sec
AS640
AS993
Alternate Path
AS541
vLink
AS009
aNode
Transit Network
AS virtual topology as
advertised by network
AS#, aNodes, vLinks, params..
NSP packet
Router decision based
On edge network path
Quality – late binding
AS90
Edge Network
Routed Path
For Multi-homing
Service
EIR Inter Domain Routing Concept
WINLAB
MF Protocol Design: Hybrid GUID/NA
Storage Router in MobilityFirst

Hybrid name-address based routing in MobilityFirst requires a new
router design with in-network storage and two lookup tables:



“Virtual DHT” table for GUID-to-NA lookup as needed
Conventional NA-to-port # forwarding table for “fast path”
Also, enhanced routing algorithm for store/forward decisions
GUID –based forwarding
(slow path)
GUID-Address Mapping – virtual DHT table
Look up GUID-NA table when:
- no NAs in pkt header
- encapsulated GUID
- delivery failure or expired NA entry
GUID
NA
11001..11
NA99,32
DATA
To NA11
Router
Storage
DATA
SID
GUID=
11001…11
NA99,NA32
To NA51
Store when:
- Poor short-term path quality
- Delivery failure, no NA entry
- GNRS query failure
- etc.
NA Forwarding Table – stored physically at router
Dest NA
Look up NA-next hop table when:
- pkt header includes NAs
- valid NA to next hop entry
Port #, Next Hop
NA99
Port 5, NA11
NA62
Port 5, NA11
Port 7, NA51
NA32
DATA
Network Address Based Forwarding
(fast path)
WINLAB
MF Protocol Example: Handling Disconnection
Store-and-forward mobility service example
DATA
GUID
NA99  rebind to NA75
Delivery failure at NA99 due to device mobility
Router stores & periodically checks GNRS binding
Deliver to new network NA75 when GNRS updates
NA99
Disconnection
interval
Data Plane
Device
mobility
NA75
DATA
DATA
GUID
NA75
GUID SID
NA99
DATA
GUID SID
Send data file to “John Smith22’s
laptop”, SID= 11 (unicast, mobile
delivery)
WINLAB
MF GNRS + Storage Routing Performance
Result for WiFi Mobility Scenario



Detailed NS3 Simulations to
compare MF with TCP/IP
Hotspot AP Deployment:
Includes gaps and overlaps
Cars move according to realistic
traces & request browsing type
traffic (req. size: 10KB to 5MB)
Single Car: Aggregate Throughput vs.Time
Empirical CDF of file transfer time
100
Total Data Received (MBits)
1
0.8
CDF
0.6
d: Average distance
between APs
0.4
MF: d = 200
TCP/IP: d = 200
MF: Avg. d = 400
TCP/IP: d = 400
0.2
0
0
10
20
30
40
50
File Transfer Time (sec)
60
70
80
60
TCP/IP-30miles/hr
TCP/IP-50miles/hr
TCP/IP-70miles/hr
MF-30miles/hr
MF-50miles/hr
MF-70miles/hr
40
20
0
0
50
100
Time (sec)
WINLAB150
200
LTE/WiFi HetNet Results: MF vs. TCP
MF provides several benefits in a heterogeneous wireless
environment:

Seamless mobility across network domains via dynamic GUID-NA bindings
 Routers automatically store packets in transit during periods of disconnection
 Simultaneous use of multiple networks is also possible
Aggregate Throughput with Time
1000
900
Aggregate Throughput (MBytes)

Throughput boost
due to
transmission of
stored packets
800
700
TCP takes more time to
re-start session (DHCP
+ Application reset)
600
500
400
300
200
MobilityFirst
TCP/IP
100
0
0
20
40
60
Time (sec)
80
100
120
WINLAB
MF Protocol Example: Dual Homing Service
Multihoming service example: LTE + WiFi or LTE + 60 Ghz or LTE1+LTE2
DATA
DATA
Router bifurcates PDU to NA99 & NA32
(no GUID resolution needed)
GUID
NetAddr= NA99
NA99
Data Plane
NA32
DATA
DATA
GUID
NetAddr= NA32
GUID= SID
11001…11 NA99,NA32
DATA
GUID SID
Send data file to “John Smith22’s
laptop”, SID= 129 (multihoming –
all interfaces)
WINLAB
MF Multi-Homing Example Result


Multipath service with data striping between LTE and WiFi
Using backpressure propagation and path quality info
GNRS Server
Query:
(GUIDY)
450
Data
Response:
(NA1,NA2,
Policy: Stripe)
GUIDY Data
Chunk
Chunk
Chunk
Ch u
nk
NA1
Sender: GUIDX
Backpressure
Ch
Net Addr Path Quality
NA1
4
NA2
36
un
k
Backpressure
Ch
Chunk
Chunk
un
NA2
k
Receiver:
GUIDY
File Transfer Completion Time (secs)
GUIDY NA1
use both WiFi and LTE
use only WiFi
use only LTE
400
350
300
250
200
150
100
50
0
5meters/s 10meters/s 20meters/s 30meters/s
Speed of Vehicle
Splitting
Logic
Multi-homing technique can also be combined
with Network Coding …
Data
1000
Aggregate Throughput (Mb)
GUIDY NA2
MobilityFirst Multihoming
Oracle Application
Using only LTE
Using only Wi-Fi
800
600
400
200
0
0
10
20
30
40
50
60
70
Time (sec)
WINLAB
80
90
100
MF Protocol Example: Enhanced CDN
Service Using Compute Layer Feature
Enhanced service example – content delivery with in-network caching & transcoding
GUID=13247..99
NA31
NA43
GUID=13247..99
MF Compute Layer
with Content Cache
Service plug-in
Filter on
SID=128
Content cache at mobile
Operator’s network – NA99
GUID=13247..99
NA99
GNRS query
Returns list:
NA99,31,22,43
NA29
GNRS
Query
GUID=13247..99
NA22
Content Owner’s
Server
Data fetch from
NA99
Content file
Mobile’s GUID
Data fetch from
NA43
Get (content_GUID,
SID=128 - cache service)
Get (content_GUID)
Query
User mobility
GUID=13247..99SID=128 (enhanced service)
WINLAB
MobilityFirst Prototyping: Phased Strategy
Phase 2
Phase 1
Content
Addressi
ng Stack
Context
Addressi
ng Stack
Phase 3
Host/Device
Addressing
Stack
Encoding/Certifying Layer
Global Name Resolution Service (GNRS)
Storage Aware
Routing
Locator-X Routing
(e.g., GUID-based)
Context-Aware /
Late-bind Routing
Prototype
Standalone Modules
Integrated MF Protocol Stack and Services
Evaluation
Simulation and Emulation
Smaller Scale Testbed
Deployable s/w pkg., box
Distributed Testbed
E.g. ‘Live’ on GENI
WINLAB
95
MF Host Protocol Stack
‘Socket’ API
open
send
send_to
recv
recv_from
close
App-1
App-2
Linux PC/laptop with WiMAX & WiFi
App-3
Context API
Network API
Context
Services
E2E Transport
GUID Services
Network Layer
Security
Sensors
Android device with WiMAX & WiFi
Routing
User policies
Interface Manager
‘Hop’ Link Transport
Early Dev.
WiFi
Integrate
WiMAX
Device: HTC Evo 4G, Android v2.3 (rooted), NDK
(C++ dev)
WINLAB
96
MF Click Software Router
Lightweight, scalable multicast
• GNRS for maintenance of
multicast memberships
• Heuristic approaches to
reduce network load, limit
duplicated buffering, and
improve aggregate delivery
delays
• Click prototype, with SID for
multicast flows
• Evaluating hail a cab
application as a example
multipoint delivery scenario
97
Multicast
Inter-Domain
(EIR)
WINLAB
MF Routing Prototype on ORBIT

Click-based prototyping of edge-aware inter-domain routing
(EIR) on Orbit nodes



Implementation on 200+ nodes on the grid
Routing protocol uses “aNode” concept to disseminate full topology
and aggregated edge network properties
Telescopic NSP (network state packet) advertisement for scalability
EIR Click router
RIB
OSPF w.
Telescoping
Link state advs
NSP
GNRSd
Binding request
SID 3
SID 2
SID 1
NextHop
Table
EIR forwarding engine
Data Packets
Data Packet
WINLAB
OpenFlow/SDN Implementation of MF




Protocol stack embedded within controller
Label switching, NA or GUID-based routing (incl. GNRS lookup)
Controllers interact with other controllers and network support
services such as GNRS
Flow rule is set up for the remaining packets in the chunk based on
Hop ID (which is inserted as a VLAN tag in all packets)
E.g., SRC MAC = 04:5e:3f:76:84:4a, VLAN = 101
=> OUT PORT = 16
MF Protocol Stack
WINLAB
99
MF Multi-Site Deployment on GENI
NL
R
Cambridge,
MA
Madison, WI Ann Arbor, MI
Lincoln, NE
Palo Alto, CA
N. Brunswick,
NJ
Salt Lake, UT
Tokyo, Japan
Los Angeles,
CA
I2
Atlanta, GA
MobilityFirst
Routing and Name
Resolution
Service Sites
MobilityFirst Access
Net
Clemson,
SC
Long-term (nonGENI)
Short-term
Wide Area ProtoGENI
ProtoGENI
WINLAB
Web Sites for More Information:
 WINLAB:
www.winlab.rutgers.edu
 ORBIT: www.orbit-lab.org
 MobilityFirst: http:
mobilityfirst.winlab.rutgers.edu
WINLAB
102