wmpg workshop august, 2005 whynet: scalable testbed for next-generation mobile wireless networking...
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WMPG Workshop
August , 2005
WHYNET: Scalable Testbed for Next-Generation Mobile Wireless Networking Technologies
R. Bagrodia, E. Belding-Royer, B. Daneshrad, M. Fitz, M. Gerla, S. Krishnamurthy, R. Bagrodia, E. Belding-Royer, B. Daneshrad, M. Fitz, M. Gerla, S. Krishnamurthy, U. Mitra, P. Mohapatra, M. Molle, R. Rao, C. Shen, M. Srivastava, M. TakaiU. Mitra, P. Mohapatra, M. Molle, R. Rao, C. Shen, M. Srivastava, M. Takai
Rajive BagrodiaUCLA Computer Science Department
WMPG Workshop
August , 2005
Future Wireless Networks: Trends & Challenges
• Growing demand for mobile access, but wireless capacity limited– Departure from traditional layering approach to cross-layer design
approaches (e.g., information sharing, joint design)
– Exploiting wireless link flexibility by dynamic selection of transmission parameters (e.g., power, channel, modulation)
• Convergence and interoperability of heterogeneous systems with diverse radio technologies (e.g., 3G, 4G, WLAN, UWB)– Multi-interface/multi-mode/programmable radio devices
• Self-organizing wireless networks to extend coverage, reduce costs, potentially also improve performance (e.g., mesh networks; ad-hoc access networks)
• Embedded networked sensing and its applications• Security issues
WMPG Workshop
August , 2005
Implication for Networked Systems
• The next generation wireless communication technology being developed for this purpose will be adaptive (software-defined radios, smart antennas, programmable networks, …)
• There is substantial ‘cross-layer interaction’ among the technology solutions at multiple layers of the protocol stack (e.g., medium access, routing, and transport) to provision dynamic Quality of Service among the voice, video, and data traffics that must be carried by such networks
• There is limited experience, in the commercial or military arena, with large scale deployments and use of such on-the-move communication technology
• Static analysis and planning may not be adequate to achieve the dynamically varying Quality of Service requirements for the diverse applications
• Real-time network simulations/emulations can play a critical role in assessing the dynamic impact of net-centricity in the design and operation of such networks
WMPG Workshop
August , 2005
WHYNET: Thesis
• Cross-layer interactions between radios, antenna, protocols and applications is key to exploiting next generation wireless technologies.
• A hybrid testbed that exploit advantages of physical and simulation testbeds to study such intercations and their impact on application-level performance
• Testbed must be accurate, efficient and scalable:– Accuracy: permit phy, radio, MAC, & networking attributes to be reflected in
a common setting– Efficiency: real-time evaluation of models with tens of nodes. – Scalability: evaluation of wireless networks with thousands of devices
• Demonstrate the unique contributions of WHYNET for cross-layer optimization studies
• Generate a repository of wireless networking scenarios, measurements, models and implementations
• Make testbed accessible to the research community via the web
WMPG Workshop
August , 2005
Potential Impact
• Cross layer interaction– Effective use of new radio technologies at higher layers
• Example: IEEE 802.11a (fastest on the market)– Highest PHY rate: 54 Mbps, above MAC: less than 30 Mbps
– With RTS/CTS: less than 24 Mbps even under no contention
IEEE 802.11a without RTS/CTS (1472 byte packets)
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6 12 18 24 30 36 42 48 54Physical Layer Data Rate [Mbps]
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Theoretical
Intel (BSS)
QualNet
IEEE 802.11a with RTS/CTS (1472 byte packets)
0
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6 12 18 24 30 36 42 48 54Physical Layer Data Rate [Mbps]
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hp
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[Mb
ps]
Theoretical
Intel (BSS)
QualNet
WMPG Workshop
August , 2005
Adequate feedback from PHY is one of the key requirements to success
Cross Layer Interaction
Application
Middleware Service
Network
MAC
PHY Cro
ss L
ayerOthers
(802.11b…)SDRs
Smart Antenna(SISO/MIMO)
UWB
Transport
PDA application with intermittent connectivity…
Location service…
Wireless aware TCP…
Multi-path routing…
Power conservation…
WMPG Workshop
August , 2005
WHYNET Approach: Hybrid Testbed
A hybrid testbed for heterogeneous, wireless networking • Heterogeneity in wireless technologies: MANET, wireless LAN, 3G
cellular, sensors, narrowband, wideband, UWB, …• Hybrid testbed
– Combines realism of physical testing with scalability, flexibility and repeatability of simulations (Zhou et al TOMACS, April 2004)
– Smooth transition from design to deployment
Distributed Simulation Testbed
Sensor Networks
Next GenerationRadio Networks
MANETs
WLANs
WMPG Workshop
August , 2005
Distributed Simulation Testbed
Sensor Networks
Next GenerationRadio Networks
MANETs
WLANs
SyntheticApplicationsSynthetic
Applications
VideoConferencing
MAC
AbstractPHY
Routing
Queuing
MAC
High FidelityPHY
MAC
MeasurementBased PHY
MAC
UWB PHY
MACMAC
AbstractPHY
MAC
High FidelityPHY
MAC
MeasurementBased PHY
MAC
PHY
MIMO SISO
MAC
PHY
MIMO SISO
VideoConferencing
VoIPVoIP
UWB PHY
HTTPHTTP
StreamingStreaming
• Domain Policies• Node Capabilities• Service Discovery• User/Node Auth.• Roaming/Location Mgmt
Routing
Queuing
Routing
Queuing
• Domain Policies• Node Capabilities• Service Discovery• User/Node Auth.• Roaming/Location Mgmt
Routing
Queuing
Real Component
Virtual Component
WHYNET Testbed
• Flexible & realistic evaluation framework
• Smooth transition from system design to deployment
SimulationRepeatability,
controllability, scalability
PhysicalRealism
EmulationReal applications &network protocols
Hybrid Testbed Case Studies: Overview
• XCP performance in wireless networks Collaboration between UCLA and HRL Labs
• Adaptive video streaming performance in ad hoc networks
• Using SCTP for transport layer Internet host mobility support Collaboration between UCLA and Univ. of Delaware
• Bandwidth aggregation on multi-homed wireless hosts in inter-working cellular and mesh networks Collaboration between UCLA and UCSD
• Evaluation of a distributed fairness algorithm (IFA) for mesh networks in presence of real and diverse set of applications
Adaptive Video Streaming Performance in Ad Hoc Networks
• Evaluate adaptive video streaming performance in presence of channel fading, congestion and node mobility in ad hoc networks
• Use QStream as a representative adaptive media application Optimizes two quantitative measures of video quality along
temporal and spatial dimensions Relies on TCP for rate control and drops low priority data during
congestion to maintain video quality and timeliness
Adaptive Video Streaming Performance in Ad Hoc Networks
• Hybrid testbed usage – emulated wireless hosts running QStream communicating with each other over a simulated ad hoc network
• Observed complete lack of correlation between perceptual and quantitative metrics, especially with node mobility
sQualnet Simulation Framework
• Scalable framework as extension to Qualnet
• Rich set of sensor network specific models Sensing and radio channels, MAC (S-MAC, T-MAC) and routing
(diffusion, DTN, tree) protocol Battery and power consumption models
• Formal release of version 1.0
• Adoption by growing user base UCLA projects: SOS Dynamic Sensor OS,
Ragobot, Ad hoc Distributed Control Systems (ADCS), and Helimote Energy Harvesting Aware Sensor Nets
External academic users: UCSB, USC, University of Bristol, University of Missouri-Rolla, Iowa State, Nanjing University, City University of Hong Long…
Industry users: SDRC, Boeing, HRL
Functional Model
Sensor Node
Hardware Model
Battery Model
Radio
CPU
ADC(Sensor)
Wireless Channel
Sensor Channel
Network Stack
Sensor Stack
Application
TransducerActuator
Joint work with Mani Srivastava
Hybrid sQualnet Capabilities
• Modeling of multitiered heterogeneous sensor networks Field of motes (non-IP) with
backbone of microservers (IP)
• Real-code emulation for motes Run unmodified SOS and TinyOS
code for motes in sQualnet Makes larger set of protocols
available, reduces debugging effort
• (in progress) Hybrid simulation: mix of simulated and real nodes Wireless channel emulation, sensor
channel emulation, actuator emulation and application emulation,
Impact of (Real) Traffic Model
• MANET traffic model (CBR) AODV and DSR perform equally well
• Sensor Network traffic model DSR performs 500 times better than
AODV
• Lesson: Routing protocol performance is highly dependent on traffic model.
• Simulation: 1K nodes, 256B pkt, 1 pkt/sec for 15 min.
To summarize: High sensitivity of predicted network performance on traffic distributions.
Testbed Challenges
• Scalability Provide use-sensitive projections: 1K MANET vs 10K node sensor
networks vs 1M node mixed network vs … Study layer-specific protocols vs. cross-layer effects
• Application-centricity Shift focus from protocol & device performance to impact on
end-end application (middleware) performance Impact on simultaneous support for multiple applications with
diverse QoS requirements
• InteroperabilityCost, robustness, efficiency … of dynamic switching among networks