Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project FLoWS Overview and Update Andrea Goldsmith.
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Information Theory for Mobile Ad-Hoc Networks (ITMANET):
The FLoWS Project
FLoWS Overview and Update
Andrea Goldsmith
DARPA’s ITMANET Challenge
• Develop and exploit a more powerful information theory for mobile wireless networks. • Anticipated byproducts include new separation theorems to inform wireless network "layering" as well as new protocol ideas.
Hypothesis: A better understanding of MANET capacity limits will lead to better network design and deployment.
Limitations in theory of MANETs today
Wireless Information Theory Wireless Network Theory Optimization Theory
– Success on narrowly-defined information theory of wireless networks.
– Large body of wireless (and wired) network theory that is ad-hoc, lacks a basis in fundamentals, and lacks an objective success criteria.
– Little cross-disciplinary work spanning these fields, except applying optimization techniques to existing wireless network designs.
Our Approach: Consummating Unions Wireless Information Theory Wireless Network Theory Optimization Theory
• When capacity is not the only metric, a new theory is needed to deal with nonasymptopia (i.e. delay, random traffic) and application requirements – Shannon theory generally breaks down when delay, error, or user/traffic dynamics must be considered • Fundamental limits are needed outside asymptotic regimes • Optimization provides the missing link to address these issues
FLoWS Program Objectives
•
Develop tractable and insightful metrics and models for MANET information theory.
•
Define fundamental performance limits for MANETs in terms of desired objective metrics.
•
Obtain upper and lower performance bounds for these metrics for a given set of MANET models.
•
Define the negotiation between the application and network for resource allocation and performance optimization of our given metrics
•
Bound the cost of using our set of metrics as the interface between the network and applications.
MANET Metrics New Paradigms for Upper Bounds Layerless Dynamic Networks Application Metrics and Network Performance Capacity and Fundamental Limits Capacity Upper Bound Delay Lower Bound Energy Source Coding and Network Utility Capacity
(C*,D*,E*)
Delay
Utility=U(C,D,E)
Energy/SNR Fundamental Limits of Wireless Systems Application Metrics Constraints Models and Dynamics Degrees of Freedom Metrics Models New MANET Theory
Thrust Objectives and Rationale
•
Models and Metrics
(Leads: Effros and Goldsmith): –
Objective:
Develop a set of metrics for dynamic networks that capture requirements of current and future applications –
Rationale:
Models for MANETs are needed that are tractable yet lead to general design and performance insights • •
New Paradigms for Upper Bounds
(Leads: Koetter and Medard) –
Objective:
Obtain bounds on a diversity of objectively-defined metrics for complex interconnected systems.
–
Rationale:
A comprehensive theory for upper bounding the performance limits of MANETs will help guide design
Layerless Dynamic Networks
– – (Lead: Zheng)
Objective:
Design of networking strategies as a single dynamic probabilistic mapping, without pre-assigned layered structure
Rationale
Remove layering and statics from MANET theory. •
End-to-End Metrics and Performance
– (Leads:Ozdaglar and Shah)
Objective
: Provide an interface between application metrics and network performance –
Rationale:
A theory of generalized rate distortion, separation, and network optimization will improve application performance
Thrust Synergies and New Intellectual Tools
Thrust 1
New Bounding Techniques Code Construction Combinatorial Tools Optimization Dynamic Network IT
Thrust 3 Thrust 2
Structured Coding Optimization Stochastic Network Analysis Game Theory CSI, Feedback, and Robustness
Progress since December
• New breakthroughs in generalized capacity and separation, robust source and channel coding, equivalence classes, scaling laws, wireless NUM, cross-layer optimization, and distributed resource allocation. • New synergies within and between our thrust areas • New and ongoing collaborations among PIs • Overview paper for Scientific American – Co-authors: Effros, Goldsmith, Medard – Paper near completion, will be submitted next month • JSAC Tutorial on MANET Capacity with Cognitive Radios – Co-authors: Goldsmith, Jafar, Maric, and Srinivasa – Paper accepted for publication, to appear in 2009. • Website updated with Dec. PI meeting slides, recent publications, and recent results.
Thrust 0 Achievements
Models
Boyd, Effros, Goldsmith, Zheng
: Fading with/without CSI
Goldsmith:
Finite State Markov Dynamics
Boyd, Goldsmith, Ozdaglar, Johari:
General Network State Distributions
Shah:
Arbitrary node placement and traffic
Boyd, Effros, Goldsmith, Koetter, Ozdaglar, Shah:
General traffic models, including multicast traffic
Effros, Goldsmith:
Expectation and Outage in Capacity and Distortion
Goldsmith:
Diversity/multiplexing/delay tradeoffs
Coleman, Medard, Koetter, Effros, Goldsmith :
Capacity Regions
Boyd, Ozdaglar, Medard, Goldsmith:
End-to-end optimization metrics subject to specific constraints (e.g. delay)
Ozdaglar, Medard:
Downloading delay
Moulin:
Error-erasure tradeoffs
Zheng:
Error exponents
Zheng, Medard:
Distortion-diversity tradeoffs
Metrics
Thrust 1 Achievements
Zheng:
error exponents unequal error protection, embedded control messages to reduce overhead.
Effros, Koetter:
A characterization of the source coding region of networks for “line networks”
Koetter:
likelihood forwarding
Zheng, Medard:
New techniques to unify multiple
Code construction
description and multi-resolution, distortion-diversity
Koetter, Effros, Medard:
channels, Equivalence classes of networks based on emulation of a channel or a building block by arbitrary including multipoint channels
Network information theory New bounding techniques
Goldsmith:
Interference channel with cognitive user, “asymmetric” cooperation
Moulin:
covert channel by timing information
Goldsmith, Effros:
generalized capacity and source-channel coding
Goldsmith, Medard, Katabi:
analog network coding
Ozdaglar, Medard:
Cross-layer optimization under different metrics and constraints
Ozdaglar, Medard:
Network coding for downloading delay
Ozdaglar, Medard:
Rate allocation in multiple access networks
Medard, Koetter:
network coding capacity via conflict graphs
Networking and optimization Combinatorial Tools
Thrust 2 Achievements
Dynamic Network Information Theory Goldsmith:
general relaying, soft combining
Goldsmith:
Interference forwarding
Goldsmith:
Degraded FS Broadcast Channels
Coleman:
Rate Distortion of Poisson Processes
Goldsmith:
DMT for multi-hop networks
Zheng:
Euclidean Information Theory
Moulin:
Information flow via timing
Coleman:
“E-type” broadcasting channels
Goldsmith:
Feedback and Directed Information
Goldsmith: Moulin:
Error/erasure tradeoff for compound channel Cognitive users and interference
Medard, Zheng:
Diversity-distortion tradeoff
Coleman:
Joint Source/Channel Coding in Networks
Moulin:
Universal Decoding in MANETs
Zheng:
Message embedding in feedback channels
Effros, Goldsmith
: Generalized capacity, distortion, and joint source/channel coding .
Zheng:
Embedded Coding and UEP
CSI, feedback, and robustness Goldsmith:
Broadcasting with layered codes
Structured coding
Thrust 3 Achievements
Boyd:
Efficient methods for large scale network utility maximization
Goldsmith:
Layered broadcast source-channel coding
Medard, Shah:
Distributed functional compression
Boyd, Goldsmith:
Wireless network utility maximization (dynamic user metrics, random environments and adaptive modulation )
Ozdaglar:
Distributed optimization algorithms for general metrics and with quantized information
Shah:
Capacity region characterization through scaling for arbitrary node placement and arbitrary demand
Shah:
Low complexity throughput and delay efficient scheduling
Meyn:
Generalized Max-Weight policies with performance optim- distributed implementations
Optimization Theory
Distributed efficient algorithms for resource allocation
Medard, Ozdaglar:
different application delay metrics and block by-block coding schemes
Medard, Ozdaglar:
Efficient resource allocation in non-fading and fading MAC channels using optimization methods and rate-splitting
Goldsmith, Johari:
cognitive radio design with incomplete channel information
Johari: Ozdaglar:
Cross-Layer optimization for Game-theoretic model for Local dynamics for topology formation Competitive scheduling in collision channels with correlated channel states
Stochastic Network Analysis
Flow-based models and queuing dynamics
Game Theory
New resource allocation paradigm that focuses on hetereogeneity and competition
Focus Talks and Posters
•
Thrust 1:
– Koetter: A tool oriented approach to network capacity (joint with Effros and Medard) •
Thrust 2:
– Goldsmith: Interference in MANETs:
Friend or Foe?
•
Thrust 3:
– Shah: Capacity region of large wireless networks (joint with Neisen and Gupta)
• Posters on all new (green) results
Progress Criteria: Phase 1 (completed)
• Upper and lower bounds characterization of n(n-1) capacity region for small networks with simple assumptions –
Koetter, Effros, Medard:
Equivalence classes of networks based on ability of a channel or a building block to emulate arbitrary channels –
Goldsmith, Medard, Katabi:
Joint relaying, combine symbols in PHY, bits, or network layer • Scaling and achievability results for large networks with fixed traffic –
Shah:
Optimal capacity scaling for arbitrary node placement and arbitrary multi-commodity flows –
Shah:
multiple access decomposition for constructive scaling laws • Analysis of tractability vs. practicality of channel models and robustness to modeling assumptions and system uncertainty –
Meyn, Zheng, Medard:
mismatched receiver, online robust algorithm to combat imperfect channel info.
–
Goldsmith:
Broadcasting with layered source code, graceful degradation for weaker users • Joint characterization of trade-offs among delay, energy and capacity – – –
Medard, Zheng: diversity-distortion tradeoff Shah:
Low complexity throughput and delay efficient scheduling
Goldsmith, Boyd
: Capacity and delay under Wireless NUM
Progress Criteria: Phase 1 (completed)
• Study of optimized node cooperation incorporating not only virtual MIMO, cooperation diversity, conferencing, and relaying but also network coding for networks of 5-10 nodes. Includes impact of generalized decode-forward and amplify-forward (list decoding, partial decoding). Includes impact of delay, energy, and outage probability.
– –
Goldsmith:
MANET capacity w/ node cooperation and cognition
Koetter:
Likelihood forwarding • Study dynamic allocation of rate, power, and the spatial degrees of freedom associated with multiple antennas, as well as dynamic spectrum allocation –
Goldsmith, Johari:
Game-theoretic model for cognitive radio design with incomplete channel information –
Medard, Ozdaglar:
Efficient resource allocation in non-fading and fading MAC channels using optimization methods and rate-splitting • Study strengths and vulnerabilities posed by addressing jamming with cooperating and non-cooperating nodes –
Moulin, Medard
: On Manet jamming
Progress Criteria: Phase 1 (completed)
• Study fundamental limits of the ability of inside attackers to observe and contaminate degrees of freedom in a MANET –
Medard, Effros
: Byzantine’s attacks • Study systematic techniques for bounding the achievable rate region for distributed source coding in complex networks, considering issues of robustness to unknown/imperfect source and network statistics and application of universal coding and decoding techniques to such systems.
– –
Coleman:
Joint Source/Channel Coding in Networks
Effros/Koetter:
A characterization of the source coding region of networks for “line networks” • Study network-aware design; stability of network operation with respect to application-aware optimization will be studied. – –
Boyd:
Dynamic and stochastic network utility maximization with delivery constraints
Ozdaglar:
Distributed optimization algorithms for general metrics and with quantized information
Progress Criteria: Phase 2 (next 12 months)
– Evolve results in all thrust areas to examine more complex models, robustness/security, more challenging dynamics, and larger networks. • • • • • • • •
Koetter, Effros, Medard:
Network equivalence
Ozdaglar, Medard:
Rate allocation in multiple access networks
Goldsmith:
Multihop networks: Cooperation, Cognition, and Robustness Tradeoffs
Moulin:
Error/erasure tradeoff for compound channel
Zheng:
Message embedding in feedback channels
Coleman:
“E-type” broadcasting channels
Johari:
Local dynamics for topology formation
Meyn:
Generalized Max-Weight policies with performance-optimal distributed implementations •
Shah:
Capacity scaling laws for arbitrary node placement and arbitrary demand – Demonstrate synergies between thrust areas: compare and tighten upper bounds and achievability results for specific models and metrics; apply generalized theory of distortion and utility based on performance regions developed in Thrusts 1-2. • • • •
Ozdaglar, Medard:
Cross-layer optimization under different metrics
Zheng, Medard:
Unifying multiple description and multi-resolution, distortion-diversity
Boyd, Goldsmith:
Wireless NUM with cooperative PHY
Medard, Ozdaglar:
Cross-Layer optimization for different application delay metrics and block-by-block coding schemes •
Ozdaglar:
Competitive scheduling in collision channels with correlated channel states
Progress Criteria: Phase 2 (next 12 months)
– Demonstrate that key synergies between information theory, network theory, and optimization/control lead to at least an order of magnitude performance gain for key metrics. • • •
Ozdaglar, Medard:
Network coding for downloading delay
Goldsmith:
Generalized capacity, distortion, and separation
Boyd, Goldsmith:
Wireless network utility maximization – Pose clearly defined community challenges related to evolving our theory that inspires other researchers to collectively make breakthrough progress. • Community challenges posed in plenary talks and tutorials, as well as invited papers and vision papers – Publish 2 vision papers, one for the community (e.g. in the IEEE Wireless Communications Magazine) and one for the broader technical community (e.g. in Nature or Science) illuminating our ideas, results, and their potential impact • Draft paper for Scientific American near completion. To be submitted in Oct.
• Outline of community paper will be discussed in Friday team meeting
Project Impact To Date
• Plenary Talks and Panels – Boyd: Dysco’07, S. Stevun Lecture’08, CNLS’08, ETH’08 – Effros: ISIT’07 – Goldsmith: ACC’07, Gomachtech’08, ISWPC’08, Infocom’08, LTE Wshp’09 – Medard: Gretsi’07, CISS’07, NRC’07, IT Winter School’08 – Koetter: ITW’07, WiOPT’08 – Meyn: Erlang Centennial’09 • Recent Tutorials – Boyd: MOCCS’08, WOSP’08 – Ozdaglar: Networks' challenge: Where game theory meets network optimization (ISIT’08) – Medard/Koetter: Intro. to Network Coding (PIMRC’08) – Maric/Dabora: Cooperation in Wireless Networks (PIMRC’08) • Conference Session/Program Chair – ISIT’07 Technical Program (Chairs: Medard and Goldsmith) – CTW’08 session (Chairs: Andrews and Goldsmith) • Invited journal papers – “Breaking spectrum gridlock through cognitive radios: an information theoretic approach”, IEEE Proc’09 (w/ Jafar, Maric, and Srinivasa)
Publications to date
• 10 accepted journal papers, 10 more submitted • 80 conference papers (published or to appear) • Publications website: – http://www.stanford.edu/~adlakha/ITMANET/flows_publications.htm
Summary
• Significant progress on all thrust areas • Significant progress on synergies between thrust areas • Ongoing and fruitful collaborations between PIs • Roadmap towards meeting Phase 2 goals underway • Significant impact of FLoWS research on the broader research community (IT, communications, networking, and control/optimization)