information theory for mobile ad-hoc networks (itmanet): the flows project
DESCRIPTION
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project. FLoWS Progress and Next Steps Andrea Goldsmith. Phase 3 Kickoff Sept. 14-15, 2009. FLoWS Challenge, Progress, and Goals. Develop and exploit a more powerful information theory for mobile wireless networks. - PowerPoint PPT PresentationTRANSCRIPT
Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project
FLoWS Progress and Next Steps
Andrea Goldsmith
Phase 3 KickoffSept. 14-15, 2009
FLoWS Challenge, Progress, and Goals
• Develop and exploit a more powerful information theory for mobile wireless networks.
• The development of this theory has progressed along three main thrust areas, with breakthrough progress and new theory in each area.
• Synergies between thrust areas have emerged, which are blurring the lines between thrusts.
• In Phases 3-4 our goal is to identify and attack the largest outstanding ITMANET challenges
Capacity Delay
Power
Upper Bound
Lower Bound
Capacity and Fundamental Limits
Application Metrics
Capacity
Delay
Power
Utility=U(C,D,E)
Application andNetwork Optimization
(C*,D*,E*)
Constraints
Degrees ofFreedom
Models andDynamics
Application Metrics and
Network Performance
LayerlessDynamic Networks
New Paradigmsfor Upper
Bounds
Models
New MANET Theory
MANET Metrics
Metrics
Fundamental Limitsof Wireless Systems
Thrust Objectives and Rationale• Models and Metrics (Leads: Effros,Goldsmith,Medard):
– 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: Effros,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, Coleman)– 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,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
Two New PIs Added to FLoWS
• Cover and El Gamal have been added for the last two phases to complement the existing team
• Cover’s work will focus on – Coordinated capacity: How much dependence can be set up
with a given set of communication constraints– Applications include distributed game theory, task assignment
and rate distortion theory.
• El Gamal’s work will focus on – Network information theory to develop new coding schemes
for the canonical channel models with many users– Computing/decision making over a network with distributed
sources: lossy distributed averaging
Metrics and ModelsLead: Goldsmith and Effros
All PIs Contribute
Project Thrusts and Organization
New Paradigmsfor Upper Bounds
Co-Leads: Effros and Medard
— Cover— El Gamal— Koetter— Goldsmith
LayerlessDynamic Networks
Co-Leads: Zheng and Coleman
— Cover— Effros— El Gamal— Goldsmith— Koetter— Medard— Moulin— Shah
App. Metrics andNetwork Performance
Co-Leads: Ozdaglar and Shah
— Coleman— Effros— Goldsmith— Johari — Medard
StructuredCoding
Thrust Synergies and New Intellectual Tools
EquivalenceClasses
Optimization
Code Construction
Combinatorial Tools
DynamicNetwork IT
Thrust 1
Thrust 2
Game Theory
Thrust 3
Optimization
StochasticNetworkAnalysis
CSI, Feedback,and Robustness
Open Questions circa 2006
• Capacity of large dynamic networks
• Capacity of basic network building blocks
Xi
Yi-1
p(yi,si|xi,si-1)
Si-1 Si D
YiTx Rx
• Capacity of time-varying links (with/without feedback)
Progress on these questions
Xi
Yi-1
p(yi,zi,si|xi,si-1)
Si-1 Si D
YiTx Rx
• Capacity of time-varying links (with/without feedback)
• Capacity of finite-state Markov channels with feedback• Converses under unequal error protection• Multiplexing-diversity-delay-distortion tradeoffs in MIMO • Generalized capacity and separation
• Capacity of basic network building blocks
• Capacity region/bounds for Z channel and interference channels• Capacity bounds for cognitive interference/MIMO channels• Upper bounds and converses for interference channels with a
relay (via interference and message forwarding)
• Capacity of dynamic networks
• Network equivalence• Scaling laws for arbitrary node placement and demand• Multicast capacity• Effect of feedback and side information• Dynamic/multiperiod network utility maximization• Generalized Max-Weight policies• Game-theoretic approaches• Mobility for interference mitigation• Delay or energy minimization• Distributed optimization
New Theory• Thrust 1
– Equivalence classes
• Thrust 2– Layered and structured codes– Control principles for feedback channels– Generalized capacity and separation
• Thrust 3– Stochastic Multi-period Network Utility Maximization– Relaxation and distributed techniques for network optimization– Stochastic games
• Interthrust– Relaying, cooperation and cognition– Network coding– Capacity regions for more than 3 users– Coordination capacity
Thrust 0 Recent Achievements
Metrics
Effros, Goldsmith: Expectation and Outage in Capacity and Distortion
Models
Goldsmith: Diversity/multiplexing/delay tradeoffs
Effros: networks with side information
Shah: multicast capacity
Moulin: Mobility
Medard: delay/energy minimization
Zheng: UEP
Medard, Zheng: Distortion-Outage tradeoff
Coleman, Effros, Goldsmith, Medard, Zheng: Channels and Networks with Feedback
Goldsmith: Cognitive Nodes
Cover: Coordinated Networks
Medard: Stability Regions
El Gamal: More than 3 users
New bounding techniques
Thrust 1 Recent Achievements
Code constructionNetwork information theory
Networkingand optimization
Combinatorial Tools
MetricsKoetter, Medard: On the stability region of networks with instantaneous decoding
Goldsmith: multicasting with a relay
Effros: linear code construction
Effros: continuity of network coding regions
Zheng, Medard : distortion-outage tradeoff
Medard: effect of coding versus routing
Goldsmith: capacity and interference rates for the interference channel
Goldsmith: multi-way relay channel
Goldsmith: joint source-channel coding with limited feedback
Cover : Capacity of coordinated actions
El Gamal: more than 3 users
Dynamic Network Information Theory
CSI, feedback, and robustness Structured coding
Thrust 2 Recent Achievements
Effros: two stage polar codes
Coleman: Control principle for feedback channels
Zheng: tilted matching for feedback channels
Medard, Zheng: Diversity-distortion tradeoff
Goldsmith: Joint source channel coding / outage
Effros: linear representation of network coding
Cover: coordination capacity
El Gamal: BC with 3+ receivers
Effros: distributed network coding with coded side information
Goldsmith: Multicast with relay; BC with cognitive relay
Moulin: exploiting mobility of relay networks
Thrust 3 Recent Achievements
Shah: Distributed MAC using queue based feedback
Johari: Large network games
Meyn: Q-learning for network optimization
Boyd, Goldsmith: Wireless network utility maximization as a stochastic optimal control problem
OptimizationDistributed and dynamic
algorithms for resource allocation
Stochastic Network AnalysisFlow-based models and
queuing dynamics
Game TheoryNew resource allocation paradigm that focuses on
hetereogeneity and competition
Ozdaglar: Distributed second order methods for network optimization
Ozdaglar: Noncooperative power control using potential games
Effros: Noncooperative network coding
Medard: Decoding and network scheduling for increased capacity
Ozdaglar: Near potential games for network analysis
Johari: Supermodular games
El Gamal: Overhead in distributed algorithms
FLoWS progress since March• New breakthroughs in upper bounds, feedback and CSI,
cognitive techniques, interference forwarding, multicast traffic, and dynamic/distributed network optimization,
• New synergies within and between our thrust areas
• New/ongoing collaborations among PIs within FLoWS and with Nequit PIs; integration of new PIs Cover and El Gamal
• Overview paper for Scientific American to appear– Co-authors: Effros, Goldsmith, Medard
• Comm. Magazine paper with overview of FLoWS– Submitted and reviewed; likely to be accepted after revision
• Discussion of Phase 3 and 4 progress criteria– Identification of main challenges
• Website updated with March PI meeting slides, recent publications, and recent results.
Focus Talks and Posters
• Thrusts 1 and 2:– El-Gamal: More than Three Users – Cover: Coordination Capacity
• Thrust 2:– Zheng: Tilted Matching for Feedback Channels
• Thrust 3:– Ozdaglar: Near-Optimal Power Control in Wireless
Networks: A Potential Game Approach
• Posters on all recent achievements
Progress Criteria: Phase 31. Revolutionize upper bounding techniques through new and different
approaches that go beyond the classical MIN-CUT bounds and Fano's inequality that have dominated capacity bounds for the last several decades.
2. Determine the optimal channel/network “coding” that achieves these capacity upper bounds when possible, and characterize for which classes of networks gaps still exist between achievability & upper bounds, & why.
3. Develop a generalized theory of rate distortion and network utilization as an optimal and adaptive interface between networks and applications that results in maximum performance regions
4. Demonstrate the consummated union between information theory, networks, and control; and why all three are necessary ingredients in this union
• Progress towards meeting each criteria (more details in Thrust talks)• Identifying “grand challenges” remaining to develop an IT for MANETS
• First pass will be presented in the thrust talks• Will focus on these challenges during Phases 3 and 4• Team meeting Tuesday dedicated to this topic
Project Impact To Date• Recent Plenary Talks
– Boyd: Stevun Lec.’08, CNLS’08, ETH’08, ISACCP’09, ISMP’09, ICOCA’09, CCCSP’09– Goldsmith: Gomachtech’08, ISWPC’08, Infocom’08, RAWC’09, WCNC’09, ICCCN’09– Medard: IT Winter School’08, UIUC Student Conference’08, Wireless Network
Coding’08, ITC.09, ITW’09– Meyn: Erlang Centennial’09, Yale Workshop’09, Diaconis Symp.’09– Ozdaglar: ACC 2009, NecSys'09 , ASMD’08– Johari: World Congress of the Game Theory Society’08– El-Gamal: Allerton’09, Padovani Lecture’09, Brice Lecture’09 – Shah: Net Coop’09, Winedale’09
• Conference Session/Program Chairs/Panels– CTW’09, ITW’09, ISMP’09, INFORMS’09, ITW’10, CTW’10
• Recent Tutorials– Meyn: Mathematics of OR’09, – Shah: CDC’09,
• Invited/award winning journal papers– “Breaking spectrum gridlock through cognitive radios: an information-theoretic
approach”, Goldsmith, Jafar, Maric, Srinivasa, IEEE Proc’09.– “A Random Linear Network Coding Approach to Multicast”, Ho , Medard , Koetter,
Karger, Effros, Shi, and Leong, Joint IT/Comsoc Paper Award 2009.– "XORs in the Air: Practical Wireless Network Coding“, Katti, Rahul, Hu, Katabi, Medard,
and Crowcroft. Bennett Prize in Communications Networking 2009.
Publications to date
• 22 accepted journal papers, 16 more submitted• 127 conference papers (published or to appear)• SciAM paper to appear• Comm. Magazine paper submitted and reviewed• Book on FLoWS vision and results under development
– Alternative to NoW Foundations and Trends article
• Publications website:– http://www.stanford.edu/~adlakha/ITMANET/flows_publications.htm
Summary
• Significant progress in and across all thrust areas• Ongoing and fruitful collaborations between PIs• Powerful new theory has been developed that goes
beyond traditional Information Theory and Networking• Addition of El Gamal and Cover adds new perspective
and experience to our team• Significant impact of FLoWS research on the broader
research community (IT, communications, networking, and control/optimization)
• Want to maximize research impact in the final two phases of the project by identifying key challenges within and beyond the progress criteria