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Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project

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.

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Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project

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  1. Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project FLoWSProgress and Next Steps Andrea Goldsmith Phase 3 Kickoff Sept. 14-15, 2009

  2. 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

  3. MANET Metrics Constraints Capacity and Fundamental Limits Capacity Layerless Dynamic Networks Delay Models and Dynamics Upper Bound New Paradigms for Upper Bounds Lower Bound Degrees of Freedom Power Application and Network Optimization Capacity Delay (C*,D*,E*) Utility=U(C,D,E) FLoWS Power Fundamental Limits of Wireless Systems Models New MANET Theory Application Metrics Metrics Application Metrics and Network Performance

  4. 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 • RationaleRemove 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

  5. 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

  6. Project Thrusts and Organization Metrics and Models Lead: Goldsmith and Effros All PIs Contribute New Paradigms for Upper Bounds Co-Leads: Effros and Medard Layerless Dynamic Networks Co-Leads: Zheng and Coleman App. Metrics and Network Performance Co-Leads: Ozdaglar and Shah — Cover — Effros — El Gamal —Goldsmith —Koetter — Medard — Moulin — Shah — Cover — El Gamal — Koetter —Goldsmith — Coleman — Effros — Goldsmith — Johari — Medard

  7. Thrust Synergies and New Intellectual Tools Thrust 1 Equivalence Classes Code Construction Combinatorial Tools Thrust 2 Dynamic Network IT Optimization Structured Coding Thrust 3 CSI, Feedback, and Robustness Stochastic Network Analysis Optimization Game Theory

  8. Open Questions circa 2006 • Capacity of time-varying links (with/without feedback) Yi-1 Xi Yi Tx Rx p(yi,si|xi,si-1) Si-1 Si D • Capacity of basic network building blocks • Capacity of large dynamic networks

  9. Progress on these questions • 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 Yi-1 Xi Yi Tx Rx p(yi,zi,si|xi,si-1) Si-1 Si D • 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)

  10. 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

  11. 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

  12. Thrust 0 Recent Achievements Models Coleman, Effros, Goldsmith, Medard, Zheng: Channels and Networks with Feedback Effros: networks with side information El Gamal: More than 3 users Cover: Coordinated Networks Moulin: Mobility Goldsmith: Cognitive Nodes Medard, Zheng: Distortion-Outage tradeoff Effros, Goldsmith: Expectation and Outage in Capacity and Distortion Zheng: UEP Goldsmith: Diversity/multiplexing/delay tradeoffs Medard: delay/energy minimization Medard: Stability Regions Shah: multicast capacity Metrics

  13. Thrust 1 Recent Achievements New bounding techniques Goldsmith: multi-way relay channel Goldsmith: multicasting with a relay Medard: effect of coding versus routing El Gamal: more than 3 users Code construction Network information theory Effros: continuity of network coding regions Goldsmith: joint source-channel coding with limited feedback Goldsmith: capacity and interference rates for the interference channel Effros: linear code construction Cover : Capacity of coordinated actions Zheng, Medard : distortion-outage tradeoff Metrics Koetter, Medard: On the stability region of networks with instantaneous decoding Combinatorial Tools Networking and optimization

  14. Thrust 2 Recent Achievements Dynamic Network Information Theory El Gamal: BC with 3+ receivers Goldsmith: Multicast with relay; BC with cognitive relay Moulin: exploiting mobility of relay networks Effros: distributed network coding with coded side information Cover: coordination capacity Effros: linear representation of network coding Medard, Zheng: Diversity-distortion tradeoff Coleman: Control principle for feedback channels Goldsmith: Joint source channel coding / outage Zheng: tilted matching for feedback channels Effros: two stage polar codes CSI, feedback, and robustness Structured coding

  15. Thrust 3 Recent Achievements Optimization Distributed and dynamic algorithms for resource allocation Boyd, Goldsmith: Wireless network utility maximization as a stochastic optimal control problem Ozdaglar: Distributed second order methods for network optimization El Gamal: Overhead in distributed algorithms Medard: Decoding and network scheduling for increased capacity Shah: Distributed MAC using queue based feedback Ozdaglar: Noncooperativepower control using potential games Johari: Large network games Ozdaglar: Near potential games for network analysis Meyn: Q-learning for network optimization Johari: Supermodular games Effros: Noncooperative network coding Game Theory New resource allocation paradigm that focuses on hetereogeneity and competition Stochastic Network Analysis Flow-based models and queuing dynamics

  16. 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.

  17. 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

  18. Progress Criteria: Phase 3 • 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. • 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. • 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 • 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

  19. 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.

  20. 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

  21. 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

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