2. Information Theory for Mobile Ad-Hoc Networks (ITMANET): The FLoWS Project FLoWS Overview and Progress Andrea Goldsmith

3. 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.

4. MANET Capacity: What we don’t know Capacity of large dynamic networks Capacity of basic network building blocks XiXi Y i-1 p(y i,s i |x i,s i-1 ) S i-1 SiSi D YiYi Tx Rx Capacity of time-varying links (with/without feedback)

5. Shannon and Wireless Networks Shannon’s capacity definition based on infinite delay and asymptotically small error was brilliant Much progress in finding the Shannon capacity limits of wireless single and multiuser channels Little known about these limits for mobile wireless networks, even for simple (canonical) models –Few fundamental design insights have emerged. –Queuing and capacity theory incompatible if capacity implies infinite delay and no error. –How should capacity be defined for wireless networks?

6. Limitations in theory of MANETs today –Shannon capacity pessimistic for wireless channels and intractable for large networks Wireless Information Theory Optimization Theory B. Hajek and A. Ephremides, “Information theory and communications networks: An unconsummated union,” IEEE Trans. Inf. Theory, Oct. 1998. Wireless Network Theory –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 –Optimization techniques applied to given network models, which rarely take into account fundamental network capacity or dynamics

7. Our Approach: Consummating Unions 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 Wireless Information Theory Wireless Network Theory Optimization Theory Menage a Trois

8. 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.

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

10. 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,Koetter,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,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

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

12. 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: Diversity-distortion tradeoff Coleman, Effros, Goldsmith, Medard, Zheng: Channels and Networks with Feedback Goldsmith: Cognitive Nodes

13. New bounding techniques Thrust 1 Recent Achievements Code construction Network information theory Networking and Optimization Combinatorial Tools Medard: coded time-division duplex for delay or energy minimization Goldsmith: multiple sender interference channel Moulin: converse for Gelfand-Pinsker MAC Effros: networks with side information Effros: effect of feedback in networks Shah: multicast capacity of large wireless networks Koetter, Medard: joint coding and scheduling in wireless networks Zheng: unequal error protection converse Moulin: mobility for interference mitigation Effros: game-theoretic approaches to network coding Koetter, Medard: Distributed scheduling for network coded multicast

14. Dynamic Network Information Theory CSI, feedback, and robustness Structured coding Thrust 2 Recent Achievements Goldsmith: cognitive interference/Z channel Goldsmith: Interference Forwarding Goldsmith: MIMO cognitive network Goldsmith: Finite State (BC) channels with Feedback Medard, Zheng: Diversity-distortion tradeoff Zheng: UEP and applications Effros: Network coding and distributed Source coding Medard: Network coding with FB in TDD Effros: Contents Feedback for Network Coding Zheng: Message-wise UEP and Feedback Coleman: Control Principle for feedback designs Moulin: Mobility to mitigate interference Shah: Scaling of heterogeneous networks Medard Koetter: Hypergraph scheduling Goldsmith: MIMO-ARQ Diversity/Multiplexing/Delay

15. Thrust 3 Recent Achievements Shah, Medard: Queueing analysis for coded networks with feedback Johari: Fluid limits for gossip Meyn: Relaxation techniques for network optimization Goldsmith, Johari: Oblivious equilibrium for stochastic games with concave utility Boyd, Goldsmith: Wireless network utility maximization as stochastic optimal control Optimization Stochastic Network Analysis Game Theory Ozdaglar: Distributed second order methods for network optimization Ozdaglar: Noncooperative scheduling with correlated channel states Effros: Noncooperative network coding Moulin: Interference mitigating mobility

16. Progress on what we don’t know XiXi Y i-1 p(y i,z i,s i |x i,s i-1 ) S i-1 SiSi D YiYi Tx 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)

17. 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

18. FLoWS progress since last September 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 and ongoing collaborations among PIs Overview paper for Scientific American –Co-authors: Effros, Goldsmith, Medard –Paper accepted for publication Magazine paper with overview of FLoWS –Paper near completion – will be submitted within 3 weeks All Phase 2 progress criteria have been met Website updated with Sept. PI meeting slides, recent publications, and recent results.

19. Focus Talks and Posters Thrust 1: –Moulin: Towards strong converses for MANETs Thrust 2: –Coleman: A dynamic approach to feedback coding strategies in MANETs Thrusts 2 and 3: –Effros: The cost of selfishness in network coding capacity Thrust 3: –Boyd and Goldsmith: Optimizing wireless network performance in stochastic environments Posters on all recent results

20. Progress Criteria: Phase 2 –Evolve results in all thrust areas to examine more complex models, robustness/security, more challenging dynamics, and larger networks. Network equivalence Multihop networks with interference forwarding Interference mitigation via mobility Unequal error protection Control principles for feedback designs Capacity scaling laws for arbitrary node placement and arbitrary demand Distributed second order methods for network optimization Generalized Max-Weight policies with optimal distributed implementations Local dynamics for topology formation Oblivous equilibrium –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. Capacity of finite-state broadcast channels w/wout feedback and Z channel (1-2) Bounds on capacity of cognitive radio and interference channel w/relay (1-2) New approach to optimize coding and scheduling (1-3 ) New game-theoretic approach to network coding (1-3 ) Multiperiod NUM applicable to any underlying network capacity region (1-2-3)

21. Progress Criteria: Phase 2 –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. Coding-based TDD has order of magnitude throughput increase versus uncoded Unbounded gain in network capacity with feedback Order of magnitude throughput gain in hyperarc scheduling Orders of magnitude BER reduction in wireless NUM Order of magnitude utility improvement for generalized Maxweight –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. Proposed book will define FLoWS ITMANET theory. –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 Scientific American paper accepted. Iteration with publisher ongoing. Magazine paper near completion, will be submitted within 3 weeks. Book proposal has been discussed with Cambridge University Press.

22. Project Impact To Date Plenary Talks –Boyd: Dysco’07, S. Stevun Lecture’08, CNLS’08, ETH’08 –Effros: ISIT’07 –Goldsmith: ACC’07, Gomachtech’08, ISWPC’08, Infocom’08, RAWC’09, WCNC’09 –Koetter: ITW’07, WiOPT’08 –Medard: Gretsi’07, CISS’07, Gilbreth Lecture (NAE)’07, IT Winter School’08, UIUC Student Conference’08, Wireless Network Coding’08, –Meyn: Erlang Centennial’09 –Ozdaglar: ACC 2009, NecSys'09, ASMD’08 –Johari: World Congress of the Game Theory Society’08 –Shah: Plenary talk at the Interperf/Valuetools 2007 Recent Tutorials –Boyd: MOCCS’08, WOSP’08 –Ozdaglar: ISIT’08, CDC’08 –Medard/Koetter: PIMRC’08 –Meyn: Mathematics of OR’08 –Shah: ACM Sigmetrics/Performance ’08, CDC’09, Conference Session/Program Chairs –ISIT’07, CTW’08, WiOpt’08, CTW’09, ITW’09, ITW’10, ISMP’09, INFORMS’09 Invited journal papers –“Breaking spectrum gridlock through cognitive radios: an information-theoretic approach”, IEEE Proc’09 (w/ Jafar, Maric, and Srinivasa)

23. Publications to date 16 accepted journal papers, 13 more submitted 89 conference papers (published or to appear) SciAM paper to appear –Magazine paper to be submitted shortly –Book on FLoWS vision and results under development Publications website: –http://www.stanford.edu/~adlakha/ITMANET/flows_publications.htmhttp://www.stanford.edu/~adlakha/ITMANET/flows_publications.htm

24. Summary Significant progress on all thrust areas Significant progress on synergies between thrust areas Ongoing and fruitful collaborations between PIs Phase 2 goals met Significant impact of FLoWS research on the broader research community (IT, communications, networking, and control/optimization)