1. EECS Divisional Presentation Computing, Algorithms and Applications May 25, 2006

2. Current CAA Faculty Primary Members: Ming-Yang Kao: theoretical computer science Jorge Nocedal: continuous optimization Secondary Members: Yan Chen: networking and security Peter Scheuermann: databases Hai Zhou: CAD algorithms and formal methods Tertiary Members: Alan Toflove: computational electrodynamics

3. A Framework to Understand CAA Research Algorithms Externals (applications of computation to other fields, and vice versa) Models of Computation Complexity (resources used by computation)

4. Strategic Bidding J. Nocedal and R. Waltz Your company sells electric power (internet resources, wireless bandwidth). You and other producers submit competitive bids to generate power. An Independent Operator purchases at a single “spot price.” Your strategic guidance: –submit low bids  spot price –submit high bids to drive up the spot price –Demands, etc, uncertain

5. Independent operator solves an (easy) optimization problem -- given the bids, determines amount g j to buy from you. Spot price is Lagrange multiplier. b j = bid of company j c j = gener cost for company g j = gener sold by plant j Powernext Day-Ahead™: daily volume and baseload price 0 10 000 20 000 30 000 40 000 50 000 60 000 70 000 80 000 90 000 100 000 110 000 120 000 27/11/0110/02/0226/04/0210/07/0223/09/0207/12/0220/02/0306/05/0320/07/0303/10/0317/12/0301/03/0415/05/0429/07/0412/10/0426/12/0411/03/0525/05/0508/08/0522/10/0505/01/0621/03/06 MWh - 50 100 150 200 250 300 En €/MWh Daily volumeBaseload price

6. Bi-level Optimization Problem: What about bids from competitors? Use stochastic optimization. Very large and nonlinear problem Mathematically deficient --- need new theory Optimization Problem!! Your problem (j=1)

7. Northwestern Lab for Internet and Security Technology (LIST) Yan Chen High-performance Network Anomaly/Intrusion Detection and Mitigation (HPNAIDM) Systems Data streaming computation: 10s Gigabit-link network traffic recording and analysis (with P. Dinda and G. Memik) Combinatorial statistics: first online network-based polymorphic worm signature generation with provable attack resilience (with M. Kao) Formal verification: vulnerability analysis of 802.16 protocols using formal methods (with H. Zhou, J. Fu (Motorola) ) Information theory: network anomaly & intrusion detection (with D. Guo)

8. The Spread of Sapphire/Slammer Worms

9. Northwestern Lab for Internet and Security Technology (LIST) Yan Chen Internet Measurement, Diagnosis & Inference Linear Algebra: Scalable and deterministic network monitoring, diagnosis, and link-level properties (e.g., loss rate) inference Statistics: Network router configuration (e.g., QoS) inference (with F. Bustamante and G. Lu (Tsinghua)) C&W AT&T Sprint UUNet Qwest Earthlink AOL It’s so slow! Why is it so slow?

10. Applied Computational Geometry Peter Scheuermann r Critical Region R R Problem: How to optimize the guidance of mobile sensors which need to be brought into a critical region, to ensure a desired level of coverage for that region? Variants use convex hull of critical region 1. fastest arrival time for the desired number of sensors 2. largest number of sensors to ensure desired quantity inside the region 3. optimal time to ensure “fair” coverage under the constraint that a minimum number of sensors are inside the region Publication: “Mission-Critical Management of Mobile Sensors (or, How to Guide a Flock of Sensors) in DMSN 2004 SENSOR RELOCATION

11. LM B CD E F A Problem: Notify me when an object is continuously_moving_towards the landmark LM, for more than 5 min., based on periodic (location,time) updates (primitive events) Solution: Use Voronoi diagram (for the LM) and monitoring of only two consecutive updates; - Issue: consumption of primitive events? Send update! To Send To Send or Not To Send? (have the previous simple events been “consumed”) Publication: “Dynamic Topological Predicates and Notifications in Moving Object Databases” in MDM 2005 DYNAMIC TOPOLOGICAL PREDICATES FOR MOVING OBJECTS

12. Optimal and Efficient Algorithms for Circuit Retiming Hai Zhou Retiming is an effective technique for circuit optimization by relocating registers without changing functionality We developed the most efficient algorithm for clock period minimization considering both long and short paths (in O(n 2 m) time) Our algorithm is correct no matter what order is used for selecting nodes

13. Gate Sizing for Coupling Noise Control as Distributed Optimization Hai Zhou Noise on a signal is proportional to attacker gate sizes and inversely proportional to its own gate size Given the coupling relations and the noise upper bound for each signal Need to find minimal gate sizes such that all noises are under constraints Our algorithm: Each gate starts at lower bound Repeat: Each signal with violation up-size its gate to the smallest with tolerable noise Correct no matter what order is taken Will converge to the optimal solution if there is one Very efficient practically May be used in wireless networks

14. TILE G C A T C G C G T A G C DNA Algorithmic Self-Assembly

15. Program = Tiles + Lab StepsOutput

16. DNA Algorithmic Self-Assembly Input: the description of a shape Output: a set of tiles and a sequence of lab steps to produce the shape Computational Objectives: minimize the # of tile types minimize the range of temperatures minimize the # of lab steps minimize errors

17. Sequencing Bio-molecules Input: information about small pieces of a target molecule Output: the character sequence of the target molecule Examples: Peptide Sequencing: linear structure (with a group at Harvard Medical School) Glycan Sequencing: tree structure (with a group at Kyoto University)

18. Sequencing Bio-molecules Given: a target bio-molecule B Steps: 1.Make many copies of B. 2.Cut each copy of B into pieces. 3.Sequence each piece (recursively). 4.Assemble the character sequences of the pieces into the character sequence of B.

19. Protein Analysis: HPLC-MS-MS Mass/Charge ProteinsPeptides Tandem Mass Spectrum One PeptideB-ions / Y-ions

20. Synergies with Other Divisions CAA Computer Engineering & Systems Signals & Systems Solid State & Photonics Cognitive Systems + Graphics & Interactive Media Musical Retrieval Computational Economics Network Optimization DNA Computing Quantum Computing Cryptography Bioinformatics Computer Worm Detection Design Optimization DNA Computing

21. CAA’s Mission: To Understand the Nature, Power, Limit of Computation; and to Apply Such Understanding to Benefit the Society. Basic Understanding about Computation: Computation is an intellectual tool as powerful and universal as mathematics. Computation can be used not only to solve mathematical problems, but also to understand and design complex systems. Examples of Computation: How many bits of information does a black hole compute? How do we make web search efficiently provide the information that we want? How do we create a biological “computer” that uses DNA/RNA-like materials to produce medicines?

22. The End Thank You!