EECS Divisional Presentation

Computing, Algorithms and Applications

May 25, 2006

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

A Framework to Understand CAA Research

Algorithms

Externals(applications of

computation to other fields, and vice versa)

Models ofComputation

Complexity(resources used by computation)

Strategic BiddingJ. 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

Independent operator solves an (easy) optimization problem -- given the bids, determines amount gj to buy from you.

Spot price is Lagrange multiplier.

,...1

,...10s.t.

min

Jdemandg

Jcapacityg

gb

Jj

j

JJ

jjJgJ

bj = bid of company j cj = gener cost for company

gj = 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

27/1

1/01

10/0

2/02

26/0

4/02

10/0

7/02

23/0

9/02

07/1

2/02

20/0

2/03

06/0

5/03

20/0

7/03

03/1

0/03

17/1

2/03

01/0

3/04

15/0

5/04

29/0

7/04

12/1

0/04

26/1

2/04

11/0

3/05

25/0

5/05

08/0

8/05

22/1

0/05

05/0

1/06

21/0

3/06

MW

h

-

50

100

150

200

250

En

€/M

Wh

Daily volume Baseload price

Bi-level Optimization Problem:

• What about bids from competitors? Use stochastic optimization.

• Very large and nonlinear problem• Mathematically deficient --- need new theory

OptimizationProblem!!

DJJ

JJ

JJD

Lgb

solutionIndepOp

cb

gcL

,:IndepOper

tosubject

)(maxJb

Your problem (j=1)

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)

The Spread of Sapphire/Slammer Worms

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 itso slow?

Applied Computational GeometryPeter Scheuermann

r

Critical Region RR 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 region1. fastest arrival time for the desired number of sensors2. largest number of sensors to ensure desired quantity inside the region3. optimal time to ensure “fair” coverage under the constraint that a minimum number of sensors are inside the region

Publication: “Mission-Critical Management of MobileSensors (or, How to Guide a Flock of Sensors) in DMSN 2004

SENSOR RELOCATION

LMB

C D

E

FAProblem: 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 inMoving Object Databases” in MDM 2005

DYNAMIC TOPOLOGICAL PREDICATES FOR MOVING OBJECTS

Optimal and Efficient Algorithms for Circuit RetimingHai 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(n2m) time)

• Our algorithm is correct no matter what order is used for selecting nodes

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

TILE

G C A T C G

C G T A G C

DNA Algorithmic Self-Assembly

DNA Algorithmic Self-Assembly

Program = Tiles + Lab Steps Output

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

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)

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.

Protein Analysis: HPLC-MS-MS

HPLC MassSpectrometer

Fragmentation & ionization

MassSpectrometer

De Novo Peptide Sequencing

Protein Database SearchingMass/Charge

Mass/Charge

Proteins Peptides

Tandem Mass Spectrum

One PeptideB-ions / Y-ions

Synergies with Other Divisions

CAA

Computer Engineering & Systems

Signals & Systems

Solid State & Photonics

Cognitive Systems +

Graphics & Interactive Media

Musical RetrievalComputational Economics

Network OptimizationDNA Computing

Quantum ComputingCryptography

BioinformaticsComputer Worm Detection

Design OptimizationDNA Computing

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?

The End

Thank You!