1. Performance Evaluation When: Wed. 2:20pm~5:10pm Where: Room 107 Instructor: 周承復 –Office hours: by appointment –www.csie.ntu.edu.tw/~ccf –E-mail: ccf@csie.ntu.edu.twccf@csie.ntu.edu.tw –Class web page and TA will be announced by this weekend TBD

2. Reading Reference Reference books: –Queueing systems (vol. I & II); Kleinrock –Analytical Performance Modeling for Computer Systems; Y.C. Tay –Prob., Stochastic process., and Queueing Theory; Randy Nelson. –Combinatorial Optimization: Algorithms and Complexity; Christos. H. Papadimitriou and Kenneth Steiglitz Paper reading & presentation

3. Grading Tentative Hw & Paper presentation : 35% class attendance (participation): 5-10% Midterm (1 or 2 times): 20-25% Term projects: 35-40% (1-2 members)

4. Projects 1 st programming project: –Discrete Time Event Simulator (in c, c++) Term project

5. Objective An intro. to techniques and tools –Construct and analyze a model (or by simulations) for computer and communication systems designs. Example –Internet, wireless communication, operating system, parallel and distributed system, database system, programming languages….

6. Objective paper reading –Server: Hardware Architecture, Operating Systems –Network –Database Management Term Project –Analytic model –Simulation (or Emulation) –Measurement (or Implementation)

7. Outline Introduction Probability review Discrete Time Event Simulator Stochastic Processes Elementary queueing theory –M/M/1, M/M/1 variants –M/G/1, M/G/1 variants, and Priority Queue Intermediate queueing theory –Bounding techniques –Matrix Geometric solutions: high-dimensional MC

8. Outline (cont.) Average Value and Fluid approximation Open and close system –equilibrium decomposition –bottleneck analysis –flow equivalence Linear Programming (ILP, or Non-Linear Programming)

9. What is the course used for ?

10. Single Server System A single-server system has a capacity C R is the average rate of the demanded work What is the stable condition for this system?

11. Single Queue vs. Multi-Queue Consider a system has K servers For a customer, which design is better? –Each server has its own queue –All K servers share a single queue

12. System Design If you want to upgrade your system, you will do –Buying k single servers with each has capacity C –Buying a single sever with capacity kC

13. Waiting in the Bus Station The inter-arrival time dist. for a bus is exponential dist. with mean 10 min John has arrived at the bus station for 5 min, so how long has he waited for till the next bus comes?

14. Priority Queue Consider a non-preemptive system and two customer classes A and B, with respective arrival and service rate a,  a, and b,  b,  b <  a. If we want to design a system with the avg. delay for a customer is small, which class should have higher priority

15. More Examples !

16. TCP Model –J. Padhye, V. Firoiu, D. Towsley, and J. Kurose. Modeling TCP throughput: a simple model and its empirical validation. In Proc. SIGCOMM, 303–314, September 1998. –Renewal theory, prob. Based approach

17. TCP Model –Vishal Misra, Wei-Bo Gong, and Don Towsley, Stochastic Differential Equation Modeling and Analysis of TCP-Window size Behavior, ACM SIGMETRICS 1999. –Fluid models, Stochastic differential equation

18. BitTorrent –D. Qiu and R. Srikant. Modeling and performance analysis of BitTorrent-like peer- to-peer networks. In Proc. SIGCOMM, 367– 378, 2004. –Fluid Model, steady-state analysis

19. 802.11 –Giuseppe Bianchi, Performance Analysis of the IEEE 802.11 Distributed Coordination Function, Selected Areas in Communications, IEEE Journal on, Vol. 18, No. 3. (March 2000), pp. 535-547, –DTMC based approach

20. Personal Comm. System –Yi-Bing Lin, Seshadri Mohan, Anthony Noerpel, Queueing Priority Channel Assignment Strategies for PCS Hand-Off and Initial Access, In Vehicular Technology, IEEE Transactions on, Vol. 43, No. 3. (1994), pp. –CTMC, probability, poisson process

21. P2P streaming –Yipeng Zhou, Dah Ming Chiu, John C.S. Lui, A Simple Model for Analyzing P2P Streaming Protocols, IEEE International Conference on Network Protocols (19 October 2007), pp. 226- 235 –probability

22. Distributed Protocols –I. Gupta. On the design of distributed protocols from differential equations. In Proc.ACM Symposium on Principles of Distributed Computing (PODC), 216–225, July 2004 –Epidemic model : differential eqn.

23. Database System –P.A.Bernstein,A.Fekete,H.Guo,R.Ramakrishnan, and P. Tamma, Relaxed currency serializability for middle-tier caching and replication. In Proc. ACM SIGMOD Int. Conf. Management of Data, 599–610, June 2006. –Bottlenecks and flow equivalence

24. Storage System –Q. Zhu, Z. Chen, L.Tan, Y. Zhou, K. Keeton, and J.Wilkes. Hibernator: helping disk arrays sleep through the winter. In Proc. ACMSymp. Operating Systems Principles (SOSP), 39(5):177–190, October 2005 –Integer Linear Programming

25. NEW ISSUES

26. Cloud Computing Resource Allocation and Markets –Online Auctions in IaaS Clouds: Welfare and Profit Maximization with Server Costs Xiaoxi Zhang etl. –An Online Auction Framework for Dynamic Resource Provisioning in Cloud Computing Weijie Shi etl.

27. BIG Data Analytics Machine Learning and Crowdsourcing –An Online Learning Approach to Improving the Quality of Crowd-Sourcing Yang Liu etl. –Learning to Rank: Regret Lower Bound and Efficient Algorithms Richard Combes etl.

28. Social Network Ads and Information Dissemination –Social Network Monetization via Sponsored Viral Marketing Parinya Chalermsook etl. –Collecting, Organizing, and Sharing Pins in Pinterest: Interest-driven or Social-driven? Jinyoung Han etl. –Filter & Follow: Do Social Media Encourage Efficient News Curation? Avner May

29. Topics for Next Week Course

30. Probability Review Probability Conditional probability Statistical independent Theorem of total Probability Bayes’ Theorem Random Variable