1. Memory of Dr. Masaki Hirabaru Shigeki Goto Waseda University

2. A big boy and a small modem in 1986 Kyushu University NTT Lab

3. APNIC and JPNIC Confederation RIR IP addresses and AS numbers IANA ICANN APNICJPNICKRNICTWNICRIPE NCC European Friends A Proposal for APNIC experiments presented by Jun Murai (WIDE Project/JNIC) and Masaki Hirabaru (WIDE Project/JNIC) at the APCCIRN meeting in Waikiki, Honolulu. January 13, 1993 History of APNIC http://www.apnic.net/info/history/index.htmlProposal for APNIC experimentsAPCCIRN meeting

4. Arbor Peakflow IP Flow-Based Technology Akihiro Shimoda, Dark Flow, 2009 Virtual Dark IP (*) IEICE, Vol.J92-B, No.1, pp.163-173, January, 2009 Two students visited Ann Arbor, Michigan, in August 2008.

5. Visible routers in Visible network Presentation at CORE University Program at Beppu, 2009 5 CORE University Program Seminar Beppu City February 2009

6. Science makes everything visible. 6 Beppu Hell T-shirt

7. Cloud or stupid network Old smart network 7 Modern stupid network

8. The router is actually smart! routing and forwarding routing prefix, prefix age, link bandwidth, available bandwidth, i/f queue, corruption loss, congestion loss, L2 address, signal strength, retransmission counter... operation uptime, location, temperature, time zone, i/f description, CPU load, operator’s contact.... MIB, PerfSONAR by ikob, Dr Kobayashi

9. How to extract information PTP: retrieve every hop’s data by single packet with header growth SIRENS: one packet collects one router’s data, multiple packets are required to retrieve whole path © ikob, Dr Kobayashi

10. Visible route © ikob, Dr Kobayashi

11. Kwangju Busan 2.5G Fukuoka Korea 2.5G SONET KOREN Taegu Daejon 10G 1G (10G) 1G Seoul XP Genkai XP Kitakyushu Kashima 1G (10G) Fukuoka Japan 250km 1,000km 2.5G JGN II 9,000km 4,000km Los Angeles Chicago Washington DC MIT Haystack 10G 2.4G APII/JGNII Abilene Koganei 1G(10G) Indianapolis 100km bwctl server Experiment for High-Performance Scientific Data Transfer 10G Tokyo XP / JGN II I-NOC *Performance Measurement Point Directory http://e2epi.internet2.edu/pipes/pmp/pmp-dir.html perf server e-vlbi server JGNII 10G GEANT SWITCH 7,000km TransPAC Pittsburgh U of Tokyo A BWCTL account available for CMM including Korean researchers International collaboration to support for science applications U. Hawaii © Masaki Hirabaru, January 27, 2005

12. Traffic volume Application: P2P traffic engineering 12 heavy traffic with other AS numbers Wei Yuan, Goto Lab. BitTorrent

13. Traffic volume Traffic engineering 13 Wei Yuan, Goto Lab. within an AS number

14. Related topic Open flow, flow based routing A flow is a series of IP packets. flow = 14 hash table routing table flow data

15. NetFPGA-1G Hardware Xilinx Virtex-2 Pro FPGA PCI Host Interface SRAM DRAM 4 * Gigabit Ethernet ports

16. Open Flow Demo at SC 08 http://jpnoc.net/OpenFlow-DEMO.m4v 16 movie by Jin Tanaka

17. No buffer memory for flow routers traditional routers: a parking lot model 17 flow router ： connection model, non- delay queue

18. 18 Anagran FR-1000 NetFPGA Caspian Networks NEC

19. Summary (Part 1) Visible routers and switches are important Application area — we need input from you Flow based routing — future internet? 19

20. Summary (Part 1) Visible routers and switches are important Application area — we need input from you Flow based routing — future internet? 20 http://www.e-marutou.com/?pid=3749729 Enjoy your stay at Beppu!

21. Second Great Depression ? US financial company JP manufacturing company Classification by Kazuo Mizuno Phrase used by Paul Robin Krugman

22. Loss or Growth? US Investment Bank JP Export Company Kazuo Mizuno, and Mitsubishi UFJ Securities, graph redrawn by S.Goto financial asset = market capitalization +bonds outstanding +money supply

23. Black–Scholes The Black–Scholes model is a mathematical model of the market for an equity, in which the equity's price is a stochastic process.stochastic process The Black–Scholes PDE is a partial differential equation which (in the model) must be satisfied by the price of a derivative on the equity.partial differential equation The Black–Scholes formula is the result obtained by solving the Black-Scholes PDE for European put and call options. European http://en.wikipedia.org/wiki/Black-Scholes 23

24. Black–Scholes Merton and Scholes received the 1997 Nobel Prize in Economics for this and related work. Black was ineligible for the prize because of his death in 1995.Nobel Prize in Economics The price of the underlying instrument S t follows a Wiener process W t with constant drift μ and volatility σ, and the price changes are log-normally distributed:underlying instrumentWiener processconstantvolatilitylog-normally ja.wikipedia.org/wiki/ ブラック - ショールズ方程式 ブラック - ショールズモデルとは、 1 種類の配当のない株と 1 種類の債券の 2 つが 存在する証券市場のモデルで、時刻 t における株価 S t と債券価格 B t が配当株債券証券市場 dS t = S t (σdW t + μdt), B t = exp(rt), r,σ,μ は定数, W t は標準ブラウン運動, を満たすものをいう。ブラウン運動 dS t = μS t dt+ σS t dW t 24

25. Network Traffic Our diffusion equation is similar to that taken by Black and Scholes who modeled the option pricing behavior as a geometric Brownian motion. http://dspace.wul.waseda.ac.jp/dspace/bitstream/2065/4894/1/93038_391.pdf Yoshitaka Takahashi, A branching Poisson Process Input Finite-Capacity Queueing System for Telecommunication Networks, Waseda Commercial Review, vol.391, pp.105— 116, Dec 2001. 25

26. Fractal and Multifractal Benoit B. Mandelbrot, A Multifractal Walk Down Wall Street, Scientific American, February 1999. http://www.elliottwave.com/education/SciAmerican/Mandelbrot_Article2.htm Benoit B. Mandelbrot and Richard L. Hudson, The (Mis)behaviour of Markets: A Fractal View of Risk, Ruin, and Reward, 2004. (In Japanese, Econophysics) 高安秀樹「経済物理学の発見」 光文社新書１６７, 2004. 26

27. Random Walk vs. Fractal A Multifractal Walk Down Wall Street 27 Burton G. Malkiel, Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing

28. Fractal 28 Koch curve ja.wikipedia.org/wiki/ コッホ曲線

29. 29 Tatsuya Mori, PhD Thesis, Waseda Universtiy, 2005 Network Traffic normal distribution (fGn model) Captured Packets Pr [X (t i ) = x] X (t i ) histogram asymmetric symmetric histogram X (t i ) titi titi

30. Naoki Arai and Shigeki Goto, Traffic Analysis Based on Autonomous System Numbers, IWS2000, Internet Workshp 2000 pp.121-126, February 16, 2000. 30 Power Function (High volume AS numbers)

31. Lessons (Part 2) It is not possible to predict stock prices by the new theory. The old model underestimates the risk because it uses random walk, or normal distribution. Network traffic: 95% rule of SLA is reasonable? 31