acm - an acm publication

2016 - August

  • Rethinking Randomness: An interview with Jeff Buzen, Part II

    In Part 1, Jeff Buzen discussed the basic principles of his new approach to randomness, which is the topic of his book Rethinking Randomness. He continues here with a more detailed discussion of models that have been used successfully to predict the performance of systems ranging from early time sharing computers to modern web servers.

    Peter J. Denning
    Editor in Chief

  • Rethinking Randomness: An interview with Jeff Buzen, Part I

    For more than 40 years, Jeffrey Buzen has been a leader in performance prediction of computer systems and networks. His first major contribution was an algorithm, known now as Buzen's Algorithm, that calculated the throughput and response time of any practical network of servers in a few seconds. Prior algorithms were useless because they would have taken months or years for the same calculations. Buzen's breakthrough opened a new industry of companies providing performance evaluation services, and laid scientific foundations for designing systems that meet performance objectives. Along the way, he became troubled by the fact that the real systems he was evaluating seriously violated his model's assumptions, and yet the faulty models predicted throughput to within 5 percent of the true value and response time to within 25 percent. He began puzzling over this anomaly and invented a new framework for building computer performance models, which he called operational analysis. Operational analysis produced the same formulas, but with assumptions that hold in most systems. As he continued to understand this puzzle, he formulated a more complete theory of randomness, which he calls observational stochastics, and he wrote a book Rethinking Randomness laying out his new theory. We talked with Jeff Buzen about his work.

    Peter J. Denning
    Editor in Chief

2018 Symposia

Ubiquity symposium is an organized debate around a proposition or point of view. It is a means to explore a complex issue from multiple perspectives. An early example of a symposium on teaching computer science appeared in Communications of the ACM (December 1989).

To organize a symposium, please read our guidelines.


Ubiquity Symposium: Big Data

Table of Contents

  1. Big Data, Digitization, and Social Change (Opening Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic
  2. Big Data and the Attention Economy by Bernardo A. Huberman
  3. Big Data for Social Science Research by Mark Birkin
  4. Technology and Business Challenges of Big Data in the Digital Economy by Dave Penkler
  5. High Performance Synthetic Information Environments: An integrating architecture in the age of pervasive data and computing By Christopher L. Barrett, Jeffery Johnson, and Madhav Marathe
  6. Developing an Open Source "Big Data" Cognitive Computing Platform by Michael Kowolenko and Mladen Vouk
  7. When Good Machine Learning Leads to Bad Cyber Security by Tegjyot Singh Sethi and Mehmed Kantardzic
  8. Corporate Security is a Big Data Problem by Louisa Saunier and Kemal Delic
  9. Big Data: Business, technology, education, and science by Jeffrey Johnson, Luca Tesei, Marco Piangerelli, Emanuela Merelli, Riccardo Paci, Nenad Stojanovic, Paulo Leitão, José Barbosa, and Marco Amador
  10. Big Data or Big Brother? That is the question now (Closing Statement) by Jeffrey Johnson, Peter Denning, David Sousa-Rodrigues, Kemal A. Delic