tristanls

1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

tristanls

sjcl (http://crypto.stanford.edu/sjcl/)

crypto-js (https://code.google.com/p/crypto-js/)

jsCrypto (https://code.google.com/p/jscryptolib/)

triplesec (https://github.com/keybase/triplesec)

polycrypt (https://github.com/polycrypt)

tristanls

(function (ctr,t) {
  
  function inc () { ctr++ }

  function display (ntps,ntpsStr,i,lps,lpsStr,ratioStr) {
    ntps= ctr*1e3/(Date.now()-t); //nextTicks per second
    ntpsStr= ", nextTicksPerSecond: "+ ntps.toFixed(1);
  
    ctr= 0;
    i= 100e6;