Developing a SIP signalling WebRTC communication platform for enterprises . Also discusses filling up the gaps left in WebRTC like ICE, Security , transcoders , auth , connection to IMS ( IP Multimedia Subsystem ) and RCS etc . Discuss interesting usecases for such a solution in fields like Tele-medicine , BYOD , Field Force management , Customer care etc 


Outline/Structure of the Talk

Unified Communications
SIP ( Session Initiation protocol )
WebRTC + SIP ( simplified )
WebRTC + SIP + ICE ( TURN and STUN )
Demo of SIPml5 with traces
Solution Architecture
Application Modules


  • Virtual office / BYOD
  • Tele- health
  • field force management
  • customer care center

More Material

  • Protocol Layers
  • WebRTC Device support
  • WebRTC Developer Interest
  • Business Users for WebRTC

Learning Outcome

Will be able to understand the nitty gritties of WebRTC SIP based application and apply to their respective fields .

Target Audience



schedule Submitted 6 years ago

  • 60 Mins

    In this talk, I will talk about our motivation for creating Julia. Julia is a high-level, high-performance dynamic programming language. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. Julia’s Base library, largely written in Julia itself, also integrates mature, best-of-breed open source C and Fortran libraries for linear algebra, random number generation, signal processing, and string processing. In addition, the Julia developer community is contributing a number of external packages through Julia’s built-in package manager at a rapid pace. This is why Julia is seeing rapid adoption in universities for teaching and research, as well as in businesses.

    I will discuss what makes Julia fast. Julia's ability to combine these levels of performance and productivity in a single language stems from the choice of a number of features that work well with each other:

    1. An expressive parametric type system, allowing optional type annotations;
    2. Multiple dispatch using those types to select implementations;
    3. A dynamic dataflow type inference algorithm allowing types of most expressions to be inferred;
    4. Aggressive code specialization against run-time types;
    5. Metaprogramming;
    6. Just-In-Time compilation using the LLVM compiler framework; and
    7. Careful design of the language and standard library to be amenable to type analysis;

    I will also touch upon how the language design has made it possible to explore many parallel programming models in Julia, completely within the language.


  • Shashi Gowda

    Shashi Gowda / Viral B. Shah - Julia - A Lisp for Fast Number Crunching

    240 Mins

    Julia is a programming language for data science and numerical computing. Julia is a high-level, high-performance dynamic language, it uses just-in-time compilation to provide fast machine code - dynamic code runs at about half the speed of C, and orders of magnitude faster than traditional numerical computing tools.

    Julia borrows two main ideas from Lisp lore:

    1. Multiple-dispatch: a method is identified by a name and the types of all of its arguments (traditional OOP only uses the type of a single argument) multiple-dispatch allows for a natural programming model suitable for mathematics and general purpose programming. Interestingly, the same feature is responsible for Julia's ability to generate really fast machine code.
    2. Macros: Julia has syntax that is familiar to users of other technical computing environments, however, Julia expressions are homoiconic -- Julia code can be represented as Julia data structures, and transformed from one form to another via hygienic macros. There are some very interesting uses of macros to create domain-specific languages for effective programming. 

    (I will be presenting this workshop along with Viral B Shah - co-creator of Julia)

  • Ravi Mohan

    Ravi Mohan - Building a General Game Playing Engine with OCaml and Erlang

    Ravi Mohan
    Ravi Mohan
    schedule 6 years ago
    Sold Out!
    90 Mins
    Experience Report

    "General Game Playing  is the design of artificial intelligence programs that play more than one game"  Wikipedia [1]

    In other words, one program has to be able to play (and win!) multiple games ( Chess, checkers, Go, Othello etc).

    Summary: This experience report is about my  "Forever Project" [2,3,4] to build such a system in OCaml, and the problems (theoretical and practical) and will include a demo of the program, warts and all.

    Detail: GGP is an active CS research area [5]Annual competitions are held every year where  ggp programs compete against each other[6], playing games which they have never seen before (the rules are supplied as an input file for the system to consume five minutes before the match begins).

    Over the last year, in my non-existent spare time, I've been building a GGP engine to compete in a GGP competition.

    Most such engines are written in Java, C++  etc.. I'm using OCaml for the game playing agent, and Manoj is building the backend in Erlang.

    As mentioned above this is our "Forever Project"  We've made some decent progress.

    Come, see, laugh, jeer!

  • Bhasker Kode

    Bhasker Kode - Workshop: Erlang by example

    Bhasker Kode
    Bhasker Kode
    Building stuff
    schedule 6 years ago
    Sold Out!
    480 Mins

    From fundamentals to deploying Erlang micro-service.

  • Bhasker Kode

    Bhasker Kode - who uses erlang? where & why

    Bhasker Kode
    Bhasker Kode
    Building stuff
    schedule 6 years ago
    Sold Out!
    45 Mins

    a general talk about where erlang is used, who uses it, where is it used & why, concluding with the state of erlang in asia.