A WebRTC Video Chat Implementation Within the Yioop Search Engine

Web real-time communication (abbreviated as WebRTC) is one of the latest Web application technologies that allows voice, video, and data to work collectively in a browser without a need for third-party plugins or proprietary software installation. When two browsers from different locations communicate with each other, they must know how to locate each other, bypass security and firewall protections, and transmit all multimedia communications in real time. This project not only illustrates how WebRTC technology works but also walks through a real example of video chat-style application. The application communicates between two remote users using WebSocket and the data encryption algorithm specified in WebRTC technology. This project concludes with a description of the WebRTC video chat application’s implementation in Yioop.com, a PHP-based internet search engine

Personal Volunteer Computing

We propose personal volunteer computing, a novel paradigm to encourage technical solutions that leverage personal devices, such as smartphones and laptops, for personal applications that require significant computations, such as animation rendering and image processing. The paradigm requires no investment in additional hardware, relying instead on devices that are already owned by users and their community, and favours simple tools that can be implemented part-time by a single developer. We show that samples of personal devices of today are competitive with a top-of-the-line laptop from two years ago. We also propose new directions to extend the paradigm

Pando: Personal Volunteer Computing in Browsers

The large penetration and continued growth in ownership of personal electronic devices represents a freely available and largely untapped source of computing power. To leverage those, we present Pando, a new volunteer computing tool based on a declarative concurrent programming model and implemented using JavaScript, WebRTC, and WebSockets. This tool enables a dynamically varying number of failure-prone personal devices contributed by volunteers to parallelize the application of a function on a stream of values, by using the devices' browsers. We show that Pando can provide throughput improvements compared to a single personal device, on a variety of compute-bound applications including animation rendering and image processing. We also show the flexibility of our approach by deploying Pando on personal devices connected over a local network, on Grid5000, a French-wide computing grid in a virtual private network, and seven PlanetLab nodes distributed in a wide area network over Europe.Comment: 14 pages, 12 figures, 2 table