With the start of pandemic, there was an increase in the demand of video conferencing systems. These systems were highly scalable but
they were always criticised for their lack of data security. This project aimed at creating a video conferencing system
with a distributed architecture, keeping data security at the helm. I developed a web application with a mesh architecture using WebRTC.
I also added a discovery server, capability to view multiple screens and selective display. This design could support 5 users with
video but wasn’t scalable beyond that. I used supernodes to solve this problem.
These improved the scalability of the system to 12 users.
An cluster middleware for resource management with a master-worker architecture. The master node accepts tasks along
with their requirements such as cpu and memory. Then, It identifies the appropriate worker node from the available pool
and allocates the task. Some features of this system are:
This work is an implementation of the paper S3DNN.
DNN workloads for autonomous driving typically consists of relatively reduced load near the last layers.
This work leverages this to improve the efficiency of resource usage.