Recent learning on (Computer) Networking from practice

Today I just finished implementing a heterogenous network simulation environment using Mininet for my most recent work on implementing a traffic migration framework. Although I have used Mininet before, this past few weeks have really been a roller coaster and I have learnt so much more than what I had before.

My latest Mininet environment consists of a simulated geo-distributed networks with several Network Functions, OSPF router, BGP router, load balancer (L2 and L3/4), and programmable switches (powered by OpenFlow) in general. They are implemented to show the genericness of our framework.

Besides the usual Mininet APIs, I also got my hands dirtyby actually tuning industry routing softwares, specifically with the Quagga software package. I learnt to explore and configure OSPF and BGP rules from scratch, as well as configuring public and private IP namespaces. For the programmable switches, I have deep-dived into the OpenFlow protocol and implemented a Ryu app that can explore the topology, do path discovery and actively install OpenFlow entries to switches for heterogenous packets flows (IPv4 and ARP mostly).

After all, I think the biggest impact to me was to become more truly understand what Network Functions are. They are basically Software Defined modules that sit either in the control plane and even data plane (Now P4 is talking!) and manipulate switch tables using the intelligence of a general/specific purpose computing environment (e.g. Linux).

Though it was a lot of pain figuring out how these so many new things work (can’t forget that I spend half a day figuring where the hell was the command “show ip ospf” is …), I can finally say that it was worth it! No pain no gain!

Distributed System Learning Tool (Updating)

Recently I am taking the Cloud Computing Specialization course series on Coursera. I was very intrigued by the different concepts in distributed systems. However, while I was working on the homeworks, I found it a bit tough sometimes to compute attributes like Lamport timestamp when I am not being able to visualize the message flows between distributed processes. Thus, I will start working on a visualization tool and automatic solver for these type of problems.

It aims to provide the following features:
– Drag and drop message flows between processes
– (For unicast messages) Automatically solve Lamport and Vector timestamps based on message flows
– (For multicast messages) Automatically solve orderings including FIFO and Causal

The base of the tool, e.g. its visualization canvas, the graph data structures should be extended to visualize and solve other types of problems such as the Global Snapshot Algorithm.

This post will be updated accordingly (Hopefully I will have enough time) …

(UPDATE 2020/05: Gosh I still haven’t got started on this, needs to catch up now lol)