RESEARCH 》 Network MTU research and optimization of WAN Links

WAN Network data can be optimized at various levels depending upon the network applications, protocols, topology and use-cases. So the amount of data you can optimize will depend on the strategy you choose to optimize. Such as: Network Packet level optimization, Session level optimization, File level optimization, etc.

Here is a list of TOFFEE-DataCenter features supported. TOFFEE-DataCenter currently supports some of the important features such as loss-less network data compression, Packet Deduplication (protocols/applications supported), Application Acceleration, TCP Acceleration, dynamic MTU optimization, data packaging, hardware offload support, etc.

PiPG is a powerful and yet simple Raspberry Pi Network Packet Generator. With PiPG you can now fabricate custom network packets and send via any Network Interface. Supports all kinds of standard Network Ports (Linux Kernel driver generated) such as Physical Network Interface ports, and an array of virtual ports such as loopback, tun/tap, bridge, etc. indispensable tool for: Network Debugging, Testing and Performance analysis Network Administrators Students Network R&D Protocol Analysis and Study Network Software Development Compliance Testing Ethical Hackers you can generate the following test traffic: L2-Bridging/Slow protocols: STP, LACP, OAM, LLDP, EAP, etc Routing protocols: RIPv1, RIPv2, IGMPv1, IGMPv2, OSPF, IS-IS, EIGRP, HSRP, VRRP, etc Proprietary protocols: CISCO, etc Generic: IPv4 TCP/UDP, etc Malformed random packets

I was doing some specific tests in my TOFFEE and TOFFEE-DataCenter (WAN optimization) scenarios such as variable upload and download speeds. And I was also doing some experiments with speedtest.net and I did some of these tests with TOFFEE-Mocha. I realized there is a case that I can introduce asymmetric constant delays so that you can get different download speed and a different upload speed. And in some cases much faster download speeds and relatively slower upload speeds.

When you are dealing Deep Space Networks (DSN) one among the most challenging parts is the Interplanetary distances and communicating data across such vast distances. This is where we are not dealing with common Internet type traffic such as HTTP/FTP/VoIP/etc but it is completely different when it comes to DSN so far. So optimizing data in DSN becomes mandatory. For example if you think one of the Mars Rovers, they have used LZO lossless compression.

I started working on the new TOFFEE project (which is the fork of my earlier TrafficSqueezer open-source project) starting from 1st January 2016 onwards. Ever since I was busy in research and altering certain old features so that it is more minimal than TrafficSqueezer, a more focused agenda, deliver refined code and a broader vision. I have lined up more things to follow in the upcoming months. I want to focus about all aspects of WAN communication technologies not just on core WAN Optimization research and technology.

The TOFFEE Project :: TOFFEE-DataCenter :: Linux Open-Source WAN Optimization

TrueBench is an unique open-source benchmarking system in which the core system performance and efficiency parameters are measured at extreme high resolution in the order of several million/billion µ-seconds for a given specific task. TrueBench is a part of The TOFFEE Project research.

This is my next software development update of TOFFEE-DataCenter which I am working since past few weeks. I was very busy in implementing the core TOFFEE-DataCenter components along with prototyping, benchmarking, implementing and testing the same. However today is the first time ever I did a fresh new CLI interface for the upcoming new TOFFEE-DataCenter.