VIDEOS 》 TOFFEE DataCenter WAN Optimization - Google Hangouts demo and VOIP Optimization

TOFFEE is an open-source WAN Optimization (Network Performance Optimization) software which can be used to optimize your critical networks.

TOFFEE TOFFEE Data-Center is specifically meant for Data Center, Cluster Computing, HPC applications. TOFFEE is built in Linux Kernel core. This makes it inflexible to adapt according to the hardware configuration. It does sequential packet processing and does not scale up well in large multi-core CPU based systems (such as Intel Xeon servers, Core i7 Extreme Desktop systems,etc). Apart from this since it is kernel based, if there is an issue in kernel, it may crash entire system. This becomes a challenge for any carrier grade equipment (CGE) hardware build.

TOFFEE-Butterscotch yet another variant of TOFFEE can be used to save and optimize your Home/SOHO Internet/WAN bandwidth. Unlike TOFFEE (and TOFFEE-DataCenter) TOFFEE-Butterscotch is a non peer-to-peer (and asymmetric) network optimization solution. This makes TOFFEE-Butterscotch an ideal tool for all Home and SOHO users.

There are various techniques with which one can optimize their WAN Network Data. Any long distance communication can be considered as WAN Network. A decade ago any network connecting two countries, considered as a WAN network, and a network within a city as MAN and soon. But these days in general any long distance communication is considered as WAN Network. Such as your Mobile communication networks, Satellite networks, Space Networks (Deep space networks), Trans-Atlantic cable networks, etc.

Seems there are couple of Inmotionhosting servers are down. And one of the server includes The TOFFEE Project website hosted server. I was in touch with the Inmotionhosting team trying to resolve the same. I found a unique issue that all my website files are intact and the Joomla database. But the Joomla database tables are completely wiped out and missing. Besides there is also a sort of upgrade going on in their servers. Luckily I have the most recent backup of the entire website.

TOFFEE Fudge is a simple intuitive Network Packet Generator which can be used to create custom test synthetic Network Packets and can be used in various applications such as networking research, network infrastructure troubleshooting, ethical hacking, as a network software development tool and so on.

Here is the TOFFEE WAN Optimization benchmarks of the TOFFEE version: TOFFEE-1.1.28. This is the current TOFFEE development version till date (2-Jul-2016). This is a HPC TOFFEE variant meant for high-end custom build servers and high-end desktops (i.e High Performance Computing a.k.a HPC). TOFFEE built this way often needs customized kernel compilation and build such as processor specific and hardware specific tune-ups since it is highly CPU intensive (if not offloaded via Hardware Accelerator Cards).

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. With TrueBench Raspberry Pi 3, Raspberry Pi 2B and Raspberry Pi 2 are benchmarked and you can do a comparative analysis with standard mainstream x86 devices.

VPN Networks may degrade network performance due to various packet processing overheads such as encryption and by adding extra network protocol header(s) (such as IPv4/IPv6, IPSec, etc). This may inflate near MTU sized packets and causes excessive packet fragmentation. Here are the few examples of packet processing involved in a VPN (or a VPN like) Tunnel. With TOFFEE you can optimize these packets even before they get processed on to a VPN device. TOFFEE optimizes packet contents (application payload and transport headers) so that these TOFFEE optimized packets when they get processed by VPN devices (or VPN software stack) they may never need further packet fragmentation. Here is a deployment scenario of TOFFEE with VPN devices.