DOCUMENTATION 》 Riverbed and Silver Peak WAN Optimization vs TOFFEE-DataCenter (TOFFEE and or TrafficSqueezer) - FAQ

Software-Defined Wide Area Networking (SD-WAN) is a new innovative way to provide optimal application performance by redefining branch office networking. Unlike traditional expensive private WAN connection technologies such as MPLS, etc., SD-WAN delivers increased network performance and cost reduction. SD-WAN solution decouple network software services from the underlying hardware via software abstraction.

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

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.

TOFFEE-Butterscotch a TOFFEE for Home/SOHO Internet/WAN bandwidth

This is my first TOFFEE-Mocha combined x86-64 and i386 (Intel x86 64-bit and 32-bit) code release.

TOFFEE DataCenter WAN Optimization - Google Hangouts demo and VOIP Optimization

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.

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.

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.

Raspberry Pi is often used as a single board computer for applications such as IoT, hobby projects, DIY, education aid, research and prototyping device. But apart from these applications Raspberry Pi can be used for real-world applications such as in making a full-fledged networking devices. Raspberry Pi is a single board ARM based hardware which is why it is also classified as ARM based SoC. Since it is ARM based it is highly efficient, tiny form-factor and lower in power consumption with moderate computational power. This will allow it to work several hours on emergency battery backup power supply such as low-cost domestic UPS and or some renewable energy source, which is a prerequisite for a typical networking device.

TOFFEE-Butterscotch is an open-source software which can be used to save and optimize your 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.

Here is my video article on Network Latency in WAN Networks (such as long distance Satellite links, etc) and how you can optimize the same to achieve better network performance.