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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.

Bitcoin Mining - Blockchain Technology - Network Optimization via TOFFEE Data-Center WAN Optimization

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.

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.

When you build a WAN Optimization device with TOFFEE the entire packet processing (data optimization) takes place in software layer or in other words more precisely Operating System kernel space. However if you have any compression or encryption hardware accelerator hardware card the parts of the TOFFEE packet processing modules can be offloaded to hardware layer and thus improving its efficiency.

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.

Earlier the TOFFEE is intended to work on IoT devices, Satellite Networks, branch office/SOHO deployments. In most cases the users may deploy just one or couple of TOFFEE devices per site. But in the case of TOFFEE-DataCenter, users can scale-up deploying the same in multiple servers in a sort of distributed cluster computing scenario. Besides the core TOFFEE-DataCenter components (such as packet processing engine/framework), I need to do lot of changes in its Graphical User Interface (GUI) too to address these new requirements.

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

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.

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.

Today I got a feature request from Jonathan Withers. Jonathan is from a company called MultiWave Australia. He said he is able to get the TOFFEE-Mocha Raspberry Pi setup up and with that he is able to emulate geostationary satellite link. But he requested me is there a way to extend the constant packet delay from 40mS to 500mS. So as a part of his request I supported the same in the current ongoing development version of TOFFEE-Mocha.