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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.

Internet optimization through TOFFEE-DataCenter WAN Optimization Demo

Assume you have two sites (such as Site-A and Site-B) connected via slow/critical WAN link as shown below. You can optimize this link by saving the bandwidth as well possibly improve the speed. However, the WAN speed can be optimized only if the WAN link speeds are below that of the processing latency of your TOFFEE installed hardware. Assume your WAN link is 12Mbps, and assume the maximum WAN optimization speed/capacity of Raspberry Pi is 20Mbps, then your link will get speed optimization too. And in another case, assume your WAN link is 50Mbps, then using the Raspberry Pi as WAN Optimization device will actually increase the latency (i.e slows the WAN link). But in all the cases the bandwidth savings should be the same irrespective of the WAN link speed. In other words, if you want to cut down the WAN link costs via this WAN Optimization set up, you can always get it since it reduces the overall bandwidth in almost all the cases (including encrypted and pre-compressed data).

TOFFEE-Butterscotch is a 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.

The TOFFEE Project :: TOFFEE-Mocha :: Linux Open-Source WAN Emulator

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.

As a research experiment I replaced my Intel Core i7 5820K desktop PC with my Intel Celeron 1037U Mini-PC as my everyday desktop system. This is an attempt to reduce my overall monthly power consumption. As well an attempt to do feasibility tests and research to know how far Mini PC will dominate the market in future and to study the real potential of Mini PCs.