The TOFFEE Project
HOMEDOCUMENTATIONUPDATESVIDEOSRESEARCHDOWNLOADSPONSORSCONTACT


DOCUMENTATION 》 TOFFEE deployment topology guide

Language :: Portuguese Russian Spanish Chinese

Typical setup (for DIY users, SOHO, etc): 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).
For more details on TOFFEE installation hardware kindly refer: TOFFEE hardware selection guide

TOFFEE setup for DIY users

Other TOFFEE (and or TOFFEE-DataCenter) deployment scenarios:

  • TOFFEE (and or TOFFEE-DataCenter) deployment in SD-WAN Applications: HERE
  • TOFFEE (and or TOFFEE-DataCenter) deployment with VPN devices: HERE
  • TOFFEE (and or TOFFEE-DataCenter) deployment with web-proxy cache: HERE
  • TOFFEE-DataCenter a TOFFEE variant for Data Center applications: HERE
  • TOFFEE-DataCenter as a VNF for NFV: HERE
  • TOFFEE (and or TOFFEE-DataCenter) deployment in Large Infrastructure and or ISP Networks: HERE
  • TOFFEE (and or TOFFEE-DataCenter) optimized Satellite (inflight/marine/defense) ISP Networks: HERE
  • TOFFEE (and or TOFFEE-DataCenter) optimized Mobile Wireless Backhaul Networks: HERE
  • TOFFEE (and or TOFFEE-DataCenter) optimized Wireless Mesh-Networks - B.A.T.M.A.N [open-mesh.org (Open Mesh)]: HERE
  • TOFFEE (and or TOFFEE-DataCenter) optimized LoRaWAN Networks: HERE
  • TOFFEE-DataCenter with GlusterFS Storage Cluster: HERE
  • TOFFEE Data-Center WAN Optimization deployment in Big Data Analytics: HERE
  • TOFFEE Data-Center optimized Internet of Things (IoT) Platform: HERE
  • TOFFEE-Butterscotch a TOFFEE for Home/SOHO Internet/WAN bandwidth: HERE



Here is a quick architectural perspective of how TOFFEE-DataCenter optimizes incoming discrete packets:
Packet Optimization with TOFFEE-DataCenter



Suggested Topics:


TOFFEE - WAN Optimization


Categories

💎 TOFFEE-MOCHA new bootable ISO: Download
💎 TOFFEE Data-Center Big picture and Overview: Download PDF


Recommended Topics:

A study on Deep Space Networks (DSN) ↗
Saturday' 13-Mar-2021
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.

TOFFEE-Mocha WAN Emulation software development - Update: 18-June-2016 ↗
Saturday' 13-Mar-2021
In the previous update (17-Jun-2016) I discussed about the upcoming new Random Packet drop feature along with other completed features. Now I completed the entire TOFFEE-Mocha Random packet drop feature. I completed all the kernel components and the UI support of the same. And to make GUI settings more organized I split the earlier Basic-Settings page into two separate pages namely: Packet Drop and Packet Delay. So this way it is simple to understand settings according to their functionality.

TOFFEE (and TOFFEE-DataCenter) optimized Mobile Wireless Backhaul Networks ↗
Saturday' 13-Mar-2021
TOFFEE can be used to optimize expensive Wireless backhaul network infrastructure. TOFFEE can be deployed over existing slow or often outdated old backhaul networks too. This will leverage mobile ISPs and network service providers to reduce their bulk IT CapEx and OpEx Costs.

Tracking Live Network Application Data - in a WAN Acceleration (WAN Optimization) Device ↗
Saturday' 13-Mar-2021

Moon Base and Space Colonization - First we need fast InterPlanetary Internet ↗
Saturday' 13-Mar-2021

Power consumption of my Home Lab devices for research ↗
Saturday' 13-Mar-2021
Here is my power-consumption measurements of various devices deployed within my home lab. I measured via my kill-a-watt sort of power-meter which is fairly reliable and accurate. I checked its accuracy with various standard load such as Philips LED laps and other constant power-consuming devices to make sure that the power-meter is precise.

Watch on Youtube - [1888//1] Deep Space Communication - Episode1 - Introduction ↗


Bitcoin Mining - Blockchain Technology - Network Optimization via TOFFEE Data-Center WAN Optimization ↗
Saturday' 13-Mar-2021
Bitcoin Mining - Blockchain Technology - Network Optimization via TOFFEE Data-Center WAN Optimization

First TOFFEE Code Release ↗
Saturday' 13-Mar-2021
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.

TOFFEE (and TOFFEE-DataCenter) deployment in Large Infrastructure and or ISP Networks ↗
Saturday' 13-Mar-2021
Large Infrastructure or ISP setup: In case if you are an ISP and interested in deploying a large customer WAN Optimized network or an add-on enhanced (WAN Optimized) network for select few customers, then you can deploy something as shown below. Although this case is not meant for hobby/DIY users. This is a feasible solution for high-end professional application and the same can be deployed.

TOFFEE-Mocha WAN Emulation software development - Update: 19-July-2016 ↗
Saturday' 13-Mar-2021
Today I refined the first page consolidated report graphs. TOFFEE-Mocha (unlike TOFFEE) is a WAN Emulator, so the graphs are supposed to highlight this purpose and should display the overall network activity. Unlike TOFFEE, the TOFFEE-Mocha report should contain in general what is received versus what is sent across the wire. In case if the packet drop feature is enabled, you should see few missing bytes and packets. Similarly in future I may support packet duplication feature, in that case you may see more packets/bytes sent versus the packets/bytes actually received.



Featured Educational Video:
Watch on Youtube - [435//1] 0x1d3 Who gets Laid off (or Fired) during a recession ? #TheLinuxChannel #KiranKankipati ↗

Demo TOFFEE-DataCenter WAN Optimization packaging feature ↗
Saturday' 13-Mar-2021

TOFFEE (and TOFFEE-DataCenter) optimized Mobile Wireless Backhaul Networks ↗
Saturday' 13-Mar-2021
TOFFEE can be used to optimize expensive Wireless backhaul network infrastructure. TOFFEE can be deployed over existing slow or often outdated old backhaul networks too. This will leverage mobile ISPs and network service providers to reduce their bulk IT CapEx and OpEx Costs.

TOFFEE-DataCenter with GlusterFS Storage Cluster ↗
Saturday' 13-Mar-2021

Timelapse Screen Capture of TOFFEE-DataCenter Network Acceleration - with new RRDtool graph support ↗
Saturday' 13-Mar-2021
Timelapse Screen Capture of TOFFEE-DataCenter Network Acceleration - with new RRDtool graph support




TOFFEE-Mocha WAN Emulation software development - Update: 15-July-2016 ↗
Saturday' 13-Mar-2021
Today I completed doing all the changes which are meant for the new upcoming TOFFEE-Mocha release. I have increased the resolution and the range of all factor variables. Instead 1 to 10 range now they have a range of 1 to 30. Unlike before the value 1 means it is lot more intense (or in some cases less intense) and the uppermost value 30 means lot less intense (or in some cases lot intense).



Research :: Optimization of network data (WAN Optimization) at various levels:
Network File level network data WAN Optimization


Learn Linux Systems Software and Kernel Programming:
Linux, Kernel, Networking and Systems-Software online classes [CDN]


Hardware Compression and Decompression Accelerator Cards:
TOFFEE Architecture with Compression and Decompression Accelerator Card [CDN]


TOFFEE-DataCenter on a Dell Server - Intel Xeon E5645 CPU:
TOFFEE-DataCenter screenshots on a Dual CPU - Intel(R) Xeon(R) CPU E5645 @ 2.40GHz - Dell Server