DOCUMENTATION 》 Tweaking Network Latency - Live Demo - via TOFFEE-DataCenter

When you choose to use your Raspberry Pi device as your IoT based remote weather station or if you are building Linux kernel (like kernel compilation) within the same, you need a good uninterrupted power source (UPS). But if you are using it on site or in some research camping location you can choose to power your Raspberry Pi device with your custom off-grid solar power source.

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.

Download TOFFEE-DATACENTER-1.3.25-1-portable.tar.xz via Google Drive share: platform independent (portable) source: TOFFEE-DATACENTER-1.2.2-1-portable.tar.xz * Alternatively download from SOURCEFORGE project site. * Here are the TOFFEE-DataCenter supported features. * To know more about the project kindly refer TOFFEE-Datacenter Documentation, News and Updates

The TOFFEE Project website is hosted on Inmotion Hosting. And so I am looking for alternate hosting provider to build my first CDN node. My plan is to make multiple sub-domains of my website such as cdn1.the-toffee-project.org, cdn2.the-toffee-project.org and point each of this corresponding subdomain(s) to various alternative web hosting servers geographically spread across the world. Sometimes choosing the same vendor for multiple CDN nodes may result multiple servers existing in the data-center. And this becomes an issue if there is some catastrophic network disaster.

You can build a basic TOFFEE WAN Optimization hardware completely in software layer (i.e its networking data-plane and control-plane). And if you are a product manufacturer you can make commercial WAN Optimization products with TOFFEE with software layer alone. And if you choose to improve its performance, you can use any third-party PCIe Compression Accelerator cards.

TrafficSqueezer is an open-source WAN Optimization project. TrafficSqueezer is mainly a research project which is started around mid-2006. It is initially started as a research (or prototype) code even before it is officially registered in Sourceforge.net. But this code is just primitive user-space raw socket modules. This is later refined and a pre-alpha version is created. Followed by which Alpha release. This prototype code is moved from user-space to Linux Kernel (Kernel Space) and then the journey begin in terms of making a serious WAN Optimization solution. Once the pre-beta and beta releases are complete the mainstream series is started.

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.

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.

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.

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.