VIDEOS 》 TOFFEE-Mocha WAN Emulator Jitter Feature

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.

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

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.

Here is a complete log of my lab battery purchase, service record which I maintain in Google drive. These I use for my home (or my family generic use) as well as a part of my home lab. I maintain a detailed log this way to monitor the failure rate of these batteries. This will allow me to select a specific brand/model which has higher success rate and to monitor any premature failure/expiry. The service log helps me to monitor and schedule the next service routine so that I can maintain these batteries in tip-top condition.

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.

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.