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RESEARCH 》 Optimization of network data (WAN Optimization) at various levels

WAN Network data can be optimized at various levels depending upon the network applications, protocols, topology and use-cases. So the amount of data you can optimize will depend on the strategy you choose to optimize.

Network Packet level optimization: You can optimize your network data down to individual packets. This may be useful to optimize discrete network data such as VoIP and streaming networking applications. So depending on your network you can do frame level optimization in case if it is a Layer-2 switched network something like MPLS/VPLS scenarios. And in case it is a IP based routed networks you can do IP packet level optimization. So that the IP-header is intact where-as its other protocol headers and the payload is optimized. Hence packet level optimization suits for discrete network data and corresponding network applications.
Network Packet level network data WAN Optimization

Session level optimization: Session level (or session based) optimization is suited for complete/full sessions bound by a network connection. For example TCP-connection. A remote MySQL or Oracle database access involves a TCP-connection (or a session). So in this case we are not talking about discrete packet level access (although a session will always comprise multiple packet transfers to and fro) and we are not talking about individual file-level access, instead it is a session-level bulk data transfers. In this case we can employ different network optimization strategy so that the entire session can be optimized.
Network Session level network data WAN Optimization

File level optimization: Last but not least a file-level optimization involves a typical file-download/file-upload scenario such as HTTP, FTP and so on. In this case in general even before sending across the wire we can do lossy (and lossless) compression of these files depending on its contents. But when it is being transferred across the network we can employ a network optimization strategy where an entire file transfer is optimized. We can also implement both above discussed techniques such as network packet-level and session-level to optimize file-level network data transfer. Some of the examples which comes in this category are CDN networks, HTTP Cache Proxy (such as Squid-Cache) and so on.
Network File level network data WAN Optimization

Case study :: Dolby Servers in movie theaters: Movie theaters these days get digitized extremely high-quality movie files from film producers/distributor channels. Since these files are so huge they are transferred via high-speed wire (fibre-optic) networks. But in case if the movie theaters lack high-speed network connectivity then they ship these movie copies on a regular computer hard-drive. This is a good case study and use-case where file-level network data optimization can be deployed.
Here are some interesting videos on Digital Cinema movie servers and projection technology:


Here is my detailed video of the same:

In case if you are having a company and if you are looking for ways to optimize your network, performance tune-up and or building network optimization product(s) (which may or may not include porting/integrating TOFFEE on to your product), in that case I can offer my technical consultation services. If you are interested you can contact me for the same.



Suggested Topics:


WAN Optimization and Network Optimization

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


Recommended Topics:

PiPG - Raspberry Pi Network Packet Generator ↗
Saturday' 13-Mar-2021
PiPG is a powerful and yet simple Raspberry Pi Network Packet Generator. With PiPG you can now fabricate custom network packets and send via any Network Interface. Supports all kinds of standard Network Ports (Linux Kernel driver generated) such as Physical Network Interface ports, and an array of virtual ports such as loopback, tun/tap, bridge, etc. indispensable tool for: Network Debugging, Testing and Performance analysis Network Administrators Students Network R&D Protocol Analysis and Study Network Software Development Compliance Testing Ethical Hackers you can generate the following test traffic: L2-Bridging/Slow protocols: STP, LACP, OAM, LLDP, EAP, etc Routing protocols: RIPv1, RIPv2, IGMPv1, IGMPv2, OSPF, IS-IS, EIGRP, HSRP, VRRP, etc Proprietary protocols: CISCO, etc Generic: IPv4 TCP/UDP, etc Malformed random packets

Introducing TOFFEE-DataCenter ↗
Saturday' 13-Mar-2021
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.

Internet optimization through TOFFEE-DataCenter WAN Optimization Demo ↗
Saturday' 13-Mar-2021

Network Latency in WAN Networks and performance optimization ↗
Saturday' 13-Mar-2021
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.

TOFFEE (and TOFFEE-DataCenter) deployment with VPN devices ↗
Saturday' 13-Mar-2021
In case if you need to deploy TOFFEE along with your existing VPN devices you can deploy the same as shown below. This will allow your VPN devices to encrypt your TOFFEE WAN Optimized network data. NOTE: Make sure about the VPN deployment topology done in the right order. Else TOFFEE (LAN side) may get VPN encrypted packets which may not be possible (and or difficult) to further optimize. Hence always make sure to deploy them in a topology suggested below so that TOFFEE devices are out of VPN tunnel.

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 DataCenter WAN Optimization - Google Hangouts demo and VOIP Optimization ↗
Saturday' 13-Mar-2021
TOFFEE DataCenter WAN Optimization - Google Hangouts demo and VOIP Optimization

Tweaking Network Latency - Live Demo - via TOFFEE-DataCenter ↗
Saturday' 13-Mar-2021

TOFFEE-Mocha WAN emulator Lab deployment and topology guide ↗
Saturday' 13-Mar-2021

Why TOFFEE is forked from TrafficSqueezer ↗
Saturday' 13-Mar-2021
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.



Featured Educational Video:
Watch on Youtube - [4073//1] 0x1c9 NAS OS | Expert's take on FreeNAS vs UNRAID | My two cents | Best Tips ↗

My sample Wireshark packet capture files for research ↗
Saturday' 13-Mar-2021
I have a huge repository (or collection) of sample Wireshark packet capture files for reference. I use them extensively for research and development of TOFFEE as well to understand various protocol PDUs and protocol standards. I personally collected various test captures via Wireshark during my test and experimental research setup during the course of TOFFEE development. Say if you are a student and learning Networking and or say VoIP data and VoIP packets, you can analyse my VoIP sample Wireshark captures. Or in other case assume you are doing some quick research (or development) and want to refer few handful of VoIP packets then you can download and analyse my sample packet capture files.

Off-Grid Solar Power System for Raspberry Pi ↗
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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.

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.

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).




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.



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


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