TOFFEEプロジェクト
ホームドキュメンテーション更新ビデオ研究ダウンロードスポンサー接触


DOCUMENTATION 》 TOFFEE hardware selection guide

Language :: Portuguese

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.

But the focus and assumption in this guide is that you are using a generic computing platform such as PC/server/IoT device to build a WAN Optimization device with TOFFEE platform, since hardware offload option is only feasible for large OEMs and other such commercial equipment manufacturers. So it is important that based on your WAN speeds within which these TOFFEE devices are to be deployed, you need to choose your hardware specifications as suggested in this guide.

Understanding CPU Benchmarks:
Introducing TrueBench - a high resolution CPU benchmarking system:
TrueBench
TrueBench is an unique benchmarking system in which the core system performance and efficiency parameters are measured at extreme high resolution in the order of several million/billion µ-seconds for a given specific task. TrueBench is a part of The TOFFEE Project research. For more details: visit TrueBench

Applications(use-cases) of TrueBench:

  • building low-latency high performance networking devices
  • embedded/SoC CPU (platform) evaluation
  • server and datacenter hardware evaluation
  • new product design/architecture evaluation
  • scientific applications (such as HPC, Super-Computers, etc)

Choosing the CPU for your TOFFEE device:
Here is a definitive guide which will help you to choose the CPU for your TOFFEE WAN Optimization device. TOFFEE source-code is highly modular. It can scale-up or scale-down its optimization level based on your hardware and more precisely CPU processing potential. Having said that lets assume you have enabled all optimization levels. In that context here is the table which gives an idea to choose your CPU according to your deployment specific WAN network speeds:

NOTE: This table is derived after extensive trials, testing and research over several years. And as well a co-relation between CPU's benchmarks (such as TrueBench) single thread performance benchmarks vs standard multi-thread benchmarks vs TOFFEE's real-time performance during extensive high-load packet processing.

CPU / Hardware Specs TrueBench Score WAN Speeds
Raspberry Pi3 Model B 1.2GHz 64-bit quad-core ARMv8; 1GB RAM 1,310,619,137 <= 5-10Mbps
ARM Cortex-A53(ARMv8 64bit) (ODROID-C2) 1.50 GHz, Quad Core, ODROID-C2 - IoT single board computer(SBC) 949,003,080 <= 10-20Mbps
Intel Atom D525 1.80 GHz, Dual Core, 13 W TDP 874,076,069 <= 20-30Mbps
High-end Server:
Intel Xeon E3-1240 v3
91,632,198 <= 300-600Mbps
High-end Desktop:
Intel core i7 6700K
44,200,382 <= 700-900Mbps (1Gbps approx)

So in case if you are building your own WAN Optimization device (or in general any networking device), you can benchmark with TrueBench (as suggested in the TrueBench website) and submit me your results (screen output).

TOFFEE-DataCenter: For the same/similar above specs, TOFFEE-DataCenter should provide only half the performance (WAN speeds) as compared to TOFFEE. The reason being TOFFEE-DataCenter does user-space packet processing and it is lot more versatile, flexible and modular. Due to this TOFFEE-DataCenter is capable of optimizing the data far more than TOFFEE.

Choosing the RAM/memory for your TOFFEE device:
TOFFEE device just like any typical Linux system needs just minimum amount of RAM. The entire data processing of packets will take place in your RAM. By no means TOFFEE uses your harddisk (or any secondary storage) space for packet processing. So whether it is Gigabit WAN or within 100Mbps speeds, choose RAM which has around 4-8GB of overall capacity.

However to achieve maximum optimal performance especially for high-speed WAN links, I highly recommend you to choose RAM with maximum speed. Such as DDR4 (with 2.8GHz or so). This gives the best CPU<>Memory bus interconnect speeds and improves your packet processing capabilities of your TOFFEE device. This is also sometimes applicable not just TOFFEE hardware build, but any such network devices which deals with real-time data/packet processing.

Choosing server hardware for Gigabit speeds (1G/10G and so on):Here are some examples:

Lanner FW-8894 :: 1U High Performance x86 (Dual CPU) Network Appliance for Enterprise Firewall, UTM and IPS
Lanner FW-8894
Lanner FW-8894

Lanner NCA-5210 :: 1U Mid-range Modular x86 (Single CPU) Network Appliance for Next Generation Firewall, UTM and Web Security
Lanner NCA-5210
Lanner NCA-5210

Lanner NCA-5510 :: 1U High Performance x86 (Single CPU) Network Appliance for Enterprise Firewall, UTM and IPS
Lanner NCA-5510
Lanner NCA-5510
* image courtesy Lanner Electronics Inc.

A sample low-performance TOFFEE Hardware which I built:

Intel Celeron C1037U fanless hardware
Intel Celeron C1037U fanless hardware

Intel Celeron C1037U fanless hardware

Intel Celeron C1037U fanless hardware

References:



Suggested Topics:


TOFFEE - WAN Optimization


Categories

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


おすすめトピック:

Riverbed and Silver Peak WAN Optimization vs TOFFEE-DataCenter (TOFFEE and or TrafficSqueezer) - FAQ ↗
Saturday' 13-Mar-2021

TOFFEE-Mocha Documentation :: TOFFEE-Mocha-1.0.14-1-x86_64 ↗
Saturday' 13-Mar-2021

TOFFEE Data-Center optimized Internet of Things (IoT) Platform ↗
Saturday' 13-Mar-2021

LoRaWAN - Network Optimization via TOFFEE WAN Optimization ↗
Saturday' 13-Mar-2021
LoRaWAN - Network Optimization via TOFFEE WAN Optimization

TOFFEE Data-Center WAN Optimization deployment in Big Data Analytics ↗
Saturday' 13-Mar-2021

Live demo - Data Transfer - High bandwidth to Low bandwidth ↗
Saturday' 13-Mar-2021
I always wanted to do some real experiments and research on packet flow patterns from High-bandwidth to Low-bandwidth networks via networking devices. This is something can be analyzed via capturing Network stack buffer data and other parameters, bench-marking, and so on. But eventually the data-transfer nature and other aspects is often contaminated due to the underlying OS and the way Network stack is implemented. So to understand the nature of packet flow from Higher to Lower bandwidth and vice-versa such as Lower to higher bandwidth, I thought I experiment with various tools and things which physically we can observe this phenomena.

Youtubeで見る - [889//1] 280 WAN Optimization - Animated demo of Packet Optimization in TOFFEE-DataCenter ↗


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.

Benchmark Raspberry Pi and other embedded SoC with TrueBench ↗
Saturday' 13-Mar-2021
TrueBench is an unique open-source benchmarking system in which the core system performance and efficiency parameters are measured at extreme high resolution in the order of several million/billion µ-seconds for a given specific task. TrueBench is a part of The TOFFEE Project research. With TrueBench Raspberry Pi 3, Raspberry Pi 2B and Raspberry Pi 2 are benchmarked and you can do a comparative analysis with standard mainstream x86 devices.

Optimization of network data (WAN Optimization) at various levels ↗
Saturday' 13-Mar-2021
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. Such as: Network Packet level optimization, Session level optimization, File level optimization, etc.

First TOFFEE-Mocha Code Release ↗
Saturday' 13-Mar-2021
TOFFEE-Mocha is my dream project which I thought working on it since several years. I want to make a WAN emulation software which is straight forward and simple to use. I used tc scripts along with iptables for testing my TOFFEE (and TrafficSqueezer before TOFFEE) and I am not quite satisfied with the same. As one can understand these scripts are not meant for WAN emulation.



Featured Educational Video:
Youtubeで見る - [8613//1] x254 Kernel Init Code without Kernel Module - Kernel Programming Tip #linode ↗

Streaming CDN Types ↗
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.

Advantages of CDN - Content Delivery Networks or Content Distribution Networks ↗
Saturday' 13-Mar-2021

TrueBench - Linux CPU Benchmarking system ↗
Saturday' 13-Mar-2021
TrueBench is an unique open-source benchmarking system in which the core system performance and efficiency parameters are measured at extreme high resolution in the order of several million/billion µ-seconds for a given specific task. TrueBench is a part of The TOFFEE Project research.




WAN Optimization Network Stack Architecture - Linux Kernel vs Intel DPDK vs Custom Packet Forward ↗
Saturday' 13-Mar-2021



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


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