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RESEARCH 》 Power consumption of my Home Lab devices for research

AMD RYZEN 3 1200 - FreeNAS Storage array build
  • CPU: AMD Ryzen 3 1200 (4 cores/4 threads)
  • RAM: Corsair Vengeance 8GB DDR4 LPX 2400MHz C16 Kit
  • Motherboard: Gigabyte GA-A320M-HD2 AM44
  • Graphics/Display: Asus Geforce 210GT 1GB DDR3
  • PSU: Circle CPH698V12-400
  • Storage: WDC WD10JPVX-75JC3T0 - WD 1TB HDD
System BIOS53 watts
Idle System (Linux Ubuntu OS)52 watts
Casual browsing53 watts
Youtube video playback60 watts
Kernel compilation with 4-threads "make -j4" (99% load)74 watts
Kernel compilation with 3-threads "make -j3" (80% load)71 watts

My Intel Core i7-5820K - Desktop build
  • CPU: Intel Core i7-5820K (6 cores/12 threads)
  • RAM: Corsair PC2800 DDR4 14GB Kit
  • Motherboard: Gigabyte X99-UD4
  • Graphics/Display: Asus Geforce 210GT 1GB DDR3
  • PSU: Corsair VS450
  • CPU Liquid Cooling system: Cooler Master Nepton 240m
  • Storage: Transcend TS128GSSD370 128GB SSD
Idle System (Linux Ubuntu OS)70 watts
System BIOS90 watts
Linux kernel compilation (80%) load150 watts

My Intel Celeron CPU 1037U Mini PC WAN Optimization Device
  • CPU: Intel Celeron CPU 1037U
  • RAM: DDR3 PC3L 4GB
  • Storage: Transcend TS128GSSD370 128GB SSD
Idle System (Linux Ubuntu OS)18-20 watts
System BIOS16.5 watts
Linux kernel compilation (95%) load21-24 watts

My HP Envy 15-J111TX Laptop
  • CPU: Intel Corei7-4700MQ
  • RAM: DDR3 PC3L 12GB
  • Storage: WD Blue 250GB Scorpio HDD
Idle System (Linux Ubuntu OS) charging44 watts
Idle System (Linux Ubuntu OS) charged15 watts
Poweroff charging28 watts
Poweroff charged0.1 watts
Poweron charged suspend0.75 watts
Linux kernel compilation (95%) load charging90 watts
Linux kernel compilation (95%) load charged69 watts

My Dell 15R 5537 Laptop
  • CPU: Intel Corei7-4500U
  • RAM: DDR3 PC3L 8GB
  • Storage: Seagate 320GB Momentus HDD
Idle System (Linux Ubuntu OS) charging42 watts
Idle System (Linux Ubuntu OS) charged10 watts
Poweroff charging29 watts
Poweroff charged0.1 watts
Poweron charged suspend0.70 watts
Linux kernel compilation (95%) load charging60 watts
Linux kernel compilation (95%) load charged30 watts

My Acer Aspire 4810T Laptop
  • CPU: Intel Core Solo SU3500 1.4 GHz
  • RAM: DDR3 PC3 4GB
  • Storage: WD Blue 250GB Scorpio HDD
  * No Battery, so no charging.
Idle System (Linux Manjaro OS)16.23 watts
System BIOS24.30 watts
Casual Browsing22.27 watts
Youtube Playback22.45 watts

Raspberry Pi2 Device
  • Powered via 2Amp USB power-supply
  • Raspbian OS
  • USB mouse and USB keyboard connected
Casual browsing2.6 - 3 watts
Youtube video playback (25% load)3 - 3.5 watts
Kernel compilation with 4-threads "make -j4" (99% load)3.9 - 4 watts
Kernel compilation with 3-threads "make -j3"3.67 - 3.75 watts
idle device with no keyboard and no mouse2.08 - 2.1 watts

NETGEAR RN104 ReadyNAS
  • 2x 2.5'' Laptop HDD drives
  • 2x 3.5'' Desktop HDD drives
  • Single x-RAID volume with 4 HDD drives
Device off but plugged-in0.58 watts
Idle device after booting28 watts
File copy (write operation)28.7 watts
RAID Volume scrub operation29.5 watts

APC BX600C-IN UPS - APC Back-UPS 600(UPS not powered-on but connected to live power socket)
Standby Charging13.5 watts
Standby not-Charging7.8 watts

APC BX600CI-IN UPS - APC Back-UPS 600(UPS not powered-on but connected to live power socket)
Standby Charging9.5 watts
Standby not-Charging10-0.9 watts

BenQ LED Monitor 24'' GW2470HM
off plugged-in0.00 watts
Dim11.7 watts

LG LCD TV Monitor 23'' M237WA-PT
off plugged-in0.8 watts
Dim33 watts
Bright45 watts

Samsung LCD Monitor 22'' 2243NWX
off plugged-in0.7 watts
Dim20 watts
Bright33.5 watts

Power consumption of my Home Lab devices for research

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.

So far I maintained this data in my personal Google drive spreadsheet documents. But now I thought perhaps its good to share these numbers so that it is useful for various users to access their equipment such as:

  • decide UPS and battery backup ratings
  • off-grid solar power installations
  • choose new upgraded hardware which consumes less power and deliver better performance such as SSD over traditional HDD, new CPU, new Monitor, new laptop, servers, desktops and so on. And discard obsolete old hardware.
  • choosing the right PSU (power supply unit) for your desktop PC build

Before posting this article I shot a VLOG regarding the same and posted in my Youtube channel The Linux Channel. You can kindly watch the same:

Explore my lab's historical month wise power-usage trends: I started logging my entire lab monthly power-consumption readings. You can read the article HERE.

Off-Grid Solar Power System for Raspberry Pi: 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. Kindly read my complete article about the same HERE.
Off-Grid Solar Power System for Raspberry Pi



Suggested Topics:


Generic Home Lab Research

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


Temas recomendados:

Building my own CDN - Minify Script files - Update: 23-July-2016 ↗
Saturday' 13-Mar-2021
One of the suggestions Google PageSpeed Insights tool suggested for The TOFFEE Project website is to minify the css and java script files. Minify Script files: When you read online about minification of your web script files, often they highlight file size savings and thus resulting faster download time and better website performance.

Skype VOIP Data - WAN Acceleration ↗
Saturday' 13-Mar-2021

Building my own CDN - Google PageSpeed Insights - Update: 22-Jul-2016 ↗
Saturday' 13-Mar-2021
Ever since after I launched my new The TOFFEE Project website on 1-May'2016, I can see there is a steep increase in traffic. Soon after the launch when I monitored its Alexa rankings it was reporting about 12 Million or so. But once it is getting more and more traffic the Alexa rankings shot up and now currently it shows around 2 Million (as on 22-July-2016). Alexa is an excellent tool to monitor your overall website global ranking and indirectly its performance. Unlike Google Analytics which is bound one or other way into Google's SEO. Alexa gives you a second opinion about your website's growth.

TOFFEE (and TOFFEE-DataCenter) optimized Wireless Mesh-Networks - B.A.T.M.A.N [open-mesh.org (Open Mesh)] ↗
Saturday' 13-Mar-2021
TOFFEE/TOFFEE-DataCenter can be used to optimize Ad-Hoc Mobile Wireless Mesh-Networks. To learn more about the same here are some references: B.A.T.M.A.N. - https://en.wikipedia.org/wiki/B.A.T.M.A.N. Mobile ad hoc network (MANET) - https://en.wikipedia.org/wiki/Mobile_ad_hoc_network Wireless ad hoc network (WANET) - https://en.wikipedia.org/wiki/Wireless_ad_hoc_network open-mesh.org (Open Mesh) Wiki - https://www.open-mesh.org/projects/open-mesh/wiki

TCP Tune-up and Performance Analysis Graphs - Congestion Control - Research - Dos and Don'ts ↗
Saturday' 13-Mar-2021

Bulk Ping Tests - WAN Acceleration ↗
Saturday' 13-Mar-2021



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.

Setting up a WAN Emulator within VirtualBox ↗
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 - [943//1] x23e TrueNAS ZFS Pool Resilver over and over again issue | ZFS NAS Storage | Forever Resilver ↗

Building my own CDN - Minify Script files - Update: 23-July-2016 ↗
Saturday' 13-Mar-2021
One of the suggestions Google PageSpeed Insights tool suggested for The TOFFEE Project website is to minify the css and java script files. Minify Script files: When you read online about minification of your web script files, often they highlight file size savings and thus resulting faster download time and better website performance.

The TOFFEE Project :: TOFFEE-DataCenter :: WAN Optimization ↗
Saturday' 13-Mar-2021
The TOFFEE Project :: TOFFEE-DataCenter :: Linux Open-Source WAN Optimization

TOFFEE-DataCenter a TOFFEE variant for Data Center applications ↗
Saturday' 13-Mar-2021

Demo TOFFEE_DataCenter WAN Optimization VM (in VirtualBox) Test Setup ↗
Saturday' 13-Mar-2021
Demo TOFFEE_DataCenter WAN Optimization VM (in VirtualBox) Test Setup




TOFFEE-Mocha WAN Emulation software development - Update: 20-Oct-2016 ↗
Saturday' 13-Mar-2021
I was doing some specific tests in my TOFFEE and TOFFEE-DataCenter (WAN optimization) scenarios such as variable upload and download speeds. And I was also doing some experiments with speedtest.net and I did some of these tests with TOFFEE-Mocha. I realized there is a case that I can introduce asymmetric constant delays so that you can get different download speed and a different upload speed. And in some cases much faster download speeds and relatively slower upload speeds.



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