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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

Recommended Topics:

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Demo TOFFEE-DataCenter WAN Optimization packaging feature ↗
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Internet optimization through TOFFEE-DataCenter WAN Optimization Demo ↗
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First TOFFEE-Mocha Code Release ↗
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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.

TOFFEE Documentation :: TOFFEE-1.1.24-3-rpi2 ↗
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Here is my VLOG Youtube video of the same which includes details about version release notes, future road-map and so on. The TOFFEE release is highly optimized and customized for hardware platforms such as x86-64 based Intel NUC and other Intel mobile computing platforms such as laptops and so on. This version (or release) is not suited and so not recommended to be used for high-end desktop and server hardware platform.

TOFFEE-Mocha WAN Emulator Jitter Feature ↗
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PiPG - Raspberry Pi Network Packet Generator ↗
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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

VPN Network Optimization via TOFFEE WAN Optimization ↗
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VPN Networks may degrade network performance due to various packet processing overheads such as encryption and by adding extra network protocol header(s) (such as IPv4/IPv6, IPSec, etc). This may inflate near MTU sized packets and causes excessive packet fragmentation. Here are the few examples of packet processing involved in a VPN (or a VPN like) Tunnel. With TOFFEE you can optimize these packets even before they get processed on to a VPN device. TOFFEE optimizes packet contents (application payload and transport headers) so that these TOFFEE optimized packets when they get processed by VPN devices (or VPN software stack) they may never need further packet fragmentation. Here is a deployment scenario of TOFFEE with VPN devices.

First TOFFEE-Mocha Code Release ↗
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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.

Network Latency and Bandwidth Assessment - for Network Admins and Infrastructure Architects ↗
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Featured Educational Video:
Watch on Youtube - [1836//1] x257 tp-link UE300 Linux Kernel Realtek Driver Codewalk rtl8153a-3 r8152 USB 3.0 to Gigabit - Part1 ↗

TOFFEE (and TOFFEE-DataCenter) deployment with VPN devices ↗
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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.

Demo TOFFEE_DataCenter WAN Optimization VM (in VirtualBox) Test Setup ↗
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Demo TOFFEE_DataCenter WAN Optimization VM (in VirtualBox) Test Setup

Building my own CDN - choosing a web-hosting to deploy my CDN - Update: 28-July-2016 ↗
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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.

The TOFFEE Project :: TOFFEE-Mocha :: WAN Emulator ↗
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The TOFFEE Project :: TOFFEE-Mocha :: Linux Open-Source WAN Emulator


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.


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