Looking back over my lifetime the superstars of technology in some ways did us disservice. I applaud Mr. Gates, the late Mr Jobs and others’ achievements in making technology seamless and universally accessible, but by doing so they distanced us from it, making it mysterious. Most kids have little understanding of how the machines that infest their lives work, which is a shame. It is also undesirable to most since we end up in a world where a few are able to exploit the many with their clever wizardry – look only to Apple’s eye-watering profits which recently surpassed mighty Google’s revenues!

An old passion reignited

I was fortunate to have been brought up by an electronics engineer (my Dad) who had a keen interest in computers. I have fond memories of him teaching me how to mock things up with a bread board (a rapid prototyping system for designing electronic circuits) and the nuances of good soldering. Aged 9 I was making simple burglar alarm systems so I could tell when my sister was trying to sneak into my bedroom, by 11 I was making my BBC Master computer do real world interactions via its parrallel port and some circuitry I’d rigged up and at 12 I built a model hovercraft. Making such devices is not actually that complicated!

I’m ashamed to admit that I allowed those passions to fade. I moved on to programming instead and immersed myself in the virtual world, then the Internet, but in the last year my passion for real-world electronics and computer interfacing have been rekindled. I’m delighted to report that I am also very much not alone in this! Perhaps the best known “movement” are Hackspaces – places where like-minded hackers can get together, pool ideas and resources and make cool stuff.

One of the technologies that has really helped us hackers is Arduino – a programmable, open source, simple to use board for under £20 that you can hook up to your own electronics to do all sorts of things. Combining computing and home-brew electronics just got practical again, whereas during the age of the PC it was frankly rather impractical for most since you needed quite advanced skills to directly interface basic electronics with a PC and they are expensive and large so you can’t stick one in a box to run your door bell, for instance.

In short, modern personal computers had distanced the user from the underlying technology compared to my old BBC Master which has made them accessible to a wider audience but also limited innovation to a small number of well-resourced companies. Even Linux did not help much since although the operating system is more accessible to a hacker the underlying hardware was still a PC and not really designed to have bits of DIY circuitry attached. But that is changing.

The Internet of Things

I’m not suggesting that hacking with home-brew electronics and small computers will bring the UK out of a double dip recession. What has changed though is the addition of ubiquitous network connectivity into that mixture along with an acceleration of innovation.

What I am in fact predicting is that 2012 will be the year that the Internet of Things really takes off, driven by the hacker community.

It is already here, but what will rocket-boost it is the hacker community empowered by cheap open source hardware platforms. There are two platforms in particular I’d like to highlight: Nanode and Raspberry PI. Nanode is an Arduino with the capability to speak over IP built in conveniently. It is actually quite a pain to make an Arduino communicate via IP or even serial by itself (I’ve tried, trust me!) but Nanodes make it easy, and they are dead-cheap – under £20 for a kit and about an hour to solder the components onto the PCB.

Even more exciting is the British Raspberry PI; an ARM GNU/Linux computer for $25. ARM are the British central processor chips that used to be in Acorn computers and are now powering the world’s smart phones, tablets, netbooks and more. With such a cheap and powerful computer available the possibilities are no longer limited by money, but rather by one’s imagination. I am not suggesting that all those new devices will be one-off non-commercial affairs either. As we have seen with the ‘Web and with smart phones many of the services and apps that have been developed have gone on to become major commercial offerings, and I would expect the same of the exponentially-increasing network-connected devices littering our lives. The revolutionary aspect will be, I believe, that everyday people will drive the innovations rather than established corporations.

Limitless possibilities

To give you some examples, I have a few Nanode projects on the go myself. First I’m using one to monitor the moisture level in the soil of my sole houseplant which was inherited from my Mum who in turn got it from my grandfather. I’m hopeless at remembering to water things and it is a very precious plant, so I have applied technology to the problem. The circuitry is very simple and rather than worry about polling data and doing charts etc. myself my next step is going to be to get it publishing data to Pachube, a cloud-based service to do all the useful stuff you want with data like drawing charts, sharing it with people and delivering notifications to your phone.

Another more commercial project is a temperature and humidity monitor (a Nanode with a SHT15 sensor) to monitor the environment in my cupboard under the stairs which is my home’s nerve centre (I’ve noticed it is getting a bit hot thanks to the collection of IT kit in there). My plan is to use the eventual design in our data centres as well – why pay some vendor £hundreds for an IP data centre environmental sensor when we can get a job lot built for us on the cheap?

I’ve got numerous other ideas and I’m not alone. Hackers are out there working on cheap-and-cheerful solutions for everything from home-care for the elderly to asset tracking in the field to home and industrial energy management. It does not stop with the individual applications either though; looking at the likes of Pachube one starts to realise the enormous potential of pooling and analyzing all the data we are starting to collect.

British invention

Britons are fabulous inventors – our history is steeped with examples of ingenuity – but we have arguably lost our way. I believe that it is time to correct that and that these low-cost, flexible, open source, community driven platforms are an ideal vehicle to reignite the nation’s passion for invention and innovation. Further, many of the most inspiring developments are happening right here in Blighty – Nanode and Raspberry PI are British and if you want to see something really cool check out these Arduino-based aerial drones.

With the Euro-zone teetering on the brink of collapse and a new recession looming we should fall back on our strengths and look to technology innovation to drive our economy forwards. ARM is the perfect example; they don’t make anything, that is all done in Asia, but they are enormously successful at creating the intellectual property and licensing it to a hungry and growing global market.

So, hackers of Britain, get out your soldering irons, make your way to your local Hackspace, share your ideas, ask the “stupid” questions (there is no such thing and have a go at bending technology to your will. We can all be wizards now!

When I recently took delivery of my magic mouse I was struck by how aptly it was named. If it were presented to someone only a few decades ago – a smooth pebble-like object which could be used to interact with a computer by moving it or merely brushing one’s fingers across its surface – might it not have appeared magical? Mr. Jobs’ elegant creations brought to life Arthur C Clarke’s maxim that any sufficiently advanced technology is indistinguishable from magic.

Adding to this, the world economy continues to stutter, teetering on the brink of another global recession fuelled this time by not the banks defaulting, but the prospect of entire governments being declared bankrupt. Is this really the time for fancy new technologies?

3D printing

Perhaps the most obvious transformational technology to pick as the one to watch would be 3D printing. It is hard to understate the likely impact of “printers” able to create almost any device object as common as personal computers are today, but we are quite a way from that point. At present they are relatively crude, able only to print a small range of types of plastic and quite expensive.

An interesting area to watch is the open source RepRap, which can be used to make some of the parts for additional copies of itself. The implications of machines that are able to make anything, including copies of themselves, are profound indeed, but I am not convinced that 2012 will be the year of 3D printers and fully automated manufacturing.

The Internet of Things into life

But no, I think the next big revolution will be something called the Internet of Things. So what is it? In this context I’m talking about all the Internet Protocol (IP) connected devices that litter our lives. Why does this matter? Well mainly because there are a lot of them – estimates of between 50 billion and 1 trillion by 2020 are out there. You might be thinking, “Nah, I only have a couple of computers, what are they on about?”. Well, I counted up all the IP devices in my home recently and got a surprise:

• 1 x Mac mini (our media computer – I recently cancelled Sky and we stream all TV)
• 1 x Cable modem with integrated Wireless Access Point
• 1 x ReadyNAS file server (for backups and storing large files such as movies)
• 1 x X-box
• 1 x Wii
• 2 x Mac Air Laptops
• 2 x HTC Desire Android smart phones
• 1 x Amazon Kindle
• 5 x IP CCTV security cameras
• 1 x CCTV system head unit
• 1 x Burgular alarm system
• 2 x Televisions
• 1 x Hi-fi amplifier

A total of twenty IP-connected devices! Now, I’m a well-off technologist so you could argue that I have more devices than most and that most people would not connect all their devices (like the TVs – all mine do is auto-update their firmware at present). However, first that list is for two people (my girlfriend and I) and second we are actually fairly minimalist with our technology and tend to have as few devices as possible; we have one laptop and phone each, only one pad device (the Kindle) between us, and a couple of other computers and consoles. Anyway, call it in round numbers 10 IP-connected devices each and assume there are 1bn people like us in the developed world and you get 10 billion devices in the West. Suddenly 50 billion in 8 years seems very likely, in fact if anything a bit low!

More addresses!

Until recently the potential for this explosion was also hampered by the fact that we were running out of IP addresses. IP addresses are codes like “78.31.108.54″ that are used to address machines on the Internet – that one happens to be my personal virtual machine. The old system is called IPv4 and each of the four parts of the code could be a maximum of 255, so the total possible addresses was about 256^4, 2^32, or about 4 billion (4 * 10^9). Some devices are inside home or office networks so don’t have an Internet address themselves, but if they could it would potentially accelerate the potential of the Internet of Things even more.

Recently new version of IP addressing, IPv6, has been rolled out which gives us vastly more – a mind-boggling 2^128 possible addresses, or about 3.4 * 10^38. As described in a lovely XKCD cartoon, it is unlikely that human society in anything resembling our current state will ever consume that many addresses, but I digress!

The peoples’ revolutions

For something to be a revolution you need a bit more than device proliferation though. Let’s take a step back and look at the last couple of decades and the other recent revolutions. I would like to contend that since the headline technology revolutions of my lifetime (personal computing and personal network connectivity) there have been two further major revolutions and that both of them have been community-driven, albeit reliant on the first two revolutions. As an aside, that is often the way of innovation, as in the words of W. Brian Arthur:

“Novel technologies form from combinations of existing ones, and in turn they become potential components for the construction of further technologies.”

The third technology revolution of my lifetime, and the first driven more by people than by institutions, was the World Wide Web, which grew organically without any central authority and whose content was created by people everywhere, especially in the beginning. I remember being at university and sitting in a tiny bedroom next to my room mate in the wee small hours while we both built our personal Web sites, borrowing bits from others who had gone before. Today the content is being generated by even more people now that the technical knowledge requirements have been reduced with systems like blogging and wikis.

The fourth revolution has been in software development communities. I’m cheating a bit and rolling two revolutions into one; first the open source software movement – generally free community-sourced and managed applications; second the accessible software development ecosystems that have been created for smart phones by companies like Apple and Google realising the awesome power of enabling the community to get creative with their platform. There are further examples as well, such as the popular Linux-Apache-MySQL-PHP (or Python, Perl etc) “stack” which millions of bedroom hackers and professional programmers alike use to rapidly develop their own Web applications; a free development platform created by the open source community.

The benefits of accessible app development platforms is fairly obvious (just look at all the things your smart phone can do), but amazingly some hard-headed business people are still in denial about open source software despite it being responsible for many systems that are now integral to our daily lives. The Linux operating system, to pick but one example, has proven to be massively reliable – more so on our experience than closed source Windows by a long way – and is completely free. Open source is an amazing example of functional communism at work. I’m a particular fan since I have built my entire business on open source technologies and thanks to them I’m able to undercut all my competitors and still make a healthy profit. Everyone wins!

You might be asking, “What about smart phones or social media? Are they not revolutions?”. Back in 2000 I had a Palm Pilot that could do quite a few smart phone type functions and Moore’s law has always predicted that we would have powerful computers in our pockets. Ubiquitous network connectivity is also key to smart phones but that too is a long-term trend. What has made smart phones really work compared to my old Palm Pilot has been the people-power behind the app development. As for social media, again I see that as more an evolution of technology; as far back as 1997 I was using Internet Relay Chat (IRC), usenet news and online forums, all arguably social media. It is the Web that is the revolution, driven people finding cool new ways to use that technology – social media being just a prominent example.

The hackers’ revolution

I believe that the fifth major technology revolution of my time will be the Internet of Things and that like other recent revolutions it will be powered by a community, in this case the hacker community, their innovative drive empowered by cheap open source hardware platforms.

I’m not suggesting that hardware hacking is anything new, but what has changed is the addition of ubiquitous network connectivity into the mix along with some cheap and flexible platforms such as Nanode (an Arduino board with ethernet attached) and Raspberry PI, a Linux computer for $25. Especially exciting is the fact that those innovations are both British.

In my next post I will describe how I think hacking is making a come back, how it will rocket-boost the Internet of Things revolution and how I believe that together it could be a real boon to our faltering economy.

I started with calculations based on our own power consumption (servers and in-datacentre network gear) and bandwidth output. We measure all power consumption and network activity, so all I had to do was design queries for our master data base.

Sampling one of our data centre suite’s energy consumption and bandwidth output, and dividing the former by the latter, gives a figure of 2.58 Watt-hours (Wh) per Megabyte (MB). That suite is our newest, and contains a mixture of Web hosting, application hosting, storage and other services. Some servers are used inefficiently at low utilisation, and some very efficiently, notable those which are part of our Miniserver VM^® grid.

For example, if we restrict the data to that from a selection of ten of our latest Miniserver VM^® host servers (quad-core 1U Dell Power Edge servers stuffed with RAM) the figure is only 0.61 Wh/MB, but I’m trying to be conservative here and make the calculations applicable to any Web-delivered service, not just the efficiently-run ones.

We must not forget the cooling and infrastructure losses (UPS, wiring etc). Our power usage efficacy (PUE) is about 1.4, but let’s err on the side of caution and add 50%, giving a total for electricity requirements at the data centre of 3.87 Wh/MB.

My educated guess of a typical 1U server’s embedded energy is 1,000 kWh (explanation here). If we assume a 3 year lifespan (it is actually more like 4-5 years in our case) then we get 333 kWh/year. Such a server uses about 100Watts continuously, or 1,100 kWh/year, so applying that ratio (1,100:333 = 3.3:1) we get an embedded energy cost of 0.78 Wh/MB.

The network and firewall boxes are probably in the same ball park in terms of embedded energy, however compared to servers there are very few of them: 1 switch per 30 servers, 1 router-firewall pair per ~200-500 servers, 1 border router pair per 2,000-20,000 servers. Therefore that equipment’s embedded energy is not significant in our sums. The same goes for the embedded energy of the data centre itself; when compared to the thousands of servers housed within, it rapidly becomes an insignificant factor. Rather than ignore it entirely, however, I shall add 10% to the embedded server energy factor (0.86 Wh/MB total) as an allowance for the embedded energy of the supporting infrastructure.

After some conversation with ISP friends we decided that the only really significant part of the network delivery energy will be the end points. Even though some big core routers consume kilo-Watts, they are shunting hundreds of gigabits per second, thus their power requirements are spread over a huge aggregation of data flows and rendered insignificant. The end points are the Digital Subscriber Line Access Multiplexers (DSLAMs – the big modems that send an ADSL signal down your phone line), and power for the home phone line itself.

According to the EU code of conduct for broadband equipment DSLAMs with more than 100 ports should use no more than about 1.3 Watts per port when active, so a fair high estimate of their average usage would be 1Watt. The phone line is a bit more difficult to estimate, but with my rudimentary knowledge of electrical systems and telecommunications equipment I think an upper estimate of 2 Watts is reasonable. Counting the phone line, and even the DSLAM, may seem a bit pointless since they are likely to be there anyway, but we are aiming to illuminate a worst-case scenario (ie. someone who otherwise would not have the phone line).

Anyway, if counting them, then we have, say, 3 Watts continuous (2,190 Wh) which gets used for about 2GBytes per month (a low average usage estimate, but in line with many ISP’s fair usage policies), which gives another 1.09 Wh/MB.

So, to sum up:

According to Google the average Web page is about 320 KBytes these days. Therefore, downloading a single Web page uses about 1.9 Wh. Boiling the water for a mug of tea in a kettle, by comparison, uses about 50 Wh (a 3KW kettle takes 90 secs to boil 2 mugs-worth – 37.5 Wh – plus a bit for the wasted water).

A music album is in the region of 100 MBytes (a bit more for iTunes, and varies depending on quality and number of tracks of course), which would be 590 Wh. A typical small electric car uses about 300 Wh per mile, so you could drive about 2 miles on the energy required to download and deliver a music album, or do the tea round for 12 people. The energy required to deliver music on CD is vastly more, of course, and I will look at that in another article, but it is interesting to see that downloading is certainly not without its carbon impact.

While the above calculations are fun it is important to point out that equating downloading to absolute energy requirements is extremely crude and should be treated with caution. A heavy Internet user would be much more efficient, for example, and the nature of the configuration of the servers in the data centre will also have a large effect, as seen with the differences if only our virtual machine grid is used in the assessment.

I also made a number of assumptions about the home end of the network, and it is useful to see the lower-end of the range. Therefore, if we use the Miniserver VM^® figure of 1.22 Wh/MB (including cooling and embedded energy), assume that the DSLAM ports are efficient when idle (most of the time) and call that 0.5 Watt and that the phone line itself is just 1 Watt giving a total of 0.55 Wh/MB (the same as if we assume the average utilisation is double my estimate, at 4BGytes/month), then we get a total figure of only 1.8 Wh/MB as the lower end of our download energy estimate.

For instance, if we assume that Apple run an efficient data centre infrastructure for serving their iTunes customers with similar properties to our virtual machine grid (which is very likely), and that the above lower estimate for the phone line is accurate, then a 100MByte album from them would only take 180 Wh – or about 3.5 mugs of tea worth of energy.

On the flip side, I have not included the energy to run the home network and PC(s)/laptop(s), which many papers do, but that greatly skews the figures and we are assuming here that those bits of equipment are used for other purposes than just downloading.

One of the areas on which we reached clear agreement in the G-Cloud and App Store phase 2 was the definition the layers of the stack, infrastructure, platform and software, and their scalable, standardised “as a service” modes. Pleasingly, our delinations were very similar to prior work from two decades ago by IBM, except that ours incorporate virtualisation.

The diagram shows what we agreed we mean by Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (right hand side) and the areas encompassed by the individual terms infrastructure / platform / software on the left. A better term than “software” might be “application” since the platform part is also really just software, but SaaS has already gained wide acceptance.

It is assumed that “as a service” means all services within the definition are fully integrated up to and including the respective level, thus incorporating any sub-levels. Therefore, SaaS providers could either sub-contract to a PaaS provider, or would incorporate the PaaS themselves and provide it as part of the SaaS “stack”. In turn the IaaS could be sub-contracted or incorporated. The customer would see an integrated service.

It is also worth explaining the overlap between ‘platform’ and ‘software’; that is because some advanced platforms are built on complex software solutions which go well beyond just operating systems and a bit of infrastructure software.

For example, one could consider bare operating system as the platform, with the bespoke software application incorporating its own software infrastructure elements (eg. a bespoke CRM solution). One might also consider a Linux-Apache-MySQL-PHP stack as the platform in its entirety, with only the PHP code and databate structure being the software/application layer. The key differentiator between ‘platform’ and ‘software’ is that a platform is standardised and to an extent commoditised, with the software being the bespoke / custom element. A platform would also often, but not always, be highly scalable across multiple servers.

Standardised / commoditised software (hosted application) services, as opposed to bespoke / custom deployments, would most likely be considered to be SaaS.

Virtual differences

Until this point many experienced readers might be saying, “Yes, that that is just hardware, middleware and software renamed!”. To a large extent you would be right, with one small exception being subtle differences between modern platform or middleware, but there is an important difference between the old concept of “hardware” and ours of “infrastructure”: virtualisation.

It was agreed among the G-Cloud team that the virtualisation should now be considered as part of the hardware layer since it has become such an integral method of dividing and provisioning hardware resources. It is important to note that we drew the line precisely between the virtualisation layer (ie. the hypervisor) and operating system, viewing a bare-bones virtual machine without operating system or kernel as the unit(s) of hardware.

Of course, virtualisation is not ubiquitous. Indeed for many systems including highly scalable ones upon which PaaS and SaaS stacks are built do not use any virtualisation (Google App Engine does not, for example). In such cases one would simply view the stack without the virtualisation layer with the boundary between infrastructure and platform being between the physical hardware and operating system layers.

Network

Another critique of this model could be that the “interconnecting network” appears to link directly from the software layer through to the client device. In reality, of course, all network traffic has to sink back down through the layers from the software to via the networking & firewalling layer, then on to the client device. To keep the stack looking like a stack, however (which is correct from a logical perspective), it is better to stick the client device on top rather than off to one side. In the full postulated functional of the G-Cloud logical architecture the connections are more explicitly shown in a 2D rather than linear model. Hopefully that will be in the public domain soon!

Decoding the academic paper

First I started with what appears to be the only paper on the subject; “Energy Intensity of Computer Manufacturing: Hybrid Assessment Combining Process and Economic Input-Output Methods” by Eric Williams of the United Nations University in Japan, and published in Environmental Science & Technology in 2004.

Unfortunately the paper bundles CRT (old-style monitor) production in with the figures which really muddies the waters, especially given that they are redundant technology) However, there seems to be one very nice bit of information embedded in the paper – a table listing the electricity, fossil, and total energy use in computer production. A quick bit of analysis: The total estimated cost of production is 6,400MJ, and if we remove the CRT-specific bits, we take off:

• CRT manufacture/assembly: 255MJ
• bulk materials – CRT 800MJ
• printed circuit boards: 20MJ (est)
• electronic chemicals: 200MJ (est)
• other processes: 400MJ (est)
• Total: 1,675MJ

So, from the paper a PC’s production is about 4,700MJ, which is 1,300kWh. At a green IT conference at Oxford University last year, Fujitsu gave a great presentation on their new super-green PC fabrication plant, and asserted that their range of green PCs took 730kWh to make (materials, production & distrubution). If his numbers are right that is an impressive improvement in 4 years, but Fujitsu have been working hard in the area. Of course, that does also depend on my estimates of what proportion are down the the CRT – I shouldn’t think I’m far off though (I’m good with numbers ).

As an aside, this is very interesting from a recycling point of view. Most PC manufacturers, be it Fujitsu, Dell or IBM will proudly telling us about less than 2% goes to landfill, but if you think about it surely the only energy that can be “reclaimed” from manufacture would be the bulk materials; all the energy of making chips, assembly, PCBs, transport etc is entirely lost. Therefore, in reality one could at most hope to recover perhaps 800-1,000MJ of the original energy-cost (ie. about 20%).

A server is just a PC with a slightly different set of components (an extra disk & more RAM, but less additional cards like graphics & audio), so I think it is reasonable to assume they are similar. Therefore, I pick a figure half way between what I have deduced from the paper (1,300 kWh) and the only convincing figure I have had from a vendor (730 kWh) and have gone for 1,000 kWh in my estimations.

Sweat the desktops

So what about the fabrication energy vs. utilisation? Well, I think the paper’s 81% fab, 19% use lifetime cost is probably no longer very accurate. First, he assumes 3 hours per day, which is far too low given the number of office PCs out there and the often intensive use of family PCs. Second, I think a 3 year lifetime is too low – most people I know use their PCs much longer (they get passed down / re-used rather than thrown away) – I believe the Fujitsu figure of 6.6 years for home users at least.

I would not, however, disagree totally with his figure of 128W for PC+screen – the gains we have made in LCD screen efficiency have been outweighed by power-hungry CPU-intensive machines in recent years, although that trend is reversing. Fujitsu’s figure was 80W for their “green” PC in full power mode, and an average LCD screen uses about 20W (about half a similar CRT).

So, a quick updated estimate (based on an average of PC & home use):

120W * 5 hours/day * 365 * 5 years ~= 1,100 kWh

If we assume LCD screens are as energy intensive as CRTs and go with Eric’s figure of 1,700 kWh for production then the ratio is 61% fab : 39% use.

If we assume that Fujitsu are telling the truth though then it is 730kWh in fabrication, plus ~300kWh for a screen (a guestimate – it is about 465 kWh for a CRT), giving about 1,000kWh fabrication then the embedded vs. use energies are almost equal.

If one then does the calculation based on an office PC usage pattern and a 6.6 year lifetime, then even with more energy efficient PCs the ratio is more like 35% fab : 65% use.

Therefore, I think that we can conclude that the ratio of production energy to usage energy for a PC (with or without screen – the proportions seem about the same) range widely from something like (35% fab : 65% use) to (70% fab : 30% use), and that the main determining factor is the usage pattern of the PC, which is also the one bit of data that we probably have the worst grasp on. Either way, though, you will use less energy overall if you sweat the desktop PCs, as we discussed in the recent BCS Green IT debate.

Replace the servers

The situation is very different for a server, however. A typical modern 1U pizza-box server will use 80W when idle and 140W when working hard. Most of the time they are not straining, so call it 100W:

100W * 24 hours/day * 365 * 1.25 PUE ~= 1,100 kWh per year

In other words, a server uses about the same amount of energy as was required to create it every single year, and the same amount that a PC with a fairly average usage pattern uses in 5 years.

Because of this it is worth while to replace servers with more efficient models on a fairly regular basis. Moore’s Law (that transistor density doubles every 18 months) means that server work capacity per Watt is increasing by a factor of 4 every 3 years. This means, that provided you are using the servers properly (virtualisation etc) and consolidating onto a smaller number of newer machines, if you replace a 3 year old server its 1,000 kWh embedded energy cost will be saved by the 3 you are turning off (4:1 consolidation) in only 4 months.