This thread is started by a question in the Ambassadors telegram group. Here’s the original question: "Hi @weynandkuijpers where can I find whatever details/data we have on energy savings?
Here’s my answer:
Hi Colin, we have done a “study” not too long ago towards compute workloads. This is the hardest (and smallest) energy gain to be identified as “processing data” takes CPU power and the differences are due to more or less efficient operating systems. I’ll look for that data, but a warning this is not going to impress you.
The big advantages and large efficiency gain numbers start with storage. The facts to why this is so are simple: traditional IT relies on creating backups (=copies) of data. Every IT manager (of about my age has been raised with the 1, 2, 3 (and 4) rule.
- There is one copy of the data that is the active copy which is the workhorse
- The second copy you need to have is a “hot standby” copy (means online and alive and kicking) for when the active one fails which is almost as complete as the original active one (this requires a lot of complex activities to keep the two copies synchronized).
- The third copy is a backup copy. This is a multiple in size of the original data set as you keep multiple copies: full weekly backups for a couple of weeks and then daily / hourly “incremental” copies to be able to go back to a certain point in time to make sure that you can recover from data corruption, ransome ware or any of the other data destruction threats (human beings deleting files … :-).
- The last and ultimate one: When you really want to do a good job you need to send a copy of the data to a secure vault service. Usually, specialized companies running this service for you.
This easily leads to a 10x overhead in energy consumption: electricity for storing and transporting data, administration, human (brain) power, and actually gas to transport physical data holding devices compared to dispersed (ThreeFold) storage. This storage mechanism does not have any full copies of datasets, it cleverly spreads the data over multiple dispersed devices (on other servers, in another rack, in another datacenter or even in another country/continent). this is driven by a storage policy and by choosing the right policy for a specific data type (16+4 = 25% extra storage, 16+8 = 50% extra storage, but certainly not 300% extra storage or more) you can achieve very (if not more reliable) storage solutions Dispersed storage is described well here: https://sdk.threefold.io/#/architecture_storage
The higher efficiency gain numbers (100x+) come (also from storage) but more specifically from the blockchain components of the ThreeFold grid. Working with permissioned nodes (“lottery” based consensus) and not proof of work (which is “race” based consensus where only one wins, the rest that has participated is a waste of effort = energy) is much more efficient. The second aspect here is that public blockchains that have 1000’s of (full) nodes which by definition mean 1000’s of copies of the same data , which is 100’s of times less efficient in terms of energy consumption.
Bu blending all of this specific choices and architectural components together we can claim that we are a lot more energy efficient than traditional technology.
So we do not have empirical data to underwrite the achieved efficiencies but a bit of knowledge about how we do things compared to the rest of the industry and common sense leads to the conclusion that these claims are valid. We will get the claims verified when we have found the right partner to do this with, and when the time is right. Hope this helps!