The blog posts are the right place to start your exploration of the issues, but you can't go much further without testing it yourselves.
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You should be apprehensive about depending upon any blockchain for high TPS and high numbers of nodes at the same time. Proper blockchain engineering at this point will be about finding ways to store the least amount of data on chain, with the least number of required TPS, as possible. Do not confuse Fabric or any other blockchain to be a high performance big data management tool. If anything, it's about "small data" that happens to be trust-critical.
As I understand your use case, in my opinion, you should not be storing all sensor data and transaction history directly on ledger; store that in large files chunked by time and gas station network, share those offledger (encrypted S3 buckets ate cheap and global, or IPFS), and use Fabric for storing hashes that can attest to the timing, provenance, metadata and integrity of that off-ledger data.
You also shouldn't try to have every gas station be a node in the network - I presume they are already part of a chain of gas stations, and within a chain there is already the trust of a single corporation, so the corp office itself should run nodes on behalf of its stations. It doesn't sound like you need prevention of double spend; I'm not even sure why you need smart contracts (you mean chaincode?) to "monitor fuel levels".
If scale is your number one goal, constantly look for ways to reduce the frequency and amount to write to the blockchain. (Reads, of course, are cheap and easy to scale).
On 9 November 2019 10:47:52 AM GMT+08:00, alok gupta <metech11@...> wrote:
Hello Mark & Christopher,
Thanks for your reply. I have gone through the blog but I am still apprehensive whether we would be able to support hundreds or thousands of organisations? We did TPS optimisation after struggling a bit with MVCC error, our solution is running fine for a single fuel station. Right now there are max 50 tps. But not sure how to take this forward. What should be our approach? Please advise.
We have seen throughput in high hundreds of TPS to low thousands of TPS in Oracle projects. The scalability and performance depend on many factors well explained in Chris’ blog posts. Certainly transaction payload size, batching parameters in the ordering service, number of channels an ordering cluster has to support given certain network bandwidth play a significant role. There are also techniques to batch transaction data, which are useful, for example, to capture an audit log from many IOT sensor readings. Feel free to reach out directly to discuss specifics.
From: Christopher Ferris <chris.ferris@...>
Sent: Wednesday, November 06, 2019 3:33 AM
To: alok gupta <metech11@...>
Subject: Re: [Hyperledger Fabric] Hyperledger Fabric Scalability
I wrote a couple of blog posts earlier this year on Hyperledger Fabric performance and scale.
There have been some more recent improvements that should improve performance even more when 2.0 ships.
I'll have another post up with those results. There are some additional efforts in the community where performance
has been pushed even further.
On Wed, Nov 6, 2019 at 3:36 AM alok gupta <metech11@...> wrote:
We are conducting a POC for Oil & GAS Retail automation. In which, we are recording all digital/ cash sales onto the Fabric ledger. We monitor the stock levels in the fuel tanks through smart contract. The idea is to replace the current automation system in India which requires massive investment in installation and maintenance. Our app is running successfully on a fuel station at a fuel station in Chandigarh, India.
My query is about the scalability of fabric over no. of channel, organizations, and peers. Can we scale up our solution to connect the fuel companies ( IOCL. HPCL etc.) with India wide fuel stations? I have seen other use cases like Wallmart food safety where there are running a huge network on blockchain. To move forward in our idea, we need a clarity on scalability Please advise.
Sent from my Android device with K-9 Mail. Please excuse my brevity.