All around the world, thousands of nodes are still humming away, carefully and unquestioningly storing and replicating the community’s cockerel pics and unfathomable music choices for ever, and ever, and ever. Don’t worry, we’re going to take this testnet down in due course. We’re not there just yet but as time goes on the network is becoming noticeably more stable, predictable and scalable - which is extremely gratifying. Please do carry on uploading and sharing, and post your logs if you see anything untoward.
Some conclusive test results have convinced us to switch our data replication model from push to pull. Under the push model that we’ve been using up to now, when there is churn (a node goes offline) nodes with copies of the data held by the dead node push them to the next nearest node. Some of those nodes will be successful in pushing their chunks, others won’t, but there should be enough tolerance in the system (as controlled by the choice of k-value) to ensure no data is lost.
The pull method is similar, except the new node, realising it is the heir to the dead node, requests chunks from its close group. Again, some requests may be successful, others won’t be, but in the end all chunks should be received.
So what’s the difference? It’s in the number of messages being sent and the number of extra copies that are necessary to make the push model work. @Qi_ma has been running tests under extreme churn conditions and discovered that pull is superior on every metric - messages, CPU, memory and success rate. Therefore switching was a no-brainer. As of now we’re using the pull model.
It’s much better, but we are still seeing occasional dropped messages, which is why success isn’t 100% just yet.
Elsewhere, DBCs are now being replicated, laying the ground for paying for data, which will be the topic of a future testnet. @bochaco has created an illustration of Merkle DAGs and how they build a tree for the chunks that lets us use the root of the tree as the storage payment proof, which we will reproduce here.
The storage payment proofs are generated using a binary Merkle tree: A Merkle tree, also known as hash tree, is a data structure used for data verification and synchronisation. It is a tree data structure where each non-leaf node is a hash of its child nodes. All the leaf nodes are at the same depth and are as far left as possible. It maintains data integrity and uses hash functions for this purpose. In Safe, in order to pay the network for data storage, all files are first self-encrypted obtaining all the chunks the user needs to pay for before uploading them. A binary Merkle tree is created using all these chunks' addresses/Xornames, each leaf in the Merkle tree holds the value obtained from hashing each of the Chunk's Xorname/address. The following tree depicts how two files A and B, with two chunks each, would be used to build the Merkle tree: [ Root ] hash(Node0 + Node1) ^ | *-------------------------------------------* | | [ Node0 ] [ Node1 ] hash(Leaf0 + Leaf1) hash(Leaf2 + Leaf3) ^ ^ | | *----------------------* *----------------------* | | | | [ Leaf0 ] [ Leaf1 ] [ Leaf2 ] [ Leaf3 ] hash(ChunkA_0.addr) hash(ChunkA_1.addr) hash(ChunkB_0.addr) hash(ChunkB_1.addr) ^ ^ ^ ^ ^ ^ ^ ^ | | | | [ ChunkA_0 ] [ ChunkA_1 ] [ ChunkB_0 ] [ ChunkB_1 ] ^ ^ ^ ^ | | | | *----------------------* *----------------------* | | self-encryption self-encryption | | [ FileA ] [ FileB ] The user links the payment made to the storing nodes by setting the Merkle tree root value as the 'Dbc::reason_hash' value. Thanks to the properties of the Merkle tree, the user can then provide the output DBC and audit trail for each of the Chunks being paid with the same DBC and tree, to the storage nodes upon uploading the Chunks for storing them on the network.
@Anselme has been working through some bugs in the faucet and wallet, which are currently not marking DBCs as spent on the network. He’s also solved some logging issues.
@Roland has raised a PR to collect system, network and process metrics. This is behind a feature gate, meaning it can be toggled on and off according to our needs. It should be useful during testnets to collect metrics from the community. Later we will enable OpenSearch metrics, but this is a simple solution for now.
@ChrisO has got an automated testnet release process working experimentally. Should be ready for live action very soon. He and @aed900 have also been working on other aspects of testnets including secrets management on Digital Ocean. Angus has also been looking at an issue where private nodes (behind NAT) get written into the routing table, which is not what we want.
Fortunately @bzee, who has been digging into
libp2p, believes an upcoming version should solve this issue for us.
Feel free to reply below with links to translations of this dev update and moderators will add them here:
As an open source project, we’re always looking for feedback, comments and community contributions - so don’t be shy, join in and let’s create the Safe Network together!