2 changed files with 164 additions and 0 deletions
Split View
Diff Options
-
BINkademlia.pdf
-
+164 -0src/kademlia/kademlia.md
BIN
kademlia.pdf
BIN
kademlia.pdf
@ -0,0 +1,164 @@ |
|||
--- |
|||
marp: true |
|||
--- |
|||
|
|||
|
|||
# Kademlia |
|||
|
|||
|
|||
<br><br><br> |
|||
[@arnaucube](https://twitter.com/arnaucube) |
|||
|
|||
2019-04-26 |
|||
|
|||
--- |
|||
|
|||
### Overview |
|||
- nodes self sets a random unique ID (UUID) |
|||
- nodes are grouped in `neighbourhoods` determined by the `node ID` distance |
|||
- Kademlia uses `distance` calculation between two nodes |
|||
- distance is computed as XOR (exclusive or) of the two `node ID`s |
|||
|
|||
--- |
|||
|
|||
- XOR acts as the distance function between all `node ID`s. Why: |
|||
- distance between a node and itself is zero |
|||
- is symmetric: distance between A to B is the same to B to A |
|||
- follows `triangle inequality` |
|||
- given A, B, C vertices (points) of a triangle |
|||
- AB <= (AC + CB) |
|||
- the distance from A to B is shorter or equal to the sum of the distance from A to C plus the distance from C to B |
|||
- so, we get the shortest path |
|||
--- |
|||
- with that last 3 properties we ensure that XOR |
|||
- captures all of the essential & important features of a "real" distance function |
|||
- is simple and cheap to calculate |
|||
- each search iteration comes one bit closer to the target |
|||
- a basic Kademlia network with `2^n` nodes will only take `n` steps (in worst case) to find that node |
|||
|
|||
--- |
|||
|
|||
### Routing tables |
|||
- each node has a routing table, that consists of a `list` for each bit of the `node ID` |
|||
- each entry holds the necessary data to locate another node |
|||
- IP address, port, `node ID`, etc |
|||
- each entry corresponds to a specific distance from the node |
|||
- for example, node in the Nth position in the `list`, must have a differing Nth bit from the `node ID` |
|||
- so, the list holds a classification of 128 distances of other nodes in the network |
|||
--- |
|||
- as nodes are encountered on the network, they are added to the `lists` |
|||
- store and retrieval operations |
|||
- helping other nodes to find a key |
|||
- every node encountered will be considered for inclusion in the lists |
|||
- keps network constantly updated |
|||
- adding resilience to failures and attacks |
|||
--- |
|||
- `k-buckets` |
|||
- `k` is a system wide number |
|||
- every `k-bucket` is a `list` having up to `k` entries inside |
|||
- example: |
|||
- network with `k=20` |
|||
- each node will have `lists` containing up to 20 nodes for a particular bit |
|||
- possible nodes for each `k-bucket` decreases quickly |
|||
- as there will be very few nodes that are that close |
|||
- since quantity of possible IDs is much larger than any node population, some of the `k-buckets` corresponding to very short distances will remain empty |
|||
--- |
|||
- example: |
|||
 |
|||
- network size: 2^3 |
|||
- max nodes: 8, current nodes: 7 |
|||
- let's take 6th node (110) (black leaf) |
|||
- 3 `k-buckets` for each node in the network (gray circles) |
|||
- nodes 0, 1, 2 (000, 001, 010) are in the farthest `k-bucket` |
|||
- node 3 (011) is not participating in the network |
|||
- middle `k-bucket` contains the nodes 4 and 5 (100, 101) |
|||
- last `k-bucket` can only contain node 7 (111) |
|||
|
|||
--- |
|||
|
|||
- Each node knows its neighbourhood well and has contact with a few nodes far away which can help locate other nodes far away. |
|||
- Kademlia priorizes long connected nodes to remain stored in the `k-buckets` |
|||
- as the nodes that have been connected for a long time in a network will probably remain connected for a long time in the future |
|||
--- |
|||
- when a `k-bucket` is full and a new node is discovered for that `k-bucket` |
|||
- node sends a ping to the last recently seen node in the `k-bucket` |
|||
- if the node is still alive, the new node is stored in a secondary list (a replacement cache) |
|||
- replacement cache is used if a node in the `k-bucket` stops responding |
|||
- basically, new nodes are used only when older nodes disappear |
|||
|
|||
--- |
|||
|
|||
### Protocol messages |
|||
- PING |
|||
- STORE |
|||
- FIND_NODE |
|||
- FIND_VALUE |
|||
Each `rpc` msg includes a random value from the initiator, to ensure that the response corresponds to the request |
|||
|
|||
--- |
|||
|
|||
### Locating nodes |
|||
- node lookups can proceed asynchronously |
|||
- `α` denotes the quantity of simultaneous lookups |
|||
- `α` tipically is 3 |
|||
- node initiates a FIND_NODE request to the `α` nodes in its own `k-bucket` that are closest ones to the desired key |
|||
--- |
|||
- when the recipient nodes receive the request, they will look in their `k-buckets` and return the `k` closest nodes to the desired key that they know |
|||
- the requester will update a results list with the results (`node ID`s) that receives |
|||
- keeping the `k` best ones (the `k` nodes that are closer to the searched key) |
|||
- the requester node will select these `k` best results and issue the request to them |
|||
- the proces is repeated again and again until get the searched key |
|||
--- |
|||
- iterations continue until no nodes are returned that are closer than the best previous results |
|||
- when iterations stop, the best `k` nodes in the results list are the ones in the whole network that are the closest to the desired key |
|||
- node information can be augmented with RTT (round trip times) |
|||
- when the RTT is spended, another query can be initiated |
|||
- always the query's number are <= `α` (quantity of simultaneous lookups) |
|||
|
|||
--- |
|||
|
|||
### Locating resources |
|||
- data (values) located by mapping it to a key |
|||
- typically a hash is used for the map |
|||
- locating data follows the same procedure as locating the closest nodes to a key |
|||
- except the search terminates when a node has the requested value in his store and returns this value |
|||
|
|||
--- |
|||
|
|||
#### Data replicating & caching |
|||
- values are stored at several nodes (k of them) |
|||
- the node that stores a value |
|||
- periodically explores the network to find the k nodes close to the key value |
|||
- to replicate the value onto them |
|||
- this compensates the disappeared nodes |
|||
--- |
|||
- avoiding "hot spots" |
|||
- for popular values (might have many requests) |
|||
- near nodes outside the k closest ones, store the value |
|||
- this new storing is called `cache` |
|||
- caching nodes will drop the value after a certain time |
|||
- depending on their distance from the key |
|||
- in this way the value is stored farther away from the key |
|||
- depending on the quantity of requests |
|||
- allows popular searches to find a storer more quickly |
|||
- alleviates possible "hot spots" |
|||
- not all implementations of Kademlia have these functionallities (replicating & caching) |
|||
- in order to remove old information quickly from the system |
|||
|
|||
--- |
|||
|
|||
### Joining the network |
|||
- to join the net, a node must first go through a `bootstrap` process |
|||
- `bootstrap` process |
|||
- needs to know the IP address & port of another node (bootstrap node) |
|||
- compute random unique `node ID` number |
|||
- inserts the bootstrap node into one of its k-buckets |
|||
--- |
|||
- `bootstrap` process [...] |
|||
- perform a node lookup of its own `node ID` against the bootstrap node |
|||
- this populate other nodes `k-buckets` with the new `node ID` |
|||
- populate the joining node `k-buckets` with the nodes in the path between that node and the bootstrap node |
|||
- refresh all `k-buckets` further away than the `k-bucket` the bootstrap node falls in |
|||
- this refresh is a lookup of a random key that is within that `k-bucket` range |
|||
- initially nodes have one `k-bucket` |
|||
- when is full, it can be split |
|||