sforkowany z mirror/meshtastic-firmware
67 wiersze
5.5 KiB
Markdown
67 wiersze
5.5 KiB
Markdown
# Mesh broadcast algorithm
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FIXME - instead look for standard solutions. this approach seems really suboptimal, because too many nodes will try to rebroast. If
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all else fails could always use the stock Radiohead solution - though super inefficient.
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TODO:
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* reread the radiohead mesh implementation
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* read about general mesh flooding solutions
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* reread the disaster radio protocol docs
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good description of batman protocol: https://www.open-mesh.org/projects/open-mesh/wiki/BATMANConcept
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interesting paper on lora mesh: https://portal.research.lu.se/portal/files/45735775/paper.pdf
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It seems like DSR might be the algorithm used by RadioheadMesh. DSR is described in https://tools.ietf.org/html/rfc4728
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https://en.wikipedia.org/wiki/Dynamic_Source_Routing
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broadcast solution:
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Use naive flooding at first (FIXME - do some math for a 20 node, 3 hop mesh. A single flood will require a max of 20 messages sent)
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Then move to MPR later (http://www.olsr.org/docs/report_html/node28.html). Use altitude and location as heursitics in selecting the MPR set
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compare to db sync algorithm?
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what about never flooding gps broadcasts. instead only have them go one hop in the common case, but if any node X is looking at the position of Y on their gui, then send a unicast to Y asking for position update. Y replies.
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If Y were to die, at least the neighbor nodes of Y would have their last known position of Y.
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## approach 1
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* send all broadcasts with a TTL
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* periodically(?) do a survey to find the max TTL that is needed to fully cover the current network.
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* to do a study first send a broadcast (maybe our current initial user announcement?) with TTL set to one (so therefore no one will rebroadcast our request)
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* survey replies are sent unicast back to us (and intervening nodes will need to keep the route table that they have built up based on past packets)
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* count the number of replies to this TTL 1 attempt. That is the number of nodes we can reach without any rebroadcasts
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* repeat the study with a TTL of 2 and then 3. stop once the # of replies stops going up.
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* it is important for any node to do listen before talk to prevent stomping on other rebroadcasters...
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* For these little networks I bet a max TTL would never be higher than 3?
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## approach 2
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* send a TTL1 broadcast, the replies let us build a list of the nodes (stored as a bitvector?) that we can see (and their rssis)
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* we then broadcast out that bitvector (also TTL1) asking "can any of ya'll (even indirectly) see anyone else?"
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* if a node can see someone I missed (and they are the best person to see that node), they reply (unidirectionally) with the missing nodes and their rssis (other nodes might sniff (and update their db) based on this reply but they don't have to)
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* given that the max number of nodes in this mesh will be like 20 (for normal cases), I bet globally updating this db of "nodenums and who has the best rssi for packets from that node" would be useful
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* once the global DB is shared, when a node wants to broadcast, it just sends out its broadcast . the first level receivers then make a decision "am I the best to rebroadcast to someone who likely missed this packet?" if so, rebroadcast
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## approach 3
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* when a node X wants to know other nodes positions, it broadcasts its position with want_replies=true. Then each of the nodes that received that request broadcast their replies (possibly by using special timeslots?)
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* all nodes constantly update their local db based on replies they witnessed.
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* after 10s (or whatever) if node Y notices that it didn't hear a reply from node Z (that Y has heard from recently ) to that initial request, that means Z never heard the request from X. Node Y will reply to X on Z's behalf.
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* could this work for more than one hop? Is more than one hop needed? Could it work for sending messages (i.e. for a msg sent to Z with want-reply set).
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## approach 4
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look into the literature for this idea specifically.
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* don't view it as a mesh protocol as much as a "distributed db unification problem". When nodes talk to nearby nodes they work together
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to update their nodedbs. Each nodedb would have a last change date and any new changes that only one node has would get passed to the
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other node. This would nicely allow distant nodes to propogate their position to all other nodes (eventually).
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* handle group messages the same way, there would be a table of messages and time of creation.
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* when a node has a new position or message to send out, it does a broadcast. All the adjacent nodes update their db instantly (this handles 90% of messages I'll bet).
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* Occasionally a node might broadcast saying "anyone have anything newer than time X?" If someone does, they send the diffs since that date.
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* essentially everything in this variant becomes broadcasts of "request db updates for >time X - for _all_ or for a particular nodenum" and nodes sending (either due to request or because they changed state) "here's a set of db updates". Every node is constantly trying to
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build the most recent version of reality, and if some nodes are too far, then nodes closer in will eventually forward their changes to the distributed db.
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* construct non ambigious rules for who broadcasts to request db updates. ideally the algorithm should nicely realize node X can see most other nodes, so they should just listen to all those nodes and minimize the # of broadcasts. the distributed picture of nodes rssi could be useful here?
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* possibly view the BLE protocol to the radio the same way - just a process of reconverging the node/msgdb database.
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