5.3 KiB
Unmanned Aerial Vehicle (UAV)
- UAV, commonly known as a Drone, is an aircraft without a human pilot aboard (unmanned or uncrewed)
- it operates
- under remote control by a human
- autonomously by on board computers
Weight: from 0.5g 15000kg Maximum speed: up to 11265Kph Propellant:
- fossil fuel
- battery
Usages
- can provide timely disaster warnings
- medical supplies
- dangerous situations
- traffic monitoring, wind estimation, remote sensing...
I many scenarios, UAVs need to exchange a relatively large amount of data among themselves and/or a control station. In many case there isn't any network infrastructure available. Drones can also used to expand terrestrial communication networks.
Drones can be equipped with several standard radio modules:
- Wi-Fi
- Cellular
- LPWAN (low power wide area network, es. LoRa)
Routing
may require multi-hop data connections
Comparison WSN with Dronets
| WSN | Dronet | |
|---|---|---|
| Mobility | none or partial | high, even 3D |
| Topology | random, star, ad-hoc node failure | mesh |
| Infrastructure | absent | absent |
| Energy source | battery | battery (very limited) |
| Typical use | environmental monitoring | rescue, monitoring, surveillance |
Goals of routing protocols:
- increase delivery ratio
- loop freedom
- low overhead
- reduce delays
- energy consumption
- scalability
Proactive routing protocols
Are they suitable for UAV networks?
- slow reaction to topology changes, will cause delays
- bandwidth constraints
Protocols:
- OLSR - Optimize Link State Routing
- DSDV - Destination-Sequenced Distance Vector
- B.A.T.M.A.N. - Better Approach to Mobile Ad Hoc Network
Reactive protocols
- DSR - Dynamic Source Routing
- AODV - Ad hoc On Demand Distance Vector
Hybrid protocols
- ZRP - Zone Routing Protocol
- TORA - Temporarily Ordered Routing Algorithm
B.A.T.M.A.N.
A proactive, distance-vector routing protocol for Mobile Ad-hoc Networks (MANETs) and Mesh Networks. Designed for decentralized decision-making and self-organizing networks.
Key features:
- decentralized routing
- no node has global knowledge of the entire network
- next-hop based
- nodes only know their best-hop neighbor for reaching a destination
- link quality driven
- decisions are based on the quality of the link between nodes
- self-healing
- adapts to changes automatically
How batman works
-
Originator messages (OGMs):
- broadcast to announce its presence
- OGMs are forwarded by neighbors to propagate through the network
- each OGM carries a sequence number to ensure the information is up-to-date and avoid routing loops
- nodes evaluates how frequently they receive OGMs to their neighbors to determine link quality
- each node maintains a routing table with the best next-hop neighbor based on link quality
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fields inside OGM
- originator address
- sequence number
- TTL (hop limit)
- LQ (quality between the sender and the originator)
- hop count
Asimmetry problem: If A can reach B well, B thinks it can reach A well too. But it may not be the case. To overcome the issue there is the Transmit Quality (TQ) algorithm.
B transmits RQ (receive quality) packet to A. A counts them to know the link quality. A knows the echo quality by counting the rebroadcasts of its own OGMs from its neighbors. Dividing echo quality by receiving quality, A can calculate the transmit quality.
propagation A when originates the OGMs, it sets TQ to 100%. The neighbor computes their own local link quality into the received TQ value and rebroadcast the packet.
TQ = TQ_{incoming} * TQ_{local}
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Geographic protocols
the geographical position information of the nodes is utilized for forwarding decisions. Nodes knows their position by GPS.
Geographic routing schemes don't need the entire network information
- no routing discovery
- no routing tables
- forward packet based on local information
- less overhead, bandwidth and so energy consumption
- for routing decisions a drone needs only the neighbors and destination position
Every node has coordinates of neighbors.
Dead end problem several techniques have been defined in sensor networks to recover from a dead end but they are often not applicable to dronets.
Geo routing is based on three main approaches
Greedy forwarding
as stated before
Store-carry and forward
When the network is intermittently connected, forwarder nodes do not have any a solution to find a relay node. Not possible to forward any data packet to a predefined node which is not in range. So the current node will carry the packet until it meet another node or the destination target itself.
Prediction
based on geographical location, direction, and speed to predict the future position of a given node. They will predict the position of a next relay node.
DGA algorithm
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