Toward Efficient Many-to-Many Broadcast in Dynamic Wireless Networks - - PowerPoint PPT Presentation

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Toward Efficient Many-to-Many Broadcast in Dynamic Wireless Networks - - PowerPoint PPT Presentation

Sep 18, 2022 191 likes •700 views

Toward Efficient Many-to-Many Broadcast in Dynamic Wireless Networks Fabian Mager , Carsten Herrmann, Marco Zimmerling TU Dresden, Germany Why Many-to-Many? Why Many-to-Many? 1 Why Many-to-Many? 2 Why Many-to-Many? 3 Requirements

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Toward Efficient Many-to-Many Broadcast in Dynamic Wireless Networks

Fabian Mager, Carsten Herrmann, Marco Zimmerling TU Dresden, Germany

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Why Many-to-Many?

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Why Many-to-Many?

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Why Many-to-Many?

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Why Many-to-Many?

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Requirements

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Requirements

  • Dynamic multi-hop networks

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Requirements

  • Dynamic multi-hop networks
  • Low latency, high reliability

Controller

Closed-loop control: 10 – 500 ms [1]

[1] Akerberg et al., Future research challenges in wireless sensor and actuator networks targeting industrial automation, IEEE INDIN 2011

Physical process

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Requirements

  • Dynamic multi-hop networks
  • Low latency, high reliability
  • Efficiency (energy, costs, etc.)

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Current Solutions

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Current Solutions

Multi-Sink Routing [1] Sequential Flooding [2] Current Practice [3] Multi-hop / Mesh yes yes no

[1] Mottola et al., MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks, IEEE Transactions on Mobile Computing 2011 [2] Ferrari et al., Efficient network flooding and time synchronization with Glossy, ACM/IEEE IPSN 2011 [3] Preiss et al., Crazyswarm: A large nano-quadcopter swarm. IEEE ICRA 2017 5

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Current Solutions

Multi-Sink Routing [1] Sequential Flooding [2] Current Practice [3] Multi-hop / Mesh yes yes no Latency high medium low

[1] Mottola et al., MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks, IEEE Transactions on Mobile Computing 2011 [2] Ferrari et al., Efficient network flooding and time synchronization with Glossy, ACM/IEEE IPSN 2011 [3] Preiss et al., Crazyswarm: A large nano-quadcopter swarm. IEEE ICRA 2017 5

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Current Solutions

Multi-Sink Routing [1] Sequential Flooding [2] Current Practice [3] Multi-hop / Mesh yes yes no Latency high medium low Dynamic no yes yes

[1] Mottola et al., MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks, IEEE Transactions on Mobile Computing 2011 [2] Ferrari et al., Efficient network flooding and time synchronization with Glossy, ACM/IEEE IPSN 2011 [3] Preiss et al., Crazyswarm: A large nano-quadcopter swarm. IEEE ICRA 2017 5

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Current Solutions

Multi-Sink Routing [1] Sequential Flooding [2] Current Practice [3] Multi-hop / Mesh yes yes no Latency high medium low Dynamic no yes yes Energy Efficiency medium high low

[1] Mottola et al., MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks, IEEE Transactions on Mobile Computing 2011 [2] Ferrari et al., Efficient network flooding and time synchronization with Glossy, ACM/IEEE IPSN 2011 [3] Preiss et al., Crazyswarm: A large nano-quadcopter swarm. IEEE ICRA 2017 5

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Our Contribution

Multi-Sink Routing [1] Sequential Flooding [2] Current Practice [3] Mixer Multi-hop / Mesh yes yes no yes Latency high medium low low Dynamic no yes yes yes Energy Efficiency medium high low high

[1] Mottola et al., MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks, IEEE Transactions on Mobile Computing 2011 [2] Ferrari et al., Efficient network flooding and time synchronization with Glossy, ACM/IEEE IPSN 2011 [3] Preiss et al., Crazyswarm: A large nano-quadcopter swarm. IEEE ICRA 2017 5

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Approach

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Example: All-to-All Communication

  • Using sequential flooding, nodes

flood one after another

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Our Key Ideas

  • Overlay floods:

Let nodes send combinations of previously received packets, built with random linear network coding

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Our Key Ideas

  • Overlay floods:

Let nodes send combinations of previously received packets, built with random linear network coding

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Our Key Ideas

  • Overlay floods:

Let nodes send combinations of previously received packets, built with random linear network coding

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Our Key Ideas

  • Overlay floods:

Let nodes send combinations of previously received packets, built with random linear network coding

  • Enable spatial reuse:

Let multiple nodes transmit simultaneously and exploit the capture effect

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Our Key Ideas

  • Overlay floods:

Let nodes send combinations of previously received packets, built with random linear network coding

  • Enable spatial reuse:

Let multiple nodes transmit simultaneously and exploit the capture effect

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Main Challenges

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Main Challenges

  • 1. When should a node send?
  • 2. What should a node send?
  • 3. How to ensure synchronous transmissions without a global clock?
  • 4. How to achieve an efficient runtime operation?

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Main Challenges

  • 1. When should a node send?
  • 2. What should a node send?
  • 3. How to ensure synchronous transmissions without a global clock?
  • 4. How to achieve an efficient runtime operation?

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When Should a Node Send?

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  • Capture effect:

Correctly receive a packet despite interfering transmitters under physical layer specific conditions (e.g. 802.15.4: SINR >= 3dB, △t < 128us)

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When Should a Node Send?

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  • Capture effect:

Correctly receive a packet despite interfering transmitters under physical layer specific conditions (e.g. 802.15.4: SINR >= 3dB, △t < 128us)

  • Too many à capture unreliable
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When Should a Node Send?

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  • Capture effect:

Correctly receive a packet despite interfering transmitters under physical layer specific conditions (e.g. 802.15.4: SINR >= 3dB, △t < 128us)

  • Too many à capture unreliable
  • Too few à less spatial reuse
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When Should a Node Send?

  • Capture effect:

Correctly receive a packet despite interfering transmitters under physical layer specific conditions (e.g. 802.15.4: SINR >= 3dB, △t < 128us)

  • Too many à capture unreliable
  • Too few à less spatial reuse
  • Adaptive transmission policy

Choose transmit probability based on local node density

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Main Challenges

  • 1. When should a node send?
  • 2. What should a node send?
  • 3. How to ensure synchronous transmissions without a global clock?
  • 4. How to achieve an efficient runtime operation?

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What Should a Node Send?

… packet_1 … … packet_2 … … packet_3 … … packet_4 … … … … … packet_n …

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  • Innovative (linearly independent)

packets are stored in a matrix

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What Should a Node Send?

… packet_1 … … packet_2 … … packet_3 … … packet_4 … … … … … packet_n … Next transmit packet + +

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  • Innovative (linearly independent)

packets are stored in a matrix

  • Nodes send randomly chosen

combinations of stored packets

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What Should a Node Send?

next transmit packet + +

  • Innovative (linearly independent)

packets are stored in a matrix

  • Nodes send randomly chosen

combinations of stored packets

  • Several rules to make packets more

useful, e.g.:

  • Immediate relay of innovation
  • Boost dissemination of own message

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… packet_1 … … packet_2 … … packet_3 … … packet_4 … … … … … packet_n …

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Evaluation

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Setup

  • Mixer prototype on TelosB
  • 4 MHz, 16 bit, 10 KB RAM
  • Radio: IEEE 802.15.4
  • FlockLab testbed, ETH Zurich
  • 27 TelosB nodes
  • All-to-all, each node 1 message

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Reliability

100%

Mixer delivered all messages in every experiment

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Latency

10 30 50 70 90 110 Payload size [bytes] 100 200 300 400 500 Latency [slots]

Mixer SeqF

10 30 50 70 90 110 Payload size [bytes] 0.0 0.5 1.0 1.5 2.0 Latency [s]

Mixer SeqF

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Latency

10 30 50 70 90 110 Payload size [bytes] 0.0 0.5 1.0 1.5 2.0 Latency [s]

Mixer SeqF Mixer (new)

10 30 50 70 90 110 Payload size [bytes] 100 200 300 400 500 Latency [slots]

Mixer SeqF Mixer (new)

Mixer outperforms sequential flooding by up to 3.5x

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Conclusion

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Conclusion

  • Mixer, a many-to-all communication primitive
  • Made for dynamic wireless multi-hop networks
  • Combines synchronous transmissions and network coding
  • Complete spectrum from 1-to-all to all-to-all
  • Any initial message distribution
  • Versatile, fast, efficient, reliable

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