Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Biologically Inspired
Internet of Things
Tim Kellogg
@kellogh
Biology?
• No central control
• Coordinated decision making
• Routing & navigation
Sensor Networks
• Low power
• Noisy networks (small messages)
• Unreliable nodes
BiologyDistributed
Systems
Fast
Sensor
Networks
Low
Power
Lossy
Communication
Hostile
Nodes
Large
Messages
Tiny
Messages
N...
Speed vs Robustness
• Cloud services are FAST!
• Biological operations take hours, days, weeks,…
• Biological systems can ...
Should Sensor Networks Be
More Like Living Organisms?
Trade-offs
• Does response time or latency matter?
• Do you need self-healing?
• Is the environment hostile?
• Is the topo...
Examples
Maximal Independent Set
An example of BEEPING where proteins
are secreted (broadcast)

Routing & Clustering

Form an IPv6 ...
Ant Foraging (Emergence)
• Ant leaves more pheromones on a good path
• Ants follow stronger pheromone trails
• Larger popu...
Thanks!
@kellogh
Upcoming SlideShare
Loading in …5
×

Biologically Inspired Internet of Things

848 views

Published on

Biological networks like cells, neurons, and ant colonies have a lot in common with distributed systems, but they have even more in common with sensor networks and heterogeneous home automation systems. They all have to deal with distributed consensus and self-organization problems, but biological and sensor networks have to deal with downright hostile nodes. In this presentation are a couple examples of how we can learn from biology to build a better Internet of Things.

Published in: Engineering
  • Be the first to comment

  • Be the first to like this

Biologically Inspired Internet of Things

  1. 1. Biologically Inspired Internet of Things Tim Kellogg @kellogh
  2. 2. Biology? • No central control • Coordinated decision making • Routing & navigation
  3. 3. Sensor Networks • Low power • Noisy networks (small messages) • Unreliable nodes
  4. 4. BiologyDistributed Systems Fast Sensor Networks Low Power Lossy Communication Hostile Nodes Large Messages Tiny Messages No Central Control Slow Dynamic Self-Healing Binary Faulty Nodes
  5. 5. Speed vs Robustness • Cloud services are FAST! • Biological operations take hours, days, weeks,… • Biological systems can regenerate after failures
  6. 6. Should Sensor Networks Be More Like Living Organisms?
  7. 7. Trade-offs • Does response time or latency matter? • Do you need self-healing? • Is the environment hostile? • Is the topology planned or dynamic?
  8. 8. Examples
  9. 9. Maximal Independent Set An example of BEEPING where proteins are secreted (broadcast) Routing & Clustering Form an IPv6 subnet Useful for Routing & Clustering for highly dynamic networks. Each member of MIS could be labeled “supervisor” and every other “worker”. Then each supervisor could be networked together for max 3-hop comms between workers. Routing based Roles Assignment for Monitoring 6LowPAN Networks - https://hal.inria.fr/hal-00747002/document Distributed monitoring and aggregation in wireless sensor networks - http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5462033&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp %3Farnumber%3D5462033
  10. 10. Ant Foraging (Emergence) • Ant leaves more pheromones on a good path • Ants follow stronger pheromone trails • Larger population can determine which branch has better yield Basically TCP with back pressure
  11. 11. Thanks! @kellogh

×