1 / 5

Related Work

Related Work. 2 major areas: Controlled, density aware flooding algorithms for wireless and multicas t networks Epidemic and gossiping algorithms for data consistency in distributive systems Both assume cheap communication, end-to-end transport Network broadcasts:

trevor
Download Presentation

Related Work

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Related Work • 2 major areas: • Controlled, density aware flooding algorithms for wireless and multicast networks • Epidemic and gossiping algorithms for data consistency in distributive systems • Both assume cheap communication, end-to-end transport • Network broadcasts: • Prior works: want to deliver a piece of data to as many nodes as possible with a time period • Simple broadcast retransmission leads to broadcast storm problem. • Best effort attempt to send a message to all nodes in a network and stop • Probabilistic broadcasts • Adaptive dissemination

  2. Related Work • Ni et al: counter based algorithm to prevent broadcast storm • Operates in a single interval • Insufficient for sensor network code propagation • E.g.: mote rejoins 3 days after the broadcast -> rebroadcast the entire network • Propagating data updates through distributive system • Demers et al: epidemic algorithms for managing replicated databases • PlanetP: epidemic gossiping for a distributive peer-to-peer index • Trickles use techniques drawn from these efforts: only local wireless broadcast

  3. Related Work • Gossiping -> SPIN’s three way handshaking protocol • Reijers et. Al : efficient code distribution • Distributes only changes to the current code • Compute and update changes to a code image through memory manipulation • Doesn’t address how to distribute the code and to validate the updates • TinyDB sensor network: • Query system uses epidemic style of code forwarding • Depends on periodic data collection with embedded metadata

  4. Discussion and Conclusion • Trickle can: • Quickly propagate new code with a small overhead • Uses a very simple mechanism • Scales logarithmic with density. • Reprogram the entire network in 30s with an overhead of less than 3 packets/h • Ignored policy used to propagate code: Maté broadcasts code routines 2 times

  5. Discussion and Conclusion • Limitations: Motes are always on • Long-term deployments have very low duty-cycle • Communication scheduling schemes • Trickle’s scalability stems from randomization and idle listening • Transmission scalability suffers under a CSMA protocol • Low power listening • Extra plus: • Could be used to disseminate any sort of data • Change the propagation scope by adding predicate to summaries

More Related