Performance Tradeoffs Among Percolation-Based Broadcast Protocols in Wireless Sensor Networks

1. Performance Tradeoffs Among Percolation-Based Broadcast Protocols in Wireless Sensor Networks Vijay Ramanand Indranil Gupta University of Illinois at Urbana-Champaign WWASN 2009

2. Introduction • Broadcast in wireless sensor networks – a fundamental operation • Used for: • Sending code updates, e.g. Trickle • Initiating aggregation, e.g. TAG, directed diffusion • Sensing route updates • Membership/multicast group management • Several specific algorithms to address the broadcast problem • Pure gossiping • Trickle • PBBF (probability-based broadcast forwarding)

3. Motivation • Broadcast applications have varied requirements • Code updates – reliability • Information query propagation – time sensitivity • Membership management – energy minimization • Which protocol to use for what application? • How do the broadcast protocols compare with each other?

4. Flooding - Simplest Broadcast Protocol • Packets simply transmitted over the air • Any node that receives the packet repeats the process S Not all transmissions shown

5. Flooding • In a N node network, k neighbors per node (average) • 1 message broadcast per node • k messages received per node on average • (3 + k).Pow power consumed per node • Pow - power consumed per message reception • Power transmit = 3.power received

6. Percolation-Based Broadcast Protocols • A probabilistic model for broadcast • Not all nodes involved in broadcast • Exact mechanism depends on the actual scheme used • Three categories discussed in this presentation • Site Percolation • Bond Percolation • Modified-bond Percolation

7. Site Percolation • A gossip mechanism • Every node decides to broadcast based on some probability ? ? ? ? ? ? S ? ? ? ? ? ? ? ? ? Not all transmissions shown

8. Site Percolation • If p is the probability that a node broadcasts • p messages broadcast per node on average • kp messages received per node on average • (3 + k).p.Pow powerconsumed per node • Pow - power consumed per message reception • Power transmit = 3.power received

9. Bond Percolation • An alternative gossip mechanism • Nodes pick a subset of neighbors and unicast packets only to the chosen nodes S Not all transmissions shown

10. Bond Percolation • If m out of k neighborsare chosen • m unicastmessages are sent per node on average • m messages received per node on average • (3m + m).Pow = 4m.Pow power consumed per node • Pow - power consumed per message reception • Power transmit = 3.power received

11. Modified Bond Percolation • Same principle as bond percolation • Packets are broadcast (not unicast) • # neighbors receive broadcast depending on their sleep cycles • If m out of k neighborsare chosen • 1 message sent per node on average • m messages received per node on average • (3 + m).Pow power consumed per node • Pow - power consumed per message reception • Power transmit = 3.power received

12. Power Consumption Summary (3+k).pow (3+k).p.pow Flooding Site Percolation >= >= >= <= => Bond Percolation Modified Bond Percolation >= 4m.pow (3+m).pow

13. Power Consumption Summary • Modified bond percolation consumes the least power per broadcast • Bond percolation consumes the highest power followed by flooding • Site percolation consumes least power for sparse networks

14. Simulation Model • Three topologies – random, clustered, and grid • Number of nodes varied from 1000 to 2500 • Grid side (for grid topology) varied from 30 to 50 • MAC independent link layer based on actual traces • For site percolation, p = 0.7 • For bond percolation, m/k = 0.5

15. Power Consumed – Random Topology Average power # Nodes Modified bond percolation Bond percolation Site percolation Flooding

16. Broadcast Latency – Random Topology Average latency # Nodes Modified bond percolation Bond percolation Site percolation Flooding

17. Latency-Power Tradeoff – Random Topology Average power Average latency Modified bond percolation Bond percolation Site percolation Flooding

18. Tradeoff Summary • Flooding – More messages, more power, less latency • Site Percolation – Fewer messages, low power (in sparse networks), less latency • Bond percolation – Unicast messages, more power, high latency • Modified bond percolation – Few messages, least power, high latency

19. Where do they fit? • Code updates – reliability, low latency • Any of the percolation-based schemes (right parameters!) • Information query propagation – time sensitivity • Flooding or site percolation • Membership management – energy minimization • Modified bond percolation (dense) • Site percolation (sparse)

20. Conclusion • Broadcast protocols may have varied performance • Latency, power, number of messages propagated • Applications have varied requirements • Code updates, query propagation, membership management • Choosing the right broadcast protocol for the right application important • Code update – percolation • Query propagation – Flooding, site percolation • Membership management – Mod. bond or site percolation • Preferred match of protocols and applications shown through simulations and analyses

21. Thank You! WWASN 2009