1. Storage Management Issues for Sensor Networks Sameer Tilak (SUNY Binghamton) Wendi Heinzelman (Univ. of Rochester) Nael Abu-Ghazaleh (SUNY Binghamton)

2. Network Partitioning

3. Problem For tiny sensors storage is a scarce resource Naïve protocols can lead to loss of information or inefficient storage Need efficient storage management protocol Un-partitioned network If delays can be tolerated instead of reporting to the base station, data can be aggregated and stored in the network to increase energy efficiency

4. Protocol Design Goals Higher storage-time Low average storage/sensor Fault-tolerance, high reliability Scalable Low protocol overhead High energy efficiency

5. Candidate Protocols Local Storage Deterministic Broadcast (Bcast) Probabilistic Broadcast (PBcast) Clustering

6. Local Storage No communication Each sensor stores its own data locally, low fault-tolerance No spatial aggregation = storage/sensor

7. Broadcast (Bcast) All sensors store data All sensors broadcast data to neighbors, high fault-tolerance Spatial aggregation possible = storage/sensor

8. PBcast Sensors probabilistically send/store data, high fault-tolerance Spatial aggregation possible = storage/sensor

9. Clustering Only CH stores data Rotate CH Distributed storage, medium fault-tolerance Spatial aggregation possible Round 1 (time = 0) Round 2 (time = 20) Round 1 (time = 40)

10. Protocol Comparison MetricLocalBcastPBacstClustering Storage- time Low Mediu m High Fault- tolerance LowHigh Medium ScalabilityHighLowMediu m High OverheadLow Medium Energy efficiency HighLow High

11. Clustering: Scales well, low storage Bcast: Scaling problem, high storage Pbcast,Local: Scales well