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Storage Management Issues for Sensor Networks

Storage Management Issues for Sensor Networks. Sameer Tilak (SUNY Binghamton) Wendi Heinzelman (Univ. of Rochester) Nael Abu-Ghazaleh (SUNY Binghamton). Network Partitioning. Problem. For tiny sensors storage is a scarce resource

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Storage Management Issues for Sensor Networks

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  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 = storage/sensor • No communication • Each sensor stores its own data locally, low fault-tolerance • No spatial aggregation

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

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

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

  10. Protocol Comparison

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

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