1. Zone Sharing: A Hot-Spots Decomposition Scheme for Data-Centric Storage in Sensor Networks Mohamed Aly Nicholas Morsillo Panos K. Chrysanthis Kirk Pruhs Advanced Data Management Technologies Lab Dept. of Computer Science University of Pittsburgh DMSN’05

2. M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 2 Roadmap Background Problem Statement: Storage Hot-spots Algorithms: Zone Sharing Experimental Results Conclusions

3. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 3 Sensor Networks Data Characteristics Monitoring Applications: One or more phenomenon Sensor readings: events An event contains one or more attributes for each phenomenon under concern Querying load variations Continuous queries: e.g. habitat monitoring applications Ad-hoc queries: e.g. disaster management applications

4. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 4 Sensor Networks Data Storage Options Base station storage Events are sent to base stations where queries are issued and evaluated Best suited for continuous queries In-Network storage Events are stored in the sensor nodes Best suited for ad-hoc queries

5. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 5 Data-Centric Storage Quality of Data (QoD) of ad-hoc queries Define an event owner based on the event value Examples: Distributed Hash Tables (DHT) [Shenker et. al., HotNets’03] Geographic Hash Tables (GHT) [Ratnasamy et. al., WSNA’02] Distributed Index for Multi-dimensional data (DIM) [Li et. al., SenSys’03] Greedy Perimeter Stateless Routing algorithm (GPSR) [Karp & Kung, Mobicom’00] Among the above schemes, DIM has been shown to exhibit the best performance

6. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 6 Storage Hot-Spots S1 x є [1,10] S2 x є [10,20] S3 x є [20,30] S4 x є [30,40] 50% 40% 7% 3%

7. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 7 Zone Sharing in DIM S2 x є [10,20] y є [1,10] S3 x є [10,20] y є [10,20] S1 x є [1,10] y є [1,20] Z = 0 Z = 10 Z = 11 70% 5% 25% S1 S2S3 A = 0 A = 10 A = 11

8. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 8 Zone Sharing in DIM S2 x є [1,10] y є [1,10] S3 x є [10,20] y є [1,20] S1 x є [1,10] y є [10,20] Z = 01 Z = 00 Z = 1 35% 30% (donor) (migrator) (receiver) S3 S2S1 A = 1 A = 00 A = 01

9. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 9 Hot-Spot Decomposition in Zone Sharing

10. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 10 Hot-Spot Decomposition in Zone Sharing

11. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 11 Hot-Spot Decomposition in Zone Sharing

12. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 12 Hot-Spot Decomposition in Zone Sharing

13. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 13 Hot-Spot Decomposition in Zone Sharing

14. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 14 Hot-Spot Decomposition in Zone Sharing

15. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 15 Hot-Spot Decomposition in Zone Sharing

16. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 16 Hot-Spot Decomposition in Zone Sharing

17. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 17 Hot-Spot Decomposition in Zone Sharing

18. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 18 Hot-Spot Decomposition in Zone Sharing

19. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 19 Hot-Spot Decomposition in Zone Sharing

20. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 20 Storage Safety Requirement (1) Pre-migration load (donor) >> post-migration load (receiver) l donor / (l migrator + l receiver ) ≥ C 1 C 1 should be greater than or equal to 2 to make sure that the donor is really falling in a hot-spot Evaluated by donor and receiver

21. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 21 Storage Safety Requirement (2) Post-migration load (migrator) >> pre-migration load (migrator) T / l migrator ≥ C 2 C 2 should be greater than or equal to 2 to avoid cyclic migrations Applied solely by migrator

22. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 22 Energy Safety Requirement (1) Energy consumed (donor) << total energy (donor) T / e donor ≤ E 1 E 1 must be less than or equal to 0.5 Applied only by donor

23. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 23 Energy Safety Requirement (2) Energy consumed (migrator) << total energy (migrator) (l migrator + r e * T) / e migrator ≤ E 2 E 2 must be less than or equal to 0.5 Applied only by migrator

24. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 24 Energy Safety Requirement (3) Energy consumed (receiver) << total energy (receiver) l migrator * r e / e receiver ≤ E 3 E 3 must be less than or equal to 0.5 Applied only by migrator

25. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 25 Distributed Migration Criterion (DMC) 1. l donor / (l migrator + l receiver ) ≥ C 1 2. T / l migrator ≥ C 2 3. T / e donor ≤ E 1 4. (l migrator + r e * T) / e migrator ≤ E 2 5. l migrator * r e / e receiver ≤ E 3

26. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 26 Single-Hop Zone Sharing (SHZS) Goal: Overall minimal changes to the original DIM Single Hop Zone Sharing: A zone can be traded at most once Periodic exchange of neighbors information DMC applied locally by nodes No changes needed to GPSR Applicability: Small Hot Spots

27. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 27 Single-Hop Zone Sharing (SHZS) Problems: Large hot-spots: overloaded neighbors  DMC hard to be satisfied Zone traded only once  nodes still in hot-spots after migration process Messages pass by original destination (donor) before going to migrator  energy consumption overhead Solution: Allow a zone to be traded more than once

28. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 28 Multi-Hop Zone Sharing (MHZS) A zone can be traded more than once A new data structure: Traded Zoned List Keeps track of the traded zones to redirect messages to their new destinations An entry is composed of 3 values: (zone address, original owner, final owner) GPSR changed to check the list first and update the destination field in the message

29. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 29 Roadmap Background Problem Statement: Storage Hot-spots Algorithms: Zone Sharing Experimental Results Conclusions

30. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 30 Simulation Description Compare: DIM, SHZS, and MHZS. Simulator similar to the DIM’s [Li et. al., SenSys’03] Two phases: insertion & query. Insertion phase Each sensor initiates 5 events Events forwarded to owners Query phase Queries of sizes 10% to 100% of the attributes ranges

31. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 31 Experimental Setup ParameterValue Network size50 to 300 sensors Initial energy50 units Energy unitenergy needed to send one event C 1 & C 2 2 E 1, E 2, and E 3 0.3 Number of hot-spots1 Hot-spot sizes (X,Y)10% - 50% of the events (X) falling into 10% of the attribute ranges (Y) Sensor node storage capacity15 units (events)

32. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 32 Experimental Results: Data Persistence Dropped Events for a network with a (50%, 10%) Hot-Spot

33. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 33 Experimental Results: QoD Result Size of a 50% Query for a network with a (50%, 10%) Hot-Spot

34. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 34 Experimental Results: Load Balancing Note: An overloaded node is a node reaching its max. capacity Overloaded Nodes for a network with a (40%, 10%) Hot-Spot

35. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 35 Experimental Results: Energy Consumption Average Node Energy for a network with a (50%, 10%) Hot-Spot

36. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 36 Conclusions Contribution: A storage hot-spots decomposition scheme for DCS sensor nets Two versions: SHZS & MHZS Experimental validation of its practicality Current ZS extensions: Hot-spots incremental avoidance scheme (submitted for publication) Possibility of ZS generalizations: Non-uniform loads for individual sensors Upper bound for ZS max. trading hops (nMHZS)

37. DMSN’05 M. Aly, N. Morsillo, P. K. Chrysanthis, K. Pruhs 37 Thank You Questions ? Advanced Data Management Technologies Lab http://db.cs.pitt.edu