Optimizing Tree Reconfiguration for Mobile Target Tracking in Sensor Networks

1. INFOCOM 2004 Optimizing Tree Reconfiguration for Mobile Target Tracking in Sensor Networks Wensheng Zhang and Guohong Cao The Pennsylvania State University 산업 및 시스템 공학과 통신시스템 및인터넷보안연구실 20075273 김효원

2. Outline • Introduction • Overview of DCTC • Optimizing TR Schemes • Root Replacement • OCR(Optimized Complete Reconfiguration) • OIR(Optimized Interception-based Reconfig.) • Performance Evaluation • Conclusion

3. Introduction • Overview of DCTC • Optimizing TR Schemes • Performance Evaluation • Conclusion

4. Introduction • Sensor network • Advances in micro-electro-mechanics and wireless communication • Adopted to many military and civil application • Sensor collaboration • limitations of sensor node • Obtain fine-grain, high-precision sensing data

5. Introduction • Sensor collaboration issue in target tracking • Sensor node promptly detect target, generate reports and send in fast and energy efficient way • In this paper, • use DCTC framework and optimize tree reconfiguration to minimize energy consumption • propose 2 optimized schemes • OCR(Optimized Complete Reconfiguration) • OIR(Optimized Interception-based Reconfiguration)

6. Introduction • Overview of DCTC • Basic Structure • Details • Problem of Optimizing Tree Reconfiguration • Optimizing TR Schemes • Performance Evaluation • Conclusion

7. Overview of DCTC • Dynamic Convoy Tree-based Collaboration • Basic structure of DCTC

8. Overview of DCTC • Dynamic Convoy Tree-based Collaboration • Construct Initial Convoy Tree Target Enters the detection region Nodes close to target construct initial convoy tree by selecting root using root election algorithm The other node in monitoring region are added to convoy tree

9. Overview of DCTC • Dynamic Convoy Tree-based Collaboration • Collecting Sensing Data via Tree • Tree Expansion and Pruning As target moves, some nodes far away from target are pruned Root should predict target moving direction and activate right group of sensor node

10. Overview of DCTC • Dynamic Convoy Tree-based Collaboration • Tree Reconfiguration if necessary As target moves, many nodes become far away from target and energy may be wasted To reduce overhead, root should be replaced by node closer to the center of monitoring region

11. Overview of DCTC • Problem of Optimizing Tree Reconfiguration • Total energy in convoy tree sequence • Convoy tree sequence • As trees are reconfigured, a sequence of trees exists at different data collection time • Optimizing tree reconfiguration = finding min-cost convoy tree sequence Data collection Tree reconfiguration

12. Introduction • Overview of DCTC • Optimizing TR Schemes • Root Replacement • OCR(Optimized Complete Reconfiguration) • OIR(Optimized Interception-based Reconfig.) • Performance Evaluation • Conclusion

13. Optimizing TR Schemes • Reconfiguration of convoy tree • Convoy tree is reconfigured in two step

14. Optimizing TR Schemes • Reconfiguration of convoy tree • Convoy tree is reconfigured in two step

15. Optimizing TR Schemes • Root Replacement • Rule 1. Root predicts Lt+1 (t+1 : next data collection time) 2. Distance check (dr : threshold) 3. Determine Root change (R→R’ )

16. Optimizing TR Schemes • Root Replacement • Rule Old Root 4. Send message grid head 5. Grid head select new root (the node closest to Lt+1) New Root Tree have a short height and small energy consumption during data collection Root that is far away from sensing node may consume lots of network bandwidth and power to send data

17. Optimizing TR Schemes • Generic Method for Optimizing dr • Overall energy consumption = data collection + tree reconfiguration • Selecting appropriate value for dr is important • Large dr → high overhead for data collection • Small dr → high overhead for tree reconfiguration • Selecting Optimal dr → minimizes overall energy consumption

18. Optimizing TR Schemes • Generic Method for Optimizing dr • Average energy consumption during k(v) : target moving velocity : root replacement occurring time : data collection overhead (energy consumption) (distance between root and target is x) : tree reconfiguration overhead (energy consumption) (distance between root and target is x)

19. Optimizing TR Schemes • Generic Method for Optimizing dr • To minimize → • Nodes do not have to compute k(v) on-line • The function can be calculated off-line and distributed to the related sensor node • In the following section.. • For computing k(v) • Describe how to compute Ed(x), Et(x) in OCR, OIR

20. Introduction • Overview of DCTC • Optimizing TR Schemes • Root Replacement • OCR(Optimized Complete Reconfiguration) • OIR(Optimized Interception-based Reconfig.) • Performance Evaluation • Conclusion

21. Optimizing TR Schemes • Optimized Complete Reconfiguration (OCR) • OCR scheme • Reconfigures all nodes in the tree After root replacement Broadcast reconf(R, R’) Before complete reconfiguration After complete reconfiguration

22. Optimizing TR Schemes • Optimized Complete Reconfiguration (OCR) • OCR scheme • Algorithm executed by root R’ dr

23. Optimizing TR Schemes • Optimized Complete Reconfiguration (OCR) • OCR scheme • Algorithm executed by node i in the tree Ni 중 R’과의 거리가 최소가 되는 노드 : set of neighbors of node i : parent of node i : children of node i : message to init tree reconfig. dr : message to detach i from Pi : message to attach i to j

24. Optimizing TR Schemes • Optimized Complete Reconfiguration (OCR) • Overhead Analysis (Data Collection) • Energy consumed to send report to R from node P(x, y) • Energy consumed by data collection # of hop (using (A2)) data report size node density (A2) # of hop between two nodes is proportional to geographic distance # of hop in the area

25. Optimizing TR Schemes • Optimized Complete Reconfiguration (OCR) • Overhead Analysis (Tree Reconfiguration) • Reconfiguration occurs exactly when • Each node sends detach message to old parent • Each node sends attach message to new parent • Energy consumed by tree reconfiguration control message size

26. Introduction • Overview of DCTC • Optimizing TR Schemes • Root Replacement • OCR(Optimized Complete Reconfiguration) • OIR(Optimized Interception-based Reconfig.) • Performance Evaluation • Conclusion

27. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • OIR scheme • Only reconfigures a small part of the tree After root replacement Broadcast reconf(R, R’) between (l0, l1) in morintoring region After interception based reconfig. Process of interception-based reconfig.

28. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • OIR scheme • Algorithm executed by root R’ Ed(x), Et(x) is calculated by Eq(11), Eq(12)

29. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • OIR scheme • Algorithm executed by node i in the tree and Check dr between (l0, l1) in morintoring region

30. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • Overhead Analysis (Data Collection) • For nodes between lines l0 and l1 • Energy consumed to collect data (P0 locates between l0 and l1) # of hop (between P0, R)

31. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • Overhead Analysis (Data Collection) • For nodes on the left side of l1 • Path between P1 and R may not be optimized • Energy consumed to collect data (P0 locates left side of l1) n is small → c1 is small (c1 = 1.1 in this paper)

32. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • Overhead Analysis (Data Collection) • For nodes on the right side of l0 • Similar to previous case • Path between P2 and R may not be optimized • Energy consumed to collect data (P2 locates right side of l0)

33. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • Overhead Analysis (Data Collection) • Energy consumed by data collection

34. Optimizing TR Schemes • Optimized Interception-Based Reconfig. (OIR) • Overhead Analysis (Tree Reconfiguration) • Reconfiguration occurs exactly when • Each node within l0, l1 sends detach msg. to old parent • Each node within l0, l1 sends attach msg. to new parent • Energy consumed by tree reconfiguration

35. Optimizing TR Schemes • Comparison between OCR & OIR • OCR and OIR take different approaches to optimize overall energy consumption • OCR : higher priority to data collection • OIR : higher priority to tree reconfiguration • OIR outperforms OCR when velocity is high, sd/sc or ds/dc is small • High velocity : OIR has smaller tree reconfig. overhead • sd/sc small : OIR has smaller data collection overhead • ds/dc small : OIR has smaller data collection overhead

36. Introduction • Overview of DCTC • Optimizing TR Schemes • Performance Evaluation • Energy Consumption Results • Data Collection Delay • Impact of Movement Prediction Accuracy • Conclusion

37. Performance Evaluation • Simulation • Evaluate performance of proposed schemes • Compare to other non-optimized reconf. scheme • Non-optimized reconfiguration schemes

38. Performance Evaluation • Energy Consumption Results • Comparing Energy Consumption • Varying v, sd/sc and ds/dc • As v increase → energy consumption increases • OCR > ACR > CCR, OIR > AIR > ACR • CCR > CIR • Tree reconf. frequency is low → Data collection dominates • AIR > ACR • Tree reconf. frequency is high → Tree reconf. dominates • OIR > OCR (sd/sc ,ds/dc : small) • OCR > OIR (sd/sc ,ds/dc : large)

39. Performance Evaluation • Data Collection Delay • Frequent reconfiguration reduce height of tree • ACR > OCR > CCR, AIR > OIR > CIR • Compared to CR, IR changed small part of tree → larger height • ACR > AIR, OCR > OIR, CCR > CIR • Data collection delay of OIR and OCR are not optimal • But, difference to the optimal value is reasonable

40. Performance Evaluation • Impact of Movement Prediction Accuracy • Simulation Model • Every 10sec, target may change its moving direction and/or velocity • With probability pk, the direction and velocity of target keep unchanged • Simulation Results • As pk drops, energy consumption increases • As pk drops, the chance of wrong prediction increases → Increasing reconfiguration overhead • Energy consumption does not increase too much if pk is not very low

41. Introduction • Overview of DCTC • Problem of Optimizing Tree Reconfiguration • Optimizing TR Schemes • Performance Evaluation • Conclusion

42. Conclusions • Optimizing tree reconfiguration when target moves • Formulize as finding min-cost convoy tree seq. • Solved it by proposing • OCR (Optimized Complete Reconfiguration) • Minimize data collection energy • OIR (Optimized Interception-based Reconfiguration) • Minimize tree reconfiguration energy • OCR, OIR optimizes by selecting appropriate root replacement threshold to minimize energy • Simulation results, Optimized schemes are better • OIR outperforms OCR when sd or sc is small