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Optimizing Tree Reconfiguration for Efficient Mobile Target Tracking in Sensor Networks

This paper presents a method for optimizing tree reconfiguration in sensor networks aimed at mobile target tracking. We introduce a Dynamic Convoy Tree-based Collaboration (DCTC) framework that starts with constructing an initial convoy tree and implementing a root election algorithm. Nodes connect to their closest neighbors to the root, allowing for efficient data collection and processing. The method includes strategies for tree expansion and pruning, predicts the upcoming root replacements, and balances energy consumption between data collection and tree reconfiguration. Key comparisons between Optimized Complete Reconfiguration (OCR) and Optimized Interception-based Reconfiguration (OIR) illustrate their respective overhead analyses.

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Optimizing Tree Reconfiguration for Efficient Mobile Target Tracking in Sensor Networks

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  1. Wensheng Zhang and GuohongCao Optimizing tree reconfiguration for mobile target tracking in sensor networks

  2. Dynamic Convoy Tree-based Collaboration (DCTC) • Constructing the Initial Convoy Tree • Apply existing root election algorithm • Other node connect to a neighbor closest to the root • Collecting sensing data via the tree • Root receives reports and processes them • Tree expansion and pruning • Apply existing prediction schemes to involve new nodes • Prune useless nodes (too far from the target) • Change the root node • The root node makes all decisions

  3. Energy consumption • E = Ed + Et (for each time interval) • Ed: Data collection • Et : Tree reconfiguration • Min-cost tree Problem of Optimizing Tree Reconfiguration Equal to Find a min-cost convoy tree sequence

  4. Optimizing Tree Reconfiguration Schemes • A convoy tree is reconfigured in two steps • The current root is replaced by a new one • The remaining part of the tree is reconfigured to reduce the communication overhead

  5. Root Replacement • R predicts Lt+1 • Replace R, if DR, Lt+1 >dr • dr • Large: high overhead on data collection • Small: high overhead on tree reconfiguration • How to determine dr?

  6. How to determine dr? • k(v) = dr/ v • time units a target needs to travel through dr • Nodes send reports to Root on every time unit • The average energy consumption between two root replacement:

  7. Optimized Complete Reconfiguration (OCR) • The current root decides and initiates root replacement • New root notifies all nodes this change. • Reconfigure the tree: Each node connects to the neighbor closest to the new root node.

  8. OCR overhead analysis • Data collection energy: • Tree reconfiguration energy:

  9. Optimized Interception-based Reconfiguration (OIR) • The current root decides and initiates root replacement • New root notifies all nodes this change. • Reconfigure the tree: Each node checks whether it needs to change its parent node.

  10. OIR overhead analysis

  11. OCR vs OIR • OCR:Higher priority on Data Collection • OIR: Higher priority on Tree Reconfiguration • High target velocity, small sd/sc, small ds/d

  12. Thanks Q&A

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