A Data-Centric Framework for Mobile Target Tracking in Sensor Networks

1. B’ B’ C’ C’ D’ D’ E’ F’ source Response (data) <r G’ Register Query H’ Storing node Type k target A Data-Centric Framework for Mobile Target Tracking in Sensor Networks Wensheng Zhang, Dr. Guohong Cao, and Dr. Tom La Porta Problem In many applications, a wireless network needs to detectandtrackmobile targets, and disseminate the sensing data to mobile sinks. Challenges Complete Information Requirements of Applications Energy Efficiency Limitations in sensor nodes Small Sensing Range Example: Battlefield Surveillance Collaboration Short Comm. Range Accurate Information Constrained Energy Supply Fault Tolerance Dynamic Data Source Security Prone to Failure, being Compromised Mobile Data Consumer Mobility Support Our Solution: A Data-Centric Framework Dynamic Convoy Tree-Based Collaboration (DCTC) Security Mechanisms Nodes individually detect their surrounding area, and generatelow-level sensing data. Motivations for DCTC • Why Dynamic? • -- The set of nodes involved in collaborations is dynamic Individual sensing data are collected and fused to form more complete and concise high-level sensing data. • Why Tree? • -- To efficiently facilitate data collection and fusion High-level sensing data are storedin network. High-level sensing data are disseminate to sinks when being queried. Basic Idea of DCTC • Nodes detecting the same target form a tree. • Relying on the tree, Root can collect data from other nodes, and process the data. Localized Collaboration-Based Security Mechanisms Collaborative Misbehavior Detection Individual detection: each node monitors its neighbors Discover misbehavior? YES Opinion collection: initiator sends out request to other neighbors (co-detectors) of the suspect to collect their opinions on the suspect. Diagnosis and result notification: collected opinions are processed to decide whether the suspect is misbehaving, and then sends out the result. • As the target moves, the convoy tree is reconfigured by adding some nodes and pruning some other nodes. Node-group Pair-wise Key-based Data Authentication (and False Data Filtering) Collaborative Key Updating • key points: • Keys of future versions are preloaded •  avoid updating-time key transmissions • The future keys of a node are collaboratively maintained by the node and its neighbors •  prevent a single node from stealing future keys • Random organization of keys •  prevent off-line analysis. • each node-group pair shares a key • a sender uses the keys it known to validate outgoing messages • a receiver or an intermediate node verify messages using the keys it known • polynomials are used to generate and maintain keys. • The tree is reconfigured as its root becomes faraway from the target key space keys known by a node • More Research on DCTC • Conservative vs. Optimistic (Prediction-based) Tree Expansion and Pruning Schemes • Complete vs. Interception-based Tree Reconfiguration Schemes • Sequential (Global) vs. LocalizedTreeReconfiguration Schemes (when nodes can adapt their transmission power) keys known by a group Data Dissemination with Adaptive Ring-Based Index (ARI) Why Ring? Why not Previous Schemes? Fault Tolerance Transparency Type k index nodes are connected via forwarding nodes to form an index ring encircling the index center (Lk) Adapting the index ring is transparent to sinks and sources. Directed Diffusion: flooding availability information. (TTDD has the similar problem.) External storage-based: unnecessary transfers of data. (DCS has the similar problem) source data sink The reliability of the index nodes can be improved due to adaptive replication. sink Lk Lk sink sink Lk Why Index-Based Scheme? to source Supporting sink mobility Supporting source mobility to source On-demand data transferring Load Balance sink move! Dealing with cluster failures node closest to Loc=hash(k) sink sink Query A B C D Query Source Index node Lk A B C D E Query Type k index node E Response (data) Type k index node F Overloaded! register Response (data) Lk F Query Lk Query Detecting node Storing node Detecting node target target target move! Ongoing Work:Heterogeneous Strategy for storing Data in Network Type k target Industry Day 2004 @ NET-CENTER . PSU