- 1 - Intentional Mobility in Wireless Sensor Networks Deployment, Dispatch, and Applications Dr. You-Chiun Wang ( 王友群 ) Department of Computer Science,

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Presentation transcript:

- 1 - Intentional Mobility in Wireless Sensor Networks Deployment, Dispatch, and Applications Dr. You-Chiun Wang ( 王友群 ) Department of Computer Science, National Chiao-Tung University 2010/10/22

- 2 - Wireless Sensor Networks SENSROS ARE STATIC!

- 3 - “Mobile” Sensor Networks Some sensor nodes can move around (e.g., robots). Purpose: automatic deployment, network repairing, and sensor dispatch

- 4 - Topics Automatic Deployment Mobile Sensor Dispatch Systems & Applications  iMouse System  VSN (Vehicular Sensor Network) System

- 5 - Automatic Deployment SENSROS ARE MOBILE!

- 6 - In a “Perfect” World

- 7 - In a “Real” World network partition partial coverage

- 8 - Can Sensors Reorganize a WSN “by Themselves”? network partition partial coverage

- 9 - Question A Given a sensing field A possibly with obstacles, how can we make mobile sensors automatically deploy a network in an efficient way?  Use the smallest number of sensors.  Sensors can consume the minimum energy to reorganize the network

Overview of Solutions We first calculate the locations to place sensors and then dispatch mobile sensors to these locations.  Placement solution should use fewer sensors.  Dispatch solution should move sensors so that they can remain the maximum energy after movement. placement Energy dispatch

Placement Algorithm A Partition a sensing field A into sub-regions and then place sensors in each region:  Single-row regions  A belt-like area between obstacles whose width is NOT larger than, where r min = min(r s, r c ).  We can deploy a sequence of sensors to satisfy both coverage and connectivity.  Multi-row regions  We need multiple rows of sensors to cover such areas.  Note: obstacles may exist in such regions.

Step 1: Partition the Sensing Field A From A, we first identify all single-row regions. A’s  Expand the obstacles’ perimeters outwardly and A’s boundaries inwardly by a distance of.  If the expansion overlaps with obstacles, we take a projection to obtain single-row regions. The remaining regions are multi-row regions.

Step 2: Place Sensors in a Single-Row Region Place sensors along the bisector of region.

Step 3: Place Sensors in a Multi-Row Region Place sensors row by row.  A row of sensors guarantee coverage and connectivity.  Adjacent rows guarantee continuous coverage.

Step 4: Handle the Boundary Case Three unsolved problems  Some areas near the boundaries are NOT covered.  Connectivity between adjacent rows needs to be maintained.  Connectivity to neighboring regions should be maintained. Solutions  Sequentially place sensors along the boundaries.  Not all boundaries should be placed with sensors.

Dispatch Algorithm (1/5) Find a maximum-weight maximum matching in a weighted complete bipartite graph.  Sensors vs. locations We should take care of the obstacles inside the sensing field. A I

Dispatch Algorithm (2/5) I B D C E I Run sensor placement algorithm on I to get the target locations. L={(x 1, y 1 ), (x 2, y 2 ), (x 3, y 3 ), (x 4, y 4 )}  Compute energy cost A

Dispatch Algorithm (3/5) Construct the weighted complete bipartite graph. A B C D E Sensors Locations Weights of edges: w(s i,l j ) = 40 – c(s i,l j ) - objective function: remaining energy - all sensors have initial energy of 40 ABCDE A  1: needs 9 energy weight (A,1) = 40 – 9 = 31

Dispatch Algorithm (4/5) Find the maximum-weight maximum matching.  Hungarian Method: finds the optimal solution in O(n 3 ). A B C D E Sensors Locations ABCDE

Dispatch Algorithm (5/5) Sensors are dispatched to the matched locations. A B C D E I A B D C E Does not move Sensors Locations