Scalable Coverage Maintenance for Dense Wireless Sensor Networks Jun Lu, Jinsu Wang, Tatsuya Suda University of California, Irvine Secon ‘ 06

Outline Introduction Scalable Coverage Maintenance (SCOM) Assumptions Problem Statement Scheme Description Redundancy Eligibility Rule Performance Evaluation Conclusions

Introduction In future WSNs are composed of a vast number of miniaturized sensors The critical challenge in WSNs is to sustain long-term operation on limited battery energy

Introduction High scalability to sensor deployment density in terms of communication overhead and computational complexity To decide coverage redundancy by checking only a small number of locations

Introduction High energy efficiency to maintain the required coverage and load balancing among sensor

SCOM_ Assumption Sensors are static Each sensor knows its own location Sensors can acquire the location of one hop neighbor

SCOM_ Assumption Sensors have synchronized timers and are aware of the amount residual energy Communication range is at least twice the sensing range

SCOM_ Problem Statement A location is covered by a sensor if it is within the SR of the sensor A location is said to be K-covered if it is within the SR of at least K sensors A region is K-covered if every location within the region is K-covered

SCOM_ Assumption K-coverage Maintenance Location Subset of S

SCOM_ Scheme Description Decision phase Bootstrap, Active, Inactive state According to local coverage and energy information Optimization phase Sensors optimize the coverage by turning off redundant active sensors

Decision phase Bootstrap state T decision =  *(1-p)+  Residual energy percentage level Check whether its sensing region is K-covered Active state and broadcasts a TURNON beacon Add the sender into the active neighbor list and stores the coordinates of the sender Random between [0,  ] Decision phase lasts for (  +  ) time units

Optimization phase An active sensor sets a back-off timer T opt according to its residual energy If it is redundant, switches to INACTIVE state and broadcasts a TURNOFF beacon, and active neighbor removes the sender from its active neighbor list

SCOM_ Redundancy Eligibility Rule Sensors with Homogenous SR Critical Point Set : S i The intersection points between the sensing perimeters of n within the sensing range of i One intersection point between the sensing perimeters of n and sensor i

SCOM_ Redundancy Eligibility Rule If S i is not empty and the sensing region of sensor i is K-covered by its neighbors if and only if each critical point in S i is K- covered by its neighbors If S i is empty, the sensing region of sensor i is not K-covered by its neighbors

SCOM_ Redundancy Eligibility Rule Sensors with Heterogeneous SR Extended Critical Point Set : ES i The critical points in sensor i ’s critical point set A sampling point on each sensing perimeter that is within sensor i ’s sensing region and does not intersect with any other sensing perimeter

SCOM_ Redundancy Eligibility Rule If ES i is not empty, the sensing region of sensor i is K-covered by its neighbors if and only if each critical point in ES i is K- covered by its neighbors If ES i is empty, the sensing region of sensor i is K-covered by neighboring sensors if and only if a sampling point within the sensing region of sensor i is K-covered by its neighbors

Performance Evaluation A square region of 100m x 100m  and  are set to 10.0 and 1.0 For homogeneous networks SR : 10m For heterogeneous networks SR : 5m, 10m, 15m

Performance Evaluation Sponsor Sector (SS) scheme Every sensor calculates its eligibility for turning off A sensor is eligible to turn off if its sensing region is contained by the union of the SS A back off mechanism is used to avoid blind points

Performance Evaluation Differentiated Surveillance (DS) Each sensor randomly generates a time reference point and broadcasts it Target region is covered with a virtual square grid, a sensor decides the working schedule based on time reference points Final schedule of the sensor is the union of the working schedules for all the grid points

Communication Overhead

Computational complexity

Energy Conservation

Load Balance

Conclusion This paper proposed SCOM that conserves energy by autonomously decide their states High scalability to sensor deployment density SCOM outperforms several existing researches on energy efficiency

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