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Localized Ant Colony of Robots for Redeployment in Wireless Sensor NetworksWang, Yuan 25 March 2014 (has links)
Sensor failures or oversupply in wireless sensor networks (WSNs), especially initial
random deployment, create both spare sensors (whose area is fully covered by other
sensors) and sensing holes. We envision a team of robots to relocate sensors and
improve their area coverage. Existing algorithms, including centralized ones and the
only localized G-R3S2, move only spare sensors and have limited improvement because
non-spare sensors, with area coverage mostly overlapped by neighbour sensors,
are not moved, and additional sensors are deployed to fill existing holes. We propose
a localized algorithm, called Localized Ant-based Sensor Relocation Algorithm with
Greedy Walk (LASR-G), where each robot may carry at most one sensor and makes
decision that depends only on locally detected information. In LASR-G, each robot
calculates corresponding pickup or dropping probability, and relocates sensor with
currently low coverage contribution to another location where sensing hole would be
significantly reduced. The basic algorithm optimizes only area coverage, while modified algorithm includes also the cost of robot movement. We compare LASR-G with
G-R3S2, and examine both single robot and multi robots scenarios. The simulation
results show the advantages of LASR-G over G-R3S2.
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Localized Ant Colony of Robots for Redeployment in Wireless Sensor NetworksWang, Yuan January 2014 (has links)
Sensor failures or oversupply in wireless sensor networks (WSNs), especially initial
random deployment, create both spare sensors (whose area is fully covered by other
sensors) and sensing holes. We envision a team of robots to relocate sensors and
improve their area coverage. Existing algorithms, including centralized ones and the
only localized G-R3S2, move only spare sensors and have limited improvement because
non-spare sensors, with area coverage mostly overlapped by neighbour sensors,
are not moved, and additional sensors are deployed to fill existing holes. We propose
a localized algorithm, called Localized Ant-based Sensor Relocation Algorithm with
Greedy Walk (LASR-G), where each robot may carry at most one sensor and makes
decision that depends only on locally detected information. In LASR-G, each robot
calculates corresponding pickup or dropping probability, and relocates sensor with
currently low coverage contribution to another location where sensing hole would be
significantly reduced. The basic algorithm optimizes only area coverage, while modified algorithm includes also the cost of robot movement. We compare LASR-G with
G-R3S2, and examine both single robot and multi robots scenarios. The simulation
results show the advantages of LASR-G over G-R3S2.
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