This paper describes collaborative sensing and actuation algorithms for environment control in the framework of optimization. The sensor network topology is self-configured according to the sensing information to optimize sensing utility. Experimental results show that the algorithms provide the sensor network topology for optimal sensing. The server can gather the sensing data from all sensor nodes robustly using the collaborative sensing algorithm and calculate the control signals for actuators to balance energy savings against the quality of the control signals. In addition to a centralized algorithm, a distributed algorithm is also proposed to calculate the control signals. Simulations reveal that the distributed algorithm, which is more scalable than the centralized one, can provide the same performance as the centralized one.
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