A method of sub-optimal sensor placement: sensing coverage and data precision

We present a novel paradigm of sensor placement concerning data precision. Sensors are used to measure a quantity of a moving target in the scenario of a wireless sensor network. These sensors, cooperating with each other, estimate the quantity in a real-time manner. We consider a problem on a minimum-cost scheme of sensor placement. The problem is described with a grid model, and the approximation of such a description is presented. The problem is solved with the branch-and-bound method and tabu search. The experiments demonstrate the validation, efficiency and scalability of this algorithm.