When a large collection of objects (e.g., robots, sensors, etc.) has to be deployed in a given environment, it is often required to plan a coordinated motion of the objects from their initial position to a fi-nal configuration enjoying some global property. In such a scenario, the problem of minimizing the distance travelled, and therefore energy con-sumption, is of vital importance. In this paper we study several motion planning problems that arise when the objects must be moved on anet-work, in order to reach certain goals which are of interest for several network applications. Among the others, these goals include broadcast-ing messages and forming connected or interference-free networks. We study these problems with the aim to minimize a number of natural measures such as the average/overall distance travelled, the maximum distance travelled, or the number of objects that need to be moved. To this respect, we provide approximability and inapproximability results, most of which are tight.
Exact and Approximate Algorithms for Movement Problems on (Special Classes of) Graphs
D. Bilò;S. Leucci;PROIETTI, GUIDO
2013-01-01
Abstract
When a large collection of objects (e.g., robots, sensors, etc.) has to be deployed in a given environment, it is often required to plan a coordinated motion of the objects from their initial position to a fi-nal configuration enjoying some global property. In such a scenario, the problem of minimizing the distance travelled, and therefore energy con-sumption, is of vital importance. In this paper we study several motion planning problems that arise when the objects must be moved on anet-work, in order to reach certain goals which are of interest for several network applications. Among the others, these goals include broadcast-ing messages and forming connected or interference-free networks. We study these problems with the aim to minimize a number of natural measures such as the average/overall distance travelled, the maximum distance travelled, or the number of objects that need to be moved. To this respect, we provide approximability and inapproximability results, most of which are tight.Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.