This paper is to study the object coverage problem in visual sensor networks. When sensors equipped camera with rotating capability in the monitoring environment are deployed randomly, the images of target object with circle shape may be captured by different camera nodes in different orientations at the same time. In order to achieve the full coverage of an object, there might be lots of redundant image data to consume the transmission energy in visual sensor networks. An approach is proposed to reduce the cover set of camera nodes by rotating cameras of sensors. Such a set can cover the entire object using as few sensors as possible. In addition, a mapping is proposed for find out the coverage problem for target objects with convex polygon shape. The simulation results show that our approach can reduce the number of sensors while preserving the maximum coverage range of object.

A methodology is described whereby a linear ADT may be rigorously encapsulated within a state monad. A CPS-like translation from the original ADT axioms into monadic ones is also described and proven correct, so that reasoning can be accomplished at the monadic level without exposing the state. The ADT axioms are suitably constrained by a linear type system to make this translation possible. This constraint also allows the state to be "updated in place," a notion made precise via a graph-rewrite operational semantics. 1 Introduction In recent years, numerous proposals for I/O, destructive updates to data structures, mutable variables, nondeterminism, and concurrency have been put forth, all using monads to structure programs in such a way that details of the computation are effectively hidden and encapsulated [18, 20]. One of the most important uses of monads is in dealing with state, resulting in a style of programming referred to appropriately by Peyton Jones and Wadler as imperativ...