  In this article, we propose an energy-efficient data gathering scheme for
wireless sensor network called Sleep-Route, which splits the sensor nodes into
two sets - active and dormant (low-power sleep). Only the active set of sensor
nodes participate in data collection. The sensing values of the dormant sensor
nodes are predicted with the help of an active sensor node. Virtual Sensing
Framework (VSF) provides the mechanism to predict the sensing values by
exploiting the data correlation among the sensor nodes. If the number of active
sensor nodes can be minimized, a lot of energy can be saved. The active nodes'
selection must fulfill the following constraints - (i) the set of active nodes
are sufficient to predict the sensing values of the dormant nodes, (ii) each
active sensor nodes can report their data to the sink node (directly or through
some other active node(s)). The goal is to select a minimal number of active
sensor nodes so that energy savings can be maximized.
  The optimal set of active node selection raise a combinatorial optimization
problem, which we refer as Sleep-Route problem. We show that Sleep-Route
problem is NP-hard. Then, we formulate an integer linear program (ILP) to solve
the problem optimally. To solve the problem in polynomial time, we also propose
a heuristic algorithm that performs near optimally.
