  A sensor is a small electronic device which has the ability to sense, compute
and communicate either with other sensors or directly with a base station
(sink). In a wireless sensor network (WSN), the sensors monitor a region and
transmit the collected data packets through routes to the sinks. In this study,
we propose a mixed--integer linear programming (MILP) model to maximize the
number of time periods that a WSN carries out the desired tasks with limited
energy and budget. Our sink and sensor placement, scheduling, routing with
connected coverage ($SPSRC$) model is the first in the literature that combines
the decisions for the locations of sinks and sensors, activity schedules of the
deployed sensors, and data flow routes from each active sensor to its assigned
sink for connected coverage of the network over a finite planning horizon. The
problem is NP--hard and difficult to solve even for small instances. Assuming
that the sink locations are known, we develop heuristics which construct a
feasible solution of the problem by gradually satisfying the constraints. Then,
we introduce search heuristics to determine the locations of the sinks to
maximize the network lifetime. Computational experiments reveal that our
heuristic methods can find near optimal solutions in an acceptable amount of
time compared to the commercial solver CPLEX 12.7.0.
