  In this paper we study the deployment of multiple unmanned aerial vehicles
(UAVs) to form a temporal UAV network for the provisioning of emergent
communications to affected people in a disaster zone, where each UAV is
equipped with a lightweight base station device and thus can act as an aerial
base station for users. Unlike most existing studies that assumed that a UAV
can serve all users in its communication range, we observe that both
computation and communication capabilities of a single lightweight UAV are very
limited, due to various constraints on its size, weight, and power supply.
Thus, a single UAV can only provide communication services to a limited number
of users. We study a novel problem of deploying $K$ UAVs in the top of a
disaster area such that the sum of the data rates of users served by the UAVs
is maximized, subject to that (i) the number of users served by each UAV is no
greater than its service capacity; and (ii) the communication network induced
by the $K$ UAVs is connected. We then propose a $\frac{1-1/e}{\lfloor \sqrt{K}
\rfloor}$-approximation algorithm for the problem, improving the current best
result of the problem by five times (the best approximation ratio so far is
$\frac{1-1/e}{5( \sqrt{K} +1)}$), where $e$ is the base of the natural
logarithm. We finally evaluate the algorithm performance via simulation
experiments. Experimental results show that the proposed algorithm is very
promising. Especially, the solution delivered by the proposed algorithm is up
to 12% better than those by existing algorithms.
