In this paper, the minimum-length scheduling problem in wireless networks is studied, where each source of traffic has a finite amount of data to deliver to its corresponding destination. Our objective is to obtain a joint scheduling and rate control policy to minimize the total time required to deliver this finite amount of data from all sources. First, networks with time-invariant channels are considered. An optimal solution is provided by formulating the minimum-length scheduling problem as finding a shortest path on a single-source directed acyclic graph. However, finding the shortest paths is computationally hard since the number of vertices and edges of the graph increases exponentially in the number of network nodes, as well as in the initial traffic demand values. Toward this end, a simplified version of the problem is considered for which we explicitly characterize the optimal solution. Next, our results are generalized to time-varying channels. First, it is shown that in case of time-varying channels, the minimum-length scheduling problem can be formulated as a stochastic shortest path problem and then an optimal policy is provided that is based on stochastic control. Finally, our analytical results are illustrated with a set of numerical examples.
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