Abstract

Cluster scheduling respecting collision avoidance is a complex problem in cluster-tree wireless sensor networks (WSNs). The difficulty of the problem also increases significantly when the traffic is organized as time-constrained data flows with opposite directions. Thus, in this paper, we seek a collision-free cluster schedule that meets all the data flow deadlines as given in time units. In this context, we have found an elegant approach that expresses the deadline of each flow as an integer number of the length of the schedule period (i.e., period crossing constraints). Consequently, the data flow timeliness requirements become easier to be tackled. Due to the scarce resources of the WSNs, the minimization of the energy consumption of the nodes is a problem of paramount importance. Therefore, the objective is to maximize the lifetime of the network by maximizing the time when the nodes stay in low-power mode. In this paper, we present a novel heuristic scheduling algorithm to obtain the desired schedule. The algorithm is based on very interesting formulations of graph theory problems. Thus, it is efficient in both computational time (instances with thousands of devices are solved in a short time) and solution quality (evaluated over smaller size instances while comparing it with optimal solutions obtained by integer linear programming).

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