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TDMA scheduling problem avoiding interference in multi-hop wireless sensor networks

机译:避免在多跳无线传感器网络中产生干扰的TDMA调度问题

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In this paper, we consider a multi-hop sensor network, where the network topology is a tree, TDMA (time division multiple access) is employed as medium access control, and all data generated at sensor nodes are delivered to a sink node (the base station) located on the root of the tree through the network. It is reported that if a transmission schedule that avoids interference between sensor nodes completely can be computed, TDMA is preferable to CSMA/CA (carrier sense multiple access with collision avoidance) in performance. In general, the TDMA scheduling problem to find the shortest schedule is formulated as a combinatorial optimization problem, where each combination corresponds to a schedule. However, solving such a combinatorial optimization problem is difficult, especially for large-scale multi-hop sensor networks. The reason of the difficulty is that the number of the combinations increases exponentially with the increase of the number of nodes. In this paper, to formulate the TDMA scheduling problem, we propose a min-max model and a min-sum model. The min-max model yields the shortest schedule, but it is difficult to solve large-scale problems. The min-sum model does not guarantee providing the shortest schedule; however, it may give us good schedules over a short amount of computation time, compared to the min-max model. Numerical examples show that the min-sum model can provide good schedules in a reasonable CPU time, even when the min-max model fails to compute the shortest schedule in a reasonable CPU time.
机译:在本文中,我们考虑了一种多跳传感器网络,其中网络拓扑是一棵树,采用TDMA(时分多址)作为介质访问控制,并且在传感器节点处生成的所有数据都将传递到宿节点(基站)通过网络位于树的根上。据报道,如果可以计算出完全避免传感器节点之间干扰的传输时间表,则在性能上,TDMA优于CSMA / CA(带有冲突避免的载波侦听多路访问)。通常,将找到最短调度表的TDMA调度问题表述为组合优化问题,其中每个组合都对应一个调度表。然而,解决这样的组合优化问题是困难的,尤其是对于大规模的多跳传感器网络。困难的原因在于,组合的数量随着节点数量的增加而呈指数增加。在本文中,为了提出TDMA调度问题,我们提出了一个最小-最大模型和一个最小和模型。最小-最大模型产生的时间表最短,但是很难解决大规模问题。最小和模型不能保证提供最短的计划;但是,与最小-最大模型相比,它可以在较短的计算时间内为我们提供良好的计划。数值示例表明,即使最小-最大模型无法在合理的CPU时间内计算出最短的调度程序,最小和模型也可以在合理的CPU时间内提供良好的调度程序。

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