无线传感器网络中基于最小延时的数据汇集树构建与传输调度算法

无线传感器网络的数据通信模式问题是目前的研究热点，针对现有的无线传感器网络数据汇集算法延时较大这一不足，对最小延时数据汇集树和传输调度问题进行了研究。提出一种基于度约束的汇集树构建算法(DCAT)。该算法按照 BFS 方式遍历图，当遍历到每个节点时，通过确定哪些节点与汇点更近来确定潜在母节点集合。然后，选择图中度数最小的潜在母节点作为当前被遍历节点的母节点。此外，为了在给定的汇集树上进行高效地数据汇集，还提出两种新的基于贪婪的TDMA传输调度算法：WIRES-G 和 DCAT-Greedy。利用随机生成的不同规模的传感器网络，参照当前最新算法，对文中方法的性能进行了全面评估。结果表明，与当前最优算法相比，文中调度算法与文中汇集树构建算法结合起来，可显著降低数据汇集的延时。

Data Aggregation Tree Construction and Transmission Scheduling Algorithm Based onMinimum Latency in Wireless Sensor Networks

Aiming at the shortcomings of the larger delay at the existing data aggregation algorithms in wireless sensor networks, we study the problem of the minimum latency data aggregation tree and transmission scheduling, and an aggregation tree construction algorithm based on degree constraint is proposed(DCAT). It works by traversing the graph in a BFS manner. As it traverses each node, the set of potential parents is determined by identifying the nodes that are one-hop closer to the sink. The potential parent with the lowest degree in the graph is selected as the parent for the currently traversed node. Furthermore, we propose two new approaches based on greedy for building a TDMA transmission schedule to perform efficient aggregation on a given tree: WIRES-G and DCAT-Greedy. We evaluate the performance of our algorithms through extensive simulations on randomly generated sensor networks of different sizes and we compare them to the previous state of the art. Our results show that both our new scheduling algorithms when combined with our new tree-building algorithm obtain significantly lower latencies than that of the previous best algorithm.