دانلود مقاله ISI انگلیسی شماره 67566
ترجمه فارسی عنوان مقاله

برآورد سیگنال گره خاص تطبیقی توزیع شده در شبکه های حسگر بی سیم مخلوط توپولوژی و ناهمگن ☆

عنوان انگلیسی
Distributed adaptive node-specific signal estimation in heterogeneous and mixed-topology wireless sensor networks ☆
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
67566 2015 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Signal Processing, Volume 117, December 2015, Pages 44–60

ترجمه کلمات کلیدی
شبکه های حسگر بی سیم؛ برآورد سیگنال توزیع شده؛ شبکه های حسگر بی سیم ناهمگن ؛ شبکه های حسگر بی سیم مختلط توپولوژی
کلمات کلیدی انگلیسی
Wireless sensor networks; Distributed signal estimation; Heterogeneous wireless sensor networks; Mixed-topology wireless sensor networks
پیش نمایش مقاله
پیش نمایش مقاله  برآورد سیگنال گره خاص تطبیقی توزیع شده در شبکه های حسگر بی سیم مخلوط توپولوژی و ناهمگن ☆

چکیده انگلیسی

A wireless sensor network (WSN) is considered where each node estimates a number of node-specific desired signals by means of the distributed adaptive node-specific signal estimation (DANSE) algorithm. It is assumed that the topology of the WSN is constructed based on one of the two approaches, either a top-down approach where the WSN is composed of heterogeneous nodes, or a bottom-up approach where the nodes are not necessarily heterogeneous. In the top-down approach, nodes with the largest energy budgets are designated as cluster heads and the remaining nodes form clusters around these nodes. In the bottom–up approach, an ad hoc WSN is partitioned into a set of smaller substructures consisting of non-overlapping cliques that are arranged in a tree topology. These two approaches are shown to be conceptually equivalent, in that the same building blocks constitute both envisaged topologies, and the functionality of the DANSE algorithm is extended to such topologies. In using the DANSE algorithm in such topologies, the WSN converges to the same solution as if all nodes had access to all of the sensor signal observations, and provides faster convergence when compared to DANSE in a single tree topology with only a slight increase in per-node energy usage.