Due to limited energy supply on many Internet of Things (IoT) devices, asynchronous duty cycle radio management is widely adopted to save energy. Flooding is a critical way to disseminate messages through the whole network. Capture effect enabled concurrent broadcast is appealing to accelerate network flooding in asynchronous duty cycle networks. However, when the flooding payload’s size is large, the concurrent broadcast performance is far from efficient due to the frequently unsatisfied capture effect. Intuitively, senders can send a short packet containing partial flooding payload to keep concurrent broadcast efficiency. In practice, we still face two challenges. Considering packet loss, a receiver needs an effective way to recover the entire flooding payload from several received packets as soon as possible. Moreover, considering different channel states of different senders, how a sender chooses the optimal packet length to guarantee high channel utilization is not easy. In this paper, we propose Chase ++ a Fountain-code based concurrent broadcast control layer to enable fast flooding in asynchronous duty cycle networks. Chase ++ uses Fountain code to alleviate the negative influence of a certain part of the flooding payload’s continuous loss. Moreover, Chase ++ adaptively selects packet length with the local estimation of channel utilization. Specifically, Chase ++ partitions long payload into several short payload blocks, further encoded into many encoded payload blocks by Fountain-code. Then, with temporal and spatial features of the sampled RSS (received signal strength) sequence, a sender estimates the number of concurrent senders. Finally, according to the estimated number of concurrent senders, the sender determines the optimal number of encoded payload blocks in a packet and assembles the encoded payload blocks as lots of packets. Then, the concurrent broadcast layer continuously transmits these packets. Receivers can recover the original flooding payload after several independent encoded payload blocks are collected. We implement Chase ++ in TinyOS with TelosB nodes. We further evaluate Chase ++ on Local testbed with 50 nodes and Indriya testbed with 95 nodes. The improvement of network flooding speed can reach 23.6% and 13.4%, respectively.

中文翻译：

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Chase ++：异步占空比网络中启用喷泉的快速泛洪

由于许多物联网（IoT）设备上的能源供应有限，异步工作周期无线电管理被广泛采用以节省能源。泛洪是在整个网络中传播消息的一种重要方法。启用捕获效果的并发广播吸引了异步占空比网络中的网络泛滥。但是，当泛洪有效载荷的大小很大时，由于捕获效果经常不令人满意，因此并发广播性能远没有达到有效。直观上讲，发送方可以发送包含部分泛洪有效载荷的短数据包，以保持并发广播效率。在实践中，我们仍然面临两个挑战。考虑到数据包丢失，接收机需要一种有效的方法，以尽快从几个接收到的数据包中恢复整个泛洪有效载荷。而且，考虑到不同发送方的不同信道状态，发送方如何选择最佳数据包长度以确保较高的信道利用率并不容易。在本文中，我们提出追赶 ++基于喷泉码的并发广播控制层，以实现异步占空比网络中的快速泛洪。 追赶 ++使用Fountain代码减轻了洪水有效载荷连续损失的某些部分的负面影响。而且，追赶 ++通过本地估计信道利用率来自适应地选择包长度。具体来说，追赶 ++将长的有效载荷划分为几个短的有效载荷块，并通过源代码将其进一步编码成许多编码的有效载荷块。然后，利用采样的RSS（接收信号强度）序列的时间和空间特征，发送方可以估计并发发送方的数量。最后，根据并发发送方的估计数量，发送方确定一个数据包中已编码有效负载块的最佳数量，并将已编码有效负载块组装为大量数据包。然后，并发广播层连续发送这些分组。在收集了几个独立的编码有效载荷块之后，接收器可以恢复原始的洪泛有效载荷。我们实施追赶 在TinyOS中，带有TelosB节点的++。我们进一步评估追赶 在具有50个节点的本地测试平台和具有95个节点的Indriya测试平台上使用++。网络泛洪速度的提高可以分别达到23.6％和13.4％。