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SYNAPSE++: Code Dissemination in Wireless Sensor Networks Using Fountain Codes

机译:SYNAPSE ++:使用源代码的无线传感器网络中的代码分发

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摘要

This paper presents SYNAPSE++, a system for over the air reprogramming of wireless sensor networks (WSNs). In contrast to previous solutions, which implement plain negative acknowledgment-based ARQ strategies, SYNAPSE++ adopts a more sophisticated error recovery approach exploiting rateless fountain codes (FCs). This allows it to scale considerably better in dense networks and to better cope with noisy environments. In order to speed up the decoding process and decrease its computational complexity, we engineered the FC encoding distribution through an original genetic optimization approach. Furthermore, novel channel access and pipelining techniques have been jointly designed so as to fully exploit the benefits of fountain codes, mitigate the hidden terminal problem and reduce the number of collisions. All of this makes it possible for SYNAPSE++ to recover data over multiple hops through overhearing by limiting, as much as possible, the number of explicit retransmissions. We finally created new bootloader and memory management modules so that SYNAPSE++ could disseminate and load program images written using any language. At the end of this paper, the effectiveness of SYNAPSE++ is demonstrated through experimental results over actual multihop deployments, and its performance is compared with that of Deluge, the de facto standard protocol for code dissemination in WSNs. The TinyOS 2 code of SYNAPSE++ is available at http://dgt.dei.unipd.it/download.
机译:本文介绍了SYNAPSE ++,这是一种用于无线传感器网络(WSN)空中重新编程的系统。与以前的解决方案不同,这些解决方案实现了基于纯否定确认的ARQ策略,而SYNAPSE ++采用了利用无速率源代码(FC)的更为复杂的错误恢复方法。这使它可以在密集网络中更好地扩展,并更好地应对嘈杂的环境。为了加快解码过程并降低其计算复杂度,我们通过原始的遗传优化方法设计了FC编码分布。此外,已经共同设计了新颖的信道访问和流水线技术,以充分利用喷泉码的好处,减轻隐藏终端的问题并减少冲突的次数。所有这些,使SYNAPSE ++能够通过监听来尽可能多地限制显式重传的次数,从而通过多跳来恢复数据。我们最终创建了新的引导程序和内存管理模块,以便SYNAPSE ++可以传播和加载使用任何语言编写的程序映像。在本文的最后,通过在实际的多跳部署上的实验结果证明了SYNAPSE ++的有效性,并将其性能与无线传感器网络中事实上的用于代码分发的标准协议Deluge进行了比较。 SYNAPSE ++的TinyOS 2代码可从http://dgt.dei.unipd.it/download获得。

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