Sensomax:一个基于代理的中间件,用于无线传感器网络中的分散动态数据收集

M. Haghighi, D. Cliff
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引用次数: 28

摘要

在本文中,我们描述了Sensomax的设计和实现,Sensomax是一种新颖的基于代理的无线传感器网络中间件(wsn),它是用Java编写的,运行在各种支持Java的嵌入式系统的网络上,从资源受限的Sun Spot节点到资源丰富的树莓派板。对于开发人员来说,编程wsn往往是一项复杂的任务,因为它需要对底层硬件资源及其固件或操作系统有详细的了解。尽管到目前为止已经提出了许多解决方案,但其中只有少数能够满足具有挑战性的需求,例如服务多用户应用程序和在运行时使用流行的高级语言(如Java)重新编程网络。Sensomax提供了现有解决方案中几种最佳实践的新颖组合,促进了完全分布式和分散的批量编程和/或传感器节点的更新;服务由单个或多个用户部署的多个同时应用程序;允许应用程序需求的动态运行时更改;并在时间驱动、数据驱动和事件驱动的操作范式之间提供实时切换。Sensomax提供了一套复杂的api、一个功能丰富的桌面应用程序、一个基于云的分布式网络的web应用程序和一个模拟器。我们演示了Sensomax在一个由12个太阳黑点组成的真实网络上的运行情况,该网络作为环境监测系统部署,600个虚拟太阳黑点节点连续运行数周,使用一种新颖的统计严格的自适应变化点检测算法来识别监测数据流中的重大“异常”变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensomax: An agent-based middleware for decentralized dynamic data-gathering in wireless sensor networks
In this paper we describe the design and implementation of Sensomax, a novel agent-based middleware for wireless sensor networks (WSNs), which is written in Java and runs on networks of various Java-enabled embedded systems ranging from resource-constrained Sun Spot nodes to resource-rich Raspberry Pi boards. Programming WSNs tends to be a complex task for developers, as it requires detailed knowledge of underlying hardware resources as well as their firmware or operating systems. Although many solutions have been proposed up to this date, only a few of those are capable of satisfying challenging demands such as serving multiple user applications and reprogramming the network at run-time in popular highlevel languages such as Java. Sensomax presents a novel combination of several best practices from existing solutions, facilitating fully distributed and decentralized bulk programming and/or updating of sensor nodes; serving multiple simultaneous applications deployed by single or multiple users; allowing dynamic run-time changes in the application requirements; and offering on-the-fly switching between time-driven, data-driven, and event-driven operational paradigms. Sensomax provides a sophisticated set of APIs, a feature-rich desktop application, a web application for cloud-based distributed networks, and a simulator. We demonstrate Sensomax in operation on a real network of 12 Sun Spots deployed as an environment-monitoring system, and 600 virtual Sun Spot nodes running continuously over periods of several weeks, using a novel statistically rigorous adaptive change-point detection algorithm to identify significant “anomalous” changes in the monitored data-streams.
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