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Deductive Framework for Programming Sensor Networks

机译:传感器网络编程的演绎框架

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Developing powerful paradigms for programming sensor networks is critical to realize the full potential of sensor networks as collaborative data processing engines. %In this article, we motivate and develop a deductive framework for programming sensor networks, extending the prior vision of viewing sensor network as a distributed database. The deductive programming approach is declarative, very expressive, and amenable to automatic optimizations. Such a framework allows users to program sensor network applications at a high-level without worrying about the low-level tedious details. %Our system translates a given deductive program to efficient distributed code that runs on individual nodes. To facilitate the above translation, we develop techniques for {em distributed and asynchronous} evaluation of deductive programs in sensor networks. Our techniques generalize to recursive programs without negations, arbitrary non-recursive programs with negations, and in general to arbitrary "locally non-recursive'''' programs with function symbols. %We present performance results on TOSSIM, a network simulator, and a small network testbed.
机译:开发用于编程传感器网络的强大范式对于实现传感器网络作为协作数据处理引擎的全部潜力至关重要。 %在本文中,我们激励并开发了用于编程传感器网络的演绎框架,扩展了将传感器网络视为分布式数据库的先前视野。 Deptuctive编程方法是声明性,非常表现力的,可用于自动优化。这样的框架允许用户以高级程序编程传感器网络应用,而不担心低级繁琐的细节。 %我们的系统将给定的演绎程序转换为在各个节点上运行的有效分布式代码。为了促进以上翻译,我们开发了传感器网络中的{EM分布式和异步}评估的技术。我们的技术概括了没有否定的递归程序,否定的任意非递归程序,通常是违反“本地非递归”的“函数符号的程序”。%我们在Tossim,网络模拟器和a上呈现绩效结果。小型网络测试。

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