III-COR: Deductive Framework for Programming Sensor Networks

对传感器网络进行编程是相当困难的，因为它迫使程序员使用低级语言进行编程，从而暴露硬件的细节，做出低级优化决策，并构建大量的网络机器。我们迫切需要一种编程方法，允许用户使用合适的编程框架在高层指定应用程序的总体功能。理想情况下，指定的用户程序将自动转换为在单个节点上运行的优化的分布式代码。本项目试图通过将传感器网络视为从环境中收集的事实的分布式数据库来实现上述愿景。其信念是，传感器网络应用的协作行为可以很容易地用演绎规则抽象出来，而非协作行为可以嵌入到内置功能中。该项目的主要目标是开发一个查询引擎，用于在传感器网络中对演绎查询进行有效的网络评估。所述查询处理计划包括将所述用户程序转换为优化的虚拟内存代码，所述虚拟内存代码下载到所述传感器节点中进行分布式执行。研究结果将在网络模拟器（TOSSIM和ns2）和基于Berkeley motes和gumstix样板的真实传感器网络平台中进行原型制作。上述研究计划有可能极大地简化传感器网络的设计和使用，它将查询引擎中设计选择和优化的所有低级复杂性捆绑在一起。从我们的贡献中受益的领域包括地面交通、紧急反应和救灾行动、天气和风暴追踪等物理现象、森林火灾追踪、动物/鸟类迁徙模式等。项目网站（http://www.cs.sunysb.edu/~hgupta/logicSense）will)用于传播所有课程材料、出版物和我们项目产生的软件。

Programming a sensor network is quite hard, since it forces the programmerto program in low-level languages that exposes details of the hardware, make low-level optimization decisions, and build a great deal of networkmachinery. A programming methodology is sorely needed that will allowa user to specify the overall functionality of the application at a high-level using a suitable programming framework.Ideally, the specified user program would be automatically translated to optimized distributed code that runs on individual nodes.This project attempts to realize the above vision by viewing the sensornetwork as a distributed database of facts gathered from the environment. The belief is that the collaborative behavior of a sensor networkapplication can be easily abstracted in terms of deductive rulesthat manipulate the facts, while the non-collaborative behavior can be embedded in built-in functions.The main goal of the project is to develop a query engine for efficient in-network evaluation of deductive queries in sensor networks. The query processing plan includes translation of the user program into optimized virtual memory code, which is downloaded into the sensor nodes for distributed execution. The research results would be prototypedin networking simulators (TOSSIM and ns2) and in real sensor network platforms based on Berkeley motes and Gumstix-like boards.The above research plan has the potential of greatly simplifying the design and use of sensor networks, by bundling all the low-level complexities of design choices and optimizations in the query engine.Examples of domains that will benefit from our contributions include ground traffic, emergency response and disaster relief operations,physical phenomenon such as weather and storm tracking, forest fire tracking, migration patterns of animals/birds, etc.The project web site (http://www.cs.sunysb.edu/~hgupta/logicSense)will be used for dissemination of all course materials, publications, and software that result from our project.