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，这些语言暴露了硬件的细节，做出低级优化决策，并构建了大量的网络机器。一种编程方法是非常需要的，这将允许用户指定的整体功能的应用程序在一个高层次上使用一个合适的编程框架。理想情况下，指定的用户程序将被自动转换为优化的分布式代码，运行在各个节点。本项目试图实现上述愿景，通过查看传感器网络作为一个分布式数据库的事实收集的环境。我们认为传感器网络应用程序的协作行为可以很容易地抽象为操纵事实的演绎规则，而非协作行为可以嵌入到内置函数中，该项目的主要目标是开发一个查询引擎，用于传感器网络中演绎查询的有效网络评估。 查询处理计划包括将用户程序翻译成优化的虚拟存储器代码，该代码被下载到传感器节点中用于分布式执行。研究结果将成为网络模拟器的原型（TOSSIM和ns 2）和基于Berkeley motes和Gumstix类板的真实的传感器网络平台。上述研究计划通过捆绑查询引擎中设计选择和优化的所有低级别复杂性，具有极大地简化传感器网络的设计和使用的潜力。将受益于我们贡献的领域的示例包括地面交通，应急响应和救灾行动，物理现象，如天气和风暴跟踪，森林火灾跟踪，动物/鸟类的迁移模式等。该项目网站（http：//www.cs.sunysb.edu/logicSense）将用于传播所有课程材料，出版物和软件，从我们的项目产生。

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.