ORCHID: Harnessing Digital Evolution to Design High-Assurance Adaptive Systems

提案编号0820220标题：兰花：在设计高保障自适应系统中利用数字演进PI：Betty Cheng、Philip McKinley、Charles OFria和Xiaobo Tana强大的网络基础设施必须能够监控环境及其自身行为，适应不断变化的条件，并保护自己免受组件故障的影响。兰花项目的标志是将基本的生物学原理--进化--引入到自适应真实世界软件系统的开发过程中。该项目将使用和扩展Avida数字进化软件平台，以解决三个主要任务：(1)利用数字进化的软件模型和搜索能力的自动生成，使开发人员能够识别可行的系统配置；(2)生成新的策略，以根据不断变化的环境条件从一个系统行为适应到另一个系统行为；以及(3)通过揭示给定配置中的潜在属性，为自适应系统提供保证，以便区分生成的配置并删除不需要的行为。将开发一个原型系统，并将其用于国土安全和环境监测的自适应水上移动传感器网络设计的实验案例研究。此外，还将开发一个教学系统Avida-EDAS，使学生能够进化自适应软件的模型，进行实验以评估不利环境条件的影响，并观察不同适应策略对系统执行的影响。

Proposal Number 0820220Title: ORCHID: Harnessing Digital Evolution in Design High-Assurance Adaptive SystemsPIs: Betty Cheng, Philip McKinley, Charles Ofria, and Xiaobo TanA robust cyber-infrastructure must be able to monitor the environment and its own behavior, adapt to changing conditions, and protect itself from component failures. The hallmark of the Orchid project is to introduce the fundamental biological principle, evolution, into the development process for adaptive real-world software systems. The project will use and extend the Avida digital evolution software platform to address three primary tasks: (1) exploiting the automatic generation of software models and search capacity of digital evolution to enable the developer to identify viable system configurations; (2) generating novel strategies to adapt from one system behavior to another in response to changing environmental conditions; and (3) providing assurance for adaptive systems by revealing latent properties within a given configuration in order to distinguish generated configurations and remove unwanted behavior. A prototype system will be developed and used to conduct an experimental case study in the design of self-adaptive aquatic mobile sensor networks for homeland security and environmental monitoring. In addition, an instructional system, Avida-EDAS, will be developed to enable students to evolve models of adaptive software, conduct experiments to assess the impact of adverse environmental conditions, and observe the effects of different adaptation strategies on system execution.