InfoFabric: Adaptive Services in Distributed Embedded Systems

这项研究正在开发“InfoFabric”服务，以管理多个共享数据流，并在可动态重新配置的传感器网络中实现高性能的传感和通信。例如，在紧急响应应用中，所采用的计算基础设施是便携式和手持终端用户设备的快速组合。多种通信模式用于跨协作对等体以及与本地和远程指挥中心和/或信息库进行交互。一个关键问题是，此类设备通常无法访问、显示和操作具有最终用户所需质量的信息。一个例子是“实地”的观察者试图将可见云的形成与远程运行天气模拟产生的输出进行匹配，后者使用实时雷达数据。除非手持设备能够高质量和实时地可视化数据，否则无法使用现场观测来改进或指导远程天气预报程序。类似地，搜索和救援行动可以通过团队成员之间丰富的(多媒体)实时通信和从远程服务器获得的地形数据的高保真图形显示来辅助。所产生的复杂、分布式和嵌入式应用程序需要解决的基本技术问题包括(1)在如何、何时何地在底层分布式平台上执行必要的处理和通信动作方面提供高度的灵活性，以及(2)尽管服务位置、平台能力(例如，终端设备上的剩余电源)和用户要求在运行时发生变化，仍然能够持续满足终端用户的需求。`InfoFabric‘方法使用轻量级发布/订阅中间件支持数据密集型嵌入式应用程序。终端用户在需要时动态订阅信息频道，InfoFabric应用用户指定的处理。处理和通信动作被动态映射到底层分布式设备和机器。为了获得高性能并满足诸如POWER等嵌入式系统的需求，新的编译器和运行时二进制代码生成方法在InfoFabric的平台上动态地生成和安装代码。代码专门用于将当前用户需求与可用的平台资源相匹配。为了满足动态需求并处理资源可用性的运行时变化，与中间件相关联的资源管理机制携带处理和通信动作的运行时适配所需的性能、使用和需求信息。由于InfoFabric中间件详细了解在将信息交付给最终用户之前应如何传输和处理信息，因此它可以使用自动冗余和复制、服务(重新)定位和(重新)分区等技术来匹配不断变化的用户需求和平台可用性。

Schwan, KarstenCCR-0208953"InfoFabric: Adaptive Services in Distributed Embedded Systems" This research is developing "Infofabric" services to manage multiple shared data streams and enable high performance sensing and communication in dynamically reconfigurable sensor nets. For example, in emergency response applications, the computing infrastructures employed are rapidly assembled conglomerates of portable and handheld end user devices. Multiple communication modes are used to interact across collaborating peers and also with local and remote command centers and/or information repositories. A key problem is that such devices typically cannot access, display, and manipulate information with the quality needed by end users. An example is an observer `in the field' trying to match visible cloud formations with the outputs produced by remotely running weather simulations, the latter using real-time radar data. Unless the handheld device can visualize data with high quality and in real-time, field observations cannot be used to refine or steer the remote weather prediction programs. Similarly, search and rescue operations can be aided by rich (multi-media), real-time communications between team members and by high fidelity graphical displays of terrain data available from remote servers.The basic technical problems to be solved for the resulting complex, distributed and embedded applications include (1) the provision of high levels of flexibility in how, where, and when necessary processing and communication actions are performed on the underlying distributed platforms, and (2) the ability to continuously meet end user needs despite runtime variations in service locations, platform capabilities (e.g., remaining power on end devices), and user requirements. The `InfoFabric' approach supports data-intensive, embedded applications with lightweight publish/subscribe middleware. An end user dynamically subscribes to information channels when needed, and the InfoFabric applies the processing specified by the user. Processing and communication actions are dynamically mapped to the underlying distributed devices and machines. To attain high performance and meet embedded systems requirements like such as power, new compiler and runtime binary code generation methods dynamically generate and install code on the InfoFabric's platform. Code is specialized to match current user needs to available platform resources. To meet dynamic needs and deal with runtime changes in resource availability, resource management mechanisms associated with middleware carry the performance, usage, and needs information required for runtime adaptation of processing and communication actions. Because the InfoFabric middleware has detailed knowledge of the ways in which information should be transported and manipulated before delivering it to end users, it can employ techniques like automatic redundancy and replication, and service (re)location and (re)partitioning to match changing user needs and platform availabilities.