CCR-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.

National Science Foundation (NSF)
Division of Computer and Network Systems (CNS)
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D. Helen Gill
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Georgia Tech Research Corporation
United States
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