Efficient Mapping and Management of Applications onto Cyber-Physical Systems
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Abstract:
The computing landscape is a richly-heterogeneous space including both fixed and mobile nodes with a large variety of sensing, actuation and computational capabilities (including mobile devices, home electronics, taxis, robotic drones, etc.). Cyber-physical applications built on these devices have the potential to gather data on, analyze, and adapt to or control a range of environments. The challenge, however, is that Cyber-Physical Systems (CPSs) are difficult to program, and even more difficult to port from one deployment to another, or to dynamically manage as nodes availability changes. Thus, CPS applications are too often programmed in a “brittle” fashion that impedes their ability to efficiently use available compute/sense/actuate resources beyond a one-shot deployment.
In response, this project is improving CPS design and control in four primary thrusts. First, the project is developing abstraction layers to facilitate CPS applications expressing their compute/sense/actuate requirements to lower-level mapping and management layers. Second, the project is exploring methods of providing a Device Attribute Catalog (DAC) that summarizes a region’s available CPS nodes and their capabilities. Third, this research is improving and exploiting the ability to model, predict, and control the mobility of CPS nodes. When some CPS nodes are mobile, the accuracy and performance of a CPS application fundamentally is a function of where nodes will be positioned at any moment in time. This work exploits both static statistical coverage analysis and dynamic prediction and interpolation. Fourth, using CPSISA, DAC, and other resources as input, the team is developing tools to statically or dynamically optimize mappings of CPS applications onto available resources.
Our research has included progress on device mobility/coverage/navigation modeling, on mobile code mapping and offloading, on collaborative sensing, mapping, navigation, communication optimization and test application development. Throughout the research, we have continued to ground our research in real-world applications studies. These include a FireGuide application for emergency response assistance using groups of mobile/robotic nodes for guiding first responders, as well as intelligent transportation systems based on automobile traffic sensing and dynamic toll pricing.
Submitted by Margaret Martonosi
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Abstract:
The computing landscape is a richly-heterogeneous space including both fixed and mobile nodes with a large variety of sensing, actuation and computational capabilities (including mobile devices, home electronics, taxis, robotic drones, etc.). Cyber-physical applications built on these devices have the potential to gather data on, analyze, and adapt to or control a range of environments. The challenge, however, is that Cyber-Physical Systems (CPSs) are difficult to program, and even more difficult to port from one deployment to another, or to dynamically manage as nodes availability changes. Thus, CPS applications are too often programmed in a “brittle” fashion that impedes their ability to efficiently use available compute/sense/actuate resources beyond a one-shot deployment.
In response, this project is improving CPS design and control in four primary thrusts. First, the project is developing abstraction layers to facilitate CPS applications expressing their compute/sense/actuate requirements to lower-level mapping and management layers. Second, the project is exploring methods of providing a Device Attribute Catalog (DAC) that summarizes a region’s available CPS nodes and their capabilities. Third, this research is improving and exploiting the ability to model, predict, and control the mobility of CPS nodes. When some CPS nodes are mobile, the accuracy and performance of a CPS application fundamentally is a function of where nodes will be positioned at any moment in time. This work exploits both static statistical coverage analysis and dynamic prediction and interpolation. Fourth, using CPSISA, DAC, and other resources as input, the team is developing tools to statically or dynamically optimize mappings of CPS applications onto available resources.
Our research has included progress on device mobility/coverage/navigation modeling, on mobile code mapping and offloading, on collaborative sensing, mapping, navigation, communication optimization and test application development. Throughout the research, we have continued to ground our research in real-world applications studies. These include a FireGuide application for emergency response assistance using groups of mobile/robotic nodes for guiding first responders, as well as intelligent transportation systems based on automobile traffic sensing and dynamic toll pricing.