Abstract
The massive increase of IoT devices and their collected data raises the question of how to analyze all that data. Edge computing provides a suitable compromise, but the question remains: How much processing should be done locally vs. offloaded to other devices? The diverse application requirements and limited resources at the edge extend the challenges.
We propose Oops, an optimization framework to adapt the resource management at runtime distributedly. It orchestrates the IoT devices and adapts their operation mode with respect to their constraints and the gateway’s limited shared resources. Oops reduces runtime overhead significantly while increasing user utility compared to state-of-the-art.
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Index Terms
Oops: Optimizing Operation-mode Selection for IoT Edge Devices
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