Unmanned aerial vehicles (UAVs) are utilized in the surveillance and reconnaissance system of hazardous locations by utilizing the feature that they can freely move away from space constraints. Furthermore, the application scope of the UAVs expanded not only for simple image data collection but also for analysis of complex image data without human intervention. However, mobile UAV systems, such as drone, have limited computing resources and battery power which makes it a challenge to use these systems for long periods of time. In this paper, we propose an AOM, Adaptive Offloading with MPTCP (Multipath TCP), architecture for increasing drone operating time. We design not only the task offloading management module via the MPTCP to utilize heterogeneous network but also the response time prediction module for mission critical task offloading decision. Through the prototype drone implementation, we show the AOM reduces the task response time and increases drone operation time.
KSP Keywords
Application scope, Battery power, Complex image, Computing resources, Critical task, Data Collection, Hazardous locations, Image data, Mission-critical, Operating time, Space constraints
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