ACODS: Adaptive Computation Offloading for Drone Surveillance System
Sponsor
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF- 2015R1D1A1A01059049).
Published In
16th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net)
Document Type
Citation
Publication Date
6-2017
Abstract
Unmanned Aerial Vehicle (UAV) surveillance systems allow for highly advanced and safe surveillance of hazardous locations. Further, multi-purpose drones can be widely deployed for not only gathering information but also analyzing the situation from sensed data. However, mobile drone systems have limited computing resources and battery power which makes it a challenge to use these systems for long periods of time or in fully autonomous modes. In this paper, we propose an Adaptive Computation Offloading Drone System (ACODS) architecture with reliable communication for increasing drone operating time. We design not only the response time prediction module for mission critical task offloading decision but also task offloading management module via the Multipath TCP (MPTCP). Through performance evaluation via our prototype implementation, we show that the proposed algorithm achieves significant increase in drone operation time and significantly reduces the response time. I
Locate the Document
DOI
10.1109/MedHocNet.2017.8001647
Persistent Identifier
https://archives.pdx.edu/ds/psu/30640
Citation Details
Jung, W. S., Yim, J., Ko, Y. B., & Singh, S. (2017, June). ACODS: Adaptive computation offloading for drone surveillance system. In 2017 16th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net) (pp. 1-6). IEEE.
Description
©2017 IEEE