Abstract
In this paper we propose a development technique for low-power devices with limited computing capacity to obtain efficient, high-performance and non-CPU-invasive Augmented Reality (AR) applications. The paper will discuss how to exploit both the available hardware and software resources. Many boards on the market are equipped with CPUs with low computing power together with GPUs for 2D/3D graphics and multimedia. The paper analyses the strengths of these architectures and how to exploit them. The Operating System (O.S.) also provides features that allow greater control over the system (e.g., avoid wasting resources) and its performance. The techniques proposed are then used, as an example, in the development of an AR application for remote assistance.
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Elliott, G.A., Anderson, J.H.: Real-world constraints of GPUs in real-time Systems. In: 2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications, pp. 48–54 (2011). https://doi.org/10.1109/RTCSA.2011.46
Schneider, M. Rambach, J., Stricker, D.: Augmented reality based on edge computing using the example of remote live support. In: 2017 IEEE International Conference on Industrial Technology (ICIT), pp. 1277-1282 (2017). https://doi.org/10.1109/ICIT.2017.7915547
López, H., Navarro, A., Relaño, J.: An analysis of augmented reality systems. In: 2010 Fifth International Multi-conference on Computing in the Global Information Technology, pp. 245-250 (2010). https://doi.org/10.1109/ICCGI.2010.24.
Elteir, M.K., Lazem, S., Azab, M.: Unleashing the hidden powers of low-cost IoT boards: GPU-based edutainment case study. J. King Saud Univ. Comput. Inf. Sci. 1319–1578 (2020)
Campeanu, G., Carlson, J., Sentilles, S.: Developing CPU-GPU embedded systems using platform-agnostic components. In: 2017 43rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA), pp. 176–180 (2017). https://doi.org/10.1109/SEAA.2017.20.
Hou, X., Lu, Y., Dey, S.:Wireless VR/AR with Edge/Cloud Computing. In: 2017 26th International Conference on Computer Communication and Networks (ICCCN) , pp. 1–8 (2017). https://doi.org/10.1109/ICCCN.2017.8038375
Maheshwari, S., Raychaudhuri, D., Seskar, I., Bronzino, F.: Scalability and performance evaluation of edge cloud systems for latency constrained applications. IEEE/ACM Symp. Edge Comput. (SEC) 2018, 286–299 (2018). https://doi.org/10.1109/SEC.2018.00028
Zhang, W., Han, B., Hui, P.: On the networking challenges of mobile augmented reality. In: Proceedings of the Workshop on Virtual Reality and Augmented Reality Network (VR/AR Network 2017), pp. 24–29. Association for Computing Machinery, New York (2017).https://doi.org/10.1145/3097895.3097900
Reghenzani, F., Massari, G., Fornaciari, W.: The real-time linux kernel: a survey on PREEMPT_RT. ACM Comput. Surv. 52(1), 1–36 (2019). https://doi.org/10.1145/3297714
Scordino, C., Lipari, G.: Linux and real-time: current approaches and future opportunities (2006)
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Longobardi, A., Tecchia, F., Carrozzino, M., Bergamasco, M. (2021). Efficient Augmented Reality on Low-Power Embedded Systems. In: De Paolis, L.T., Arpaia, P., Bourdot, P. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2021. Lecture Notes in Computer Science(), vol 12980. Springer, Cham. https://doi.org/10.1007/978-3-030-87595-4_17
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DOI: https://doi.org/10.1007/978-3-030-87595-4_17
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