PusOS: RISC-V Tabanlı Açık Kaynak Hafif Bir Sis Bilişim Sistemi Tasarımı

Abstract

Sis bilişim, veriye yakın düğümlerde işlem yaparak düşük gecikme ve yüksek hizmet kalitesi sunmayı hedefleyen dağıtık bir bilişim modelidir. Bu çalışmada, yalnızca çekirdek modunda çalışan, RISC-V mimarisi üzerinde geliştirilen, nanokernel tabanlı ve açık kaynaklı bir işletim sistemi sunulmaktadır. Sistem, kaynak kısıtlı cihazlarda düşük gecikme, yüksek güvenilirlik ve küçük sistem ayak iziyle çalışacak şekilde tasarlanmıştır. Nanokernel mimarisi sayesinde bağlam değiştirme ve sistem çağrısı yükleri ortadan kaldırılarak uygulamalar doğrudan çekirdek alanında çalıştırılarak verimlilik artırılmıştır. Ağ, depolama, hesaplama, sanallaştırma ve yönetim işlevleri entegre edilerek QEMU sanal makine öykünücüsünde test edilmiştir. Linux ile yapılan karşılaştırmalı deneylerde, önerdiğimiz sisteminin veri toplama, depolama ve çoklu görevde 4–5,5 kat daha hızlı olduğu gösterilmiştir. Böylece sis bilişim alanı için güvenilir, genişletilebilir ve hafif bir alternatif işletim sistemi sunulmaktadır.

Keywords

• Sis bilişim
• İşletim sistemleri
• Uç bilişim
• Sanallaştırma
• RISC-V

PusOS: Building an Open Source Lightweight Fog Computing System on RISC-V

Abstract

Fog computing is a distributed computing model that aims to provide low latency and high quality of service by processing data near the source nodes. In this context, we present a nanokernel-based, open-source fog computing operating system developed on the RISC-V architecture that runs solely in kernel mode. The system is designed to operate with low latency, high reliability and a minimal footprint on resource-constrained devices. By using the nanokernel architecture, context switching and system call overheads are eliminated and applications run directly in kernel space to enhance efficiency. Integrated functionalities for networking, storage, computation, virtualization, and management have been tested extensively using the QEMU emulator. Comparative experiments with Linux demonstrate that the system performs 4 to 5.5 times faster in serial data collection, storage, and multitasking thereby providing a reliable, extensible and lightweight alternative OS for fog computing domain.

Keywords

• Fog computing
• Operating systems
• Edge computing
• Virtualization
• RISC-V

References

1. Phaphoom, N., Oza, N., Wang, X., Abrahamsson, P. Does cloud computing deliver the promised benefits for IT industry?, Association for Computing Machinery, New York, NY, USA, 2012, pp. 45–52.
2. Yang, S. IoT Stream Processing and Analytics in the Fog, IEEE Communications Magazine, 2017, pp. 21–27.
3. Misirli, J., Casalicchio, E. An Analysis of Methods and Metrics for Task Scheduling in Fog Computing, Future Internet, 2023, volume 16.
4. Bonomi, F., Milito, R., Zhu, J., Addepalli, S. Fog computing and its role in the internet of things, Association for Computing Machinery, New York, NY, USA, 2012, pp. 13–16.
5. Yousefpour, A., Fung, C., Nguyen, T., Kadiyala, K., Jalali, F., Niakanlahiji, A., Kong, J., Jue, J. P. All one needs to know about fog computing and related edge computing paradigms: A complete survey, Journal of Systems Architecture, 2019, pp. 289–330.
6. Al-Dulaimy, A., Jansen, M., Johansson, B., Trivedi, A., Iosup, A., v.d. The computing continuum: From IoT to the cloud, Internet of Things, 2024, volume: 27.
7. Forti, S., Pagiaro, A., Brogi, A. Simulating FogDirector Application Management, Simulation Modelling Practice and Theory, 2020.
8. Pop, P., Zarrin, B., Barzegaran, M., Schulte, S., Punnekkat, S., Ruh, J., Steiner, W. The FORA Fog Computing Platform for Industrial IoT, Information Systems, 2021.

9. Cheng, B., Fuerst, J., Solmaz, G., Sanada, T. Fog Function: Serverless Fog Computing for Data Intensive IoT Services, IEEE International Conference on Services Computing (SCC), 2019, pp. 28–35.
10. Coutinho, A., Greve, F., Prazeres, C., Cardoso, J. Fogbed: A Rapid-Prototyping Emulation Environment for Fog Computing, IEEE International Conference on Communications (ICC), 2018, pp. 1–7.
11. Gupta, H., Dastjerdi, A. V., Ghosh, S. K., Buyya, R. iFogSim: A toolkit for modeling and simulation of resource management techniques in the Internet of Things, Edge and Fog computing environments, Software: Practice and Experience, 2017, pp. 1275–1296.
12. https://github.com/milisarge/pusos (24.11.2025 tarihinde erişildi.)
13. Naveed, G., Sajak, A.B., Rehan, Q., Megat, Z. A Review of Fog Computing Concept, Architecture, Application, Parameters and Challenges, JOIV: International Journal on Informatics Visualization, 2024, pp. 564-575.
14. Will, N.C., Maziero C.A. Intel Software Guard Extensions Applications: A Survey, ACM, 2023, volume 55-14.
15. Bajer, M. Securing and Hardening Embedded Linux Devices - case study based on NXP i.MX6 Platform, International Conference on Future Internet of Things and Cloud (FiCloud), 2022, pp. 181–189.
16. do Rosario, V. M., Pisani, F., Gomes, A. R., Borin, E. Fog-Assisted Translation: Towards Efficient Software Emulation on Heterogeneous IoT Devices, IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2018, pp. 1268–1277.
17. Waterman, A., Lee, Y., Patterson, D. A., Asanović, K. The RISC-V Instruction Set Manual, Volume I: User-Level ISA, Version 2.0, University of California, Berkeley, 2014.
18. Ince, M.N., Günay, M., Ledet, J. Lightweight distributed computing framework for orchestrating high performance computing and big data, Turkish Journal of Electrical Engineering and Computer Sciences, 2022, pp. 1571–1585.
19. Choi, N., Kim, D., Lee, S. J., Yi, Y. A Fog Operating System for User-Oriented IoT Services: Challenges and Research Directions, IEEE Communications Magazine, 2017, pp. 44–51.
20. Benomar, Z., Longo, F., Merlino, G., Puliafito, A. Enabling Container-Based Fog Computing with OpenStack, International Conference on Internet of Things (iThings), 2019, pp. 1049–1056.
21. Barzegaran, M., Cervin, A., Pop, P. Performance Optimization of Control Applications on Fog Computing Platforms Using Scheduling and Isolation, IEEE Access, 2020, pp. 104085–104098.
22. https://github.com/littlekernel/lk (24.11.2025 tarihinde erişildi.)
23. Popić, S., Pezer, D., Mrazovac, B., Teslić, N. Performance evaluation of using Protocol Buffers in the Internet of Things communication, International Conference on Smart Systems and Technologies (SST), 2016, pp. 261-265.
24. https://github.com/littlefs-project/littlefs (24.11.2025 tarihinde erişildi.)
25. Scholz, D., Raumer, D., Emmerich, P., Kurtz, A., Lesiak, K., Carle, G. Performance Implications of Packet Filtering with Linux eBPF, International Teletraffic Congress (ITC 30), 2018, pp. 209–217.
26. Li, J., Jin, J., Yuan, D., Zhang, H. Virtual Fog: A Virtualization Enabled Fog Computing Framework for Internet of Things, IEEE Internet of Things Journal, 2018, 5 (1), pp. 121-131.
27. Tseng, F.H., Tsai, M.S., Tseng, C.W., Yang, Y.T., Liu, C.C., Chou, L.D. A Lightweight Autoscaling Mechanism for Fog Computing in Industrial Applications, IEEE Transactions on Industrial Informatics, 2018, 14 (10), pp. 4529-4537.
28. https://libvirt.org (24.11.2025 tarihinde erişildi.)
29. https://qemu-project.gitlab.io/qemu/interop/qemu-qmp-ref.html (24.11.2025 tarihinde erişildi.)
30. Costa, B., Bachiega, J., Carvalho, L.R., Rosa, M., Araujo, A. Monitoring fog computing: A review, taxonomy and open challenges, Computer Networks, 2022, 215, pp. 109189.
31. https://www.qemu.org (24.11.2025 tarihinde erişildi.)
32. https://mls.akdeniz.edu.tr (24.11.2025 tarihinde erişildi.)
33. https://github.com/littlefs-project/littlefs/issues/226 (24.11.2025 tarihinde erişildi.)
34. https://trustedfirmware-a.readthedocs.io/en/v2.2/ components/spd/tlk-dispatcher.html (24.11.2025 tarihinde erişildi.)
35. Cecílio, J., de Sá, A. O., Jäger, G., Souto, A., Casimiro, A. LWSEE: Lightweight Secured Software-Based Execution Environment, Internet of Things, 2025, 30, 101513.
36. https://tez.yok.gov.tr/UlusalTezMerkezi/TezGoster?key=1pwTzRXnomYf6jwqVORfUTSyXNY_ytTIs3MjWHLb6-Cn1cdjqUzXhO-nLQ-QoV0E (24.11.2025 tarihinde erişildi.)