Traditional cloud-centric approaches are facing increasing demands for instant data processing and significant challenges in meeting the latency requirements of modern applications. Edge computing emerges as a promising approach that brings computation and data storage closer to the edge of the network, enabling real-time decision-making with reduced latency and enhanced efficiency.

The paper provides a comprehensive overview of edge computing, describing its fundamental principles, architectural components, and key advantages over centralized cloud infrastructures. By minimizing data transfer latency, edge computing ensures that critical data analysis and processing occur close to data sources, resulting in enhanced responsiveness and improved user experiences.

The paper analyzes two case studies, including autonomous driving vehicles and finance, in order to highlight the applications of edge computing in areas where real-time decision-making is crucial.

In addition to discussing the benefits of edge computing, the paper addresses the potential challenges and constraints associated with  edge computing implementation. Security and privacy concerns in decentralized edge environments are explored, and several protection strategies are described.

Finally, the paper outlines the future of edge computing for organizations and the technology industry. In doing so, the paper discusses the potential of edge computing in supporting emerging technologies, such as 5G networks and autonomous systems.

edge computing, latency, cloud, centralized cloud infrastructure.

Received: December 19, 2023; Accepted: February 2, 2024; Published: February 19, 2024

How to cite this article: Ion-Alexandru Secara, Real-time decision-making with edge computing, Far East Journal of Electronics and Communications 28 (2024), 1-19. http://dx.doi.org/10.17654/0973700624001

This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License

References:
[1] Lanner Electronics, Edge AI Computing for Autonomous Driving System, Lanner Electronics, 2022. [Online]. Available: https://lannerinc.com/applications/ transportation/edge-ai-computing-for-autonomousdriving-system.
[2] GridGain, Driving High-frequency Trading and Compliance with In-memory Computing, 2019. [Online]. Available:
https://23545599.fs1.hubspotusercontentna1.net/hubfs/23545599/Downloadable%20Assets/Whitepapers/High_Frequency_Trading_vF.pdf. [Accessed 2023].
[3] KWA Analytics, Strategies for effective real-time data capture and robust risk management, KWA Analytics, 2023. [Online]. Available: https://www.risk.net/ insight/markets/7958544/strategies-for-effective-real-time-data-capture-and-robust-risk-management.
[4] T. Pryor, Financial services organizations and edge computing, RSM, 2022. [Online]. Available: https://rsmus.com/insights/industries/financial-services/ financial-services-organizations-and-edge-computing.html.
[5] T. Nolle, Edge computing security risks and how to overcome them, TechTarget Network, 2021. [Online]. Available: https://www.techtarget.com/iotagenda/tip/ Edge-computing-security-risks-and-how-to-overcome-them.
[6] S. Rauch, Edge computing security risk and challenges in 2023, simplilearn, 2022. [Online]. Available: https://www.simplilearn.com/edge-computing-security-risk-and-challenges-article.
[7] P. Swabey and C. Glover, The security challenges of edge computing, Tech Monitor, 2022. [Online]. Available:
https://techmonitor.ai/focus/security-challenges-of-edge-computing.
[8] Level Connectivity, AMPCUS, 2023.
[Online]. Available: https://blogs.ampcus.com/unlocking-power-edge-computing-integrating-5g-networks-next-level-connectivity/.
[9] Arrow, Sensors and edge AI: how they work together to provide autonomous driving, Arrow, 2022. [Online]. Available: https://www.arrow.com/en/research- and-events/articles/sensors-and-edge-ai-how-they-work-together-to-provide-autonomous-driving.
[10] B. J. Dooley, Ubiquitous smart devices and the coming age of edge computing, UPSIDE, 2020. [Online]. Available: https://tdwi.org/articles/2020/04/27/arch-all-smart-devices-and-coming-of-edge-computing.aspx.
[11] Frost and Sullivan, Challenges of Adopting Edge Computing, 2020. [Online]. Available: https://www.frost.com/frost-perspectives/challenges-of-adopting-edge-computing/.
[12] J. Pérez, J. Diaz, J. Berrocal, R. Lopez-Viana and A. Gonzalez-Prieto, Edge computing, Computing 104 (2022), 2711-2747.
[13] K. Casey, How edge servers work, The Enterprisers Projects, 2021. [Online]. Available: https://enterprisersproject.com/article/2021/2/how-edge-servers-work.
[14] M. Crosling, The rise of edge computing: understanding its benefits and drawbacks, 2023. [Online]. Available: https://xailient.com/blog/the-rise-of-edge- computing-understanding-its-benefits-and-drawbacks/.
[15] B. Unhelkar, Handbook of research in mobile business, Technical, Methodological and Social Perspectives, 2nd ed., Information Science Reference, University of Western Sydney, Australia, 2009.
[16] M. Good, Real-time decision-making with edge to cloud, Leidos, 2020. [Online]. Available:
https://www.leidos.com/insights/real-time-decision-making-edge-cloud.