Cluster Computing, Journal Year: 2024, Volume and Issue: 28(1)
Published: Oct. 24, 2024
Language: Английский
International Journal of Advanced Research in Science Communication and Technology, Journal Year: 2025, Volume and Issue: unknown, P. 620 - 630
Published: April 4, 2025
Serverless mobile cloud applications, while highly scalable and cost-efficient, face critical challenges in terms of security vulnerabilities inefficient resource management. These are amplified by the dynamic nature environments reliance on third-party infrastructure. This research specifically addresses problem securing data transmission, managing authentication optimizing allocation computing resources serverless architectures. To resolve these issues, paper proposes a novel, integrated framework that leverages machine learning to predict application demands proactively scale functions. The approach includes implementation multi-factor authentication, role-based access control, encryption protocols enhance confidentiality system integrity. demonstrates significant improvements performance, reduced infrastructure costs, better cache management, notable reduction latency miss rates. proposed model enhances applications' reliability, scalability, cost-effectiveness combining adaptive mechanisms with intelligent provisioning
Language: Английский
Citations
0
Computers & Electrical Engineering, Journal Year: 2025, Volume and Issue: 124, P. 110372 - 110372
Published: May 1, 2025
Language: Английский
Citations
0
Published: March 15, 2024
Industry 4.0, also called the 4th Commercial Revolution, is characterized by mixing advanced digital technologies into production and automation strategies. As part of this revolution, development mobility has grown to be an important aspect in accomplishing clever sustainable increases business sectors. The use net factors (IoT) primarily based sensor networks been tested a key solution driving development. Automation refers capacity machines gadgets move operate autonomously manufacturing technique. Through made extra wireless powerful leveraging IoT-based networks. These allow real-time information collection, analysis, communiqué among machines, allowing them make smart decisions adapt converting environments.
Language: Английский
Citations
1
Future Generation Computer Systems, Journal Year: 2024, Volume and Issue: unknown, P. 107573 - 107573
Published: Oct. 1, 2024
Language: Английский
Citations
1
Mathematics, Journal Year: 2024, Volume and Issue: 13(1), P. 29 - 29
Published: Dec. 26, 2024
The industrial sector has undergone significant digital transformation, driven by advancements in technology and the Internet of Things (IoT). These developments have facilitated collection vast quantities data, which, turn, pose challenges for real-time data processing. This study seeks to validate efficacy accuracy edge computing models designed represent subprocesses within environments compare their performance with that traditional cloud models. By processing locally at point collection, provide substantial benefits minimizing latency enhancing efficiency, which are crucial decision-making operations. research demonstrates derived from distinct yield superior compared comprehensive encompassing multiple subprocesses. findings indicate an increase volume does not necessarily translate improved model performance, particularly datasets capture production processes, as combining independent process can introduce extraneous ‘noise’. subdividing into smaller, specialized models, this offers a viable approach mitigating inherent computing, thereby capabilities, scalability, adaptability modern applications.
Language: Английский
Citations
1
Internet of Things, Journal Year: 2024, Volume and Issue: 26, P. 101224 - 101224
Published: May 16, 2024
Fog computing extends Cloud-like infrastructure to the Edge, advancing Industrial Internet-of-Things (IIoT) applications in which parts of business-oriented enterprise systems, decoupled via fine-grained microservices, can be deployed networks proximity sensor devices. It boosts responsiveness IIoT events significantly where timely decision-making and actions are required, particularly for problematic trends anomalies. However, microservice placement is a non-trivial problem settings, given dynamic occurrence different variable resource needs microservices against resource-constrained, heterogeneous, distributed The cost matching deploying real-time, highly dynamic, contentious settings easily exceed benefit just-in-time Edge deployments. Current studies largely focus on managing from Cloud servers offloading when devices resource-deficient. Yet, there lack research focusing efficient use at edge improve responsiveness. complexity increases multiple inter-dependent with similar priorities required placed same To mitigate this, we develop tiered framework placement, costly dedicated Master Citizen exclusively assigned executing requests. Firstly, implement priority-based algorithm each device identify high-priority Edge-required microservices. Secondly, sort according their availability place based priority dependencies. Thirdly, strategies scaling request escalation Fog, small number These exempt common communication management responsibilities enable them allocate more resources higher instances. Finally, evaluate our simulated environment. results outperform state-of-the-art frameworks terms utilisation, resulting reduced dependency by one-third compared other approaches average application execution time 65-70%.
Language: Английский
Citations
0
Published: April 12, 2024
Language: Английский
Citations
0
Cluster Computing, Journal Year: 2024, Volume and Issue: 28(1)
Published: Oct. 24, 2024
Language: Английский
Citations
0