Academic Journal
An Advanced Intelligence Protocol for Context-Aware Edge Computing Devices in Distributed Systems.
| Τίτλος: | An Advanced Intelligence Protocol for Context-Aware Edge Computing Devices in Distributed Systems. |
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| Συγγραφείς: | Suryawanshi, Vishnu, Sharma, Nakul, Karlekar, Nandkishor P., Cholke, Abhijeet, Bogam, Vishal, Gurav, Raju Prakash, Devhare, Bharat |
| Πηγή: | Engineering, Technology & Applied Science Research; Jun2026, Vol. 16 Issue 3, p36856-36863, 8p |
| Θεματικοί όροι: | Context-aware computing, Edge computing, Distributed computing, Bayesian analysis, Automated planning & scheduling, Compliance auditing, Intelligent control systems, Reinforcement learning |
| Περίληψη: | The increasing complexity of integrated computing environments requires sustainable architectures that can adapt, evolve, and remain reliable throughout their lifetime. Current edge computing environments are frequently deficient in dynamic context management, adaptive scheduling, and continuous compliance. This work aims to mitigate these limitations and presents an open-source framework that unifies multidimensional contextual analysis, adaptive task scheduling, lifecycle-conscious security, and continuous compliance within a single closed-loop system. The proposed solution utilizes a hybrid methodology consisting of Bayesian inference for probabilistic context reasoning and Deep Reinforcement Learning (DRL) for adaptive decision-making. Experimental analysis shows that the proposed protocol framework is superior to currently available models, resulting in a 24 % reduction in latency, a 14 % decrease in power consumption, and a 96 % compliance rate. These findings confirm that the proposed approach is scalable and enables intelligent, secure, and compliance-aware edge computing systems. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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