Optimization of 6G resource allocation using CyberTwin function-based service enhancement scheme
Shranjeno v:
| izdano v: | EURASIP Journal on Wireless Communications and Networking vol. 2025, no. 1 (Dec 2025), p. 30 |
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| Izdano: |
Springer Nature B.V.
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| Teme: | |
| Online dostop: | Citation/Abstract Full Text - PDF |
| Oznake: |
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| 024 | 7 | |a 10.1186/s13638-025-02444-1 |2 doi | |
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| 045 | 2 | |b d20251201 |b d20251231 | |
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| 245 | 1 | |a Optimization of 6G resource allocation using CyberTwin function-based service enhancement scheme | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a The most innovative Service-Optimized Logging for Resource Allocation (SOL-RA) is in situations that support 6G connection. The CyberTwin architecture optimizes the quality of service provided to end users in 6G communications by using the dependability of terahertz connections and interactions of a machine-type nature. Elastically sharing elastic resources among users is made possible by the proposed resource allocation strategy, which makes use of proprietary logger functions. This ensures that efficient allocation is achieved without overlapping or lengthy wait periods. Within the framework of SOL-RA, a categorization mechanism is implemented for dense requests, which differentiates them as either stationary or priority services. Resource allocations are dynamically done based on this categorization, which enhances the organization's responsiveness to different needs. Through a tree classifier learning mechanism, CyberTwin logs play an essential part in the processing of requests and the preparation of resources. This helps to ensure that resources are distributed without inefficiency. Requests that are generating a backlog are identified and processed in parallel by the system, which significantly reduces the amount of time that is wasted waiting. In order to guarantee a specialized distribution for the categorized outputs, resource allocations are directed by CyberTwin data logs. An examination of the performance of the SOL-RA scheme takes into account important metrics such service latency, service backlog, resource usage, and request-to-response ratio. This research offers insights into the efficacy of the scheme in maximizing service quality and resource consumption in 6G settings. | |
| 653 | |a Classification | ||
| 653 | |a Computer science | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Edge computing | ||
| 653 | |a Communication | ||
| 653 | |a Proprietary | ||
| 653 | |a Quality of service architectures | ||
| 653 | |a Optimization | ||
| 653 | |a End users | ||
| 653 | |a Resource allocation | ||
| 653 | |a Network latency | ||
| 653 | |a Computer engineering | ||
| 653 | |a Communications networks | ||
| 653 | |a Quality of service | ||
| 653 | |a Algorithms | ||
| 653 | |a Machine learning | ||
| 773 | 0 | |t EURASIP Journal on Wireless Communications and Networking |g vol. 2025, no. 1 (Dec 2025), p. 30 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3203423560/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3203423560/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |