ArticleScientific reports2026
Performance and energy consumption optimization of ternary optical computers based on the M/G/1 queuing model.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study addresses quality-of-service (QoS) and energy-consumption challenges in Ternary Optical Computer (TOC) by proposing a novel three-phase service model. The model integrates an M/G/1 queuing system with an Ν-policy and multiple vacation mechanisms into the TOC service framework for the first time. In this system, the server enters a vacation state when idle and resumes service immediately when the number of customers reaches a predetermined threshold Ν. We perform an in-depth analysis of the third phase using stochastic-decomposition methods to model precisely the steady-state queue length. For the first and second phases, we employ an approximate analysis to balance computational complexity and accuracy, yielding the system's average queue length. By applying Little's Law, we then derive an expression for the overall system's sojourn time. Furthermore, we utilize the Renewal Reward Theorem to construct a cost function representing TOC energy consumption, and perform numerical experiments to identify the optimal threshold Ν. Our results demonstrate that the proposed model significantly reduces energy consumption while maintaining satisfactory system performance, offering new theoretical insights and practical guidelines for dual-objective optimization in TOC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.