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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2024

Multiprocessor Task Scheduling Optimization for Cyber-Physical System Using an Improved Salp Swarm Optimization Algorithm

The record

Type
Publication
Date
1 January 2024
Level
National
Journal
SN Computer Science
Volume
5
Issue
1
Published
1 January 2024
DOI
10.1007/s42979-023-02517-2
Scopus ID
85181920936
ISSN
2662995X
Authors
3
Open access
No
Citations
10
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending

    TargetPrimaryModerate confidenceJudged

    Improved salp swarm algorithm with local search advances multiprocessor task scheduling optimization for cyber-physical systems and grid computing.

    Moderate confidence
    The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-3 Innovation, Science and Technology

    ThemePrimaryModerate confidenceJudged

    Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. Improved salp swarm algorithm with local search advances multiprocessor task scheduling optimization for cyber-physical systems and grid computing.

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “Multiprocessor Task Scheduling Optimization for Cyber-Physical System Using an Improved Salp Swarm Optimization Algorithm”. Kortex.

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