首页    期刊浏览 2024年11月28日 星期四
登录注册

文章基本信息

  • 标题:Nature-Inspired Metaheuristic Multi-Optimal Global Resource Identification Mechanism for On-Demand Mobile Users
  • 本地全文:下载
  • 作者:Yakubu Suleiman Baguda ; Hani Meateg Al-Jahdali
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2019
  • 卷号:19
  • 期号:3
  • 页码:190-199
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:The ability to effectively identify a potential resource in mobile environment is challenging and difficult. Managing and utilization of the resources depends ultimately on the mobile users to identify the best available resource within close proximity. The resources can be available but the ability to choose the optimal resource amongst global multiple resources needs highly efficient optimization scheme which dynamically adapts with the mobile environment and users as well. It is very obvious that the naturally inspired metaheuristic algorithms have had greater impact in optimization field. The natural phenomenon of the nature-inspired algorithms can be used in exploiting the optimal resource which satisfies the on-demand mobile user requirement and constraints. In this paper, a naturally-inspired resource identification scheme has been proposed to effectively identify the potential resource within close proximity to the on-demand mobile users. The simulation result shows that the proposed nature-inspired multi-optimal global resource scheme has been able to determine the global optimal resource amongst the available the multiple resources and it has improved the performance and reduce the computational time when compared to conventional firefly resource scheme.
  • 关键词:Nature-inspired optimization; Firefly algorithm; global optimal; mobile user; resource fitness; proximity
国家哲学社会科学文献中心版权所有