Optimization of Maritime Communication Workflow Execution with a Task-Oriented Scheduling Framework in Cloud Computing

被引:4
作者
Ahmad, Zulfiqar [1 ]
Acarer, Tayfun [2 ]
Kim, Wooseong [3 ]
机构
[1] Hazara Univ, Dept Comp Sci & Informat Technol, Mansehra 21300, Pakistan
[2] Piri Reis Univ, Maritime Transportat & Management Vocat Sch Higher, TR-34940 Istanbul, Turkiye
[3] Gachon Univ, Dept Comp Engn, Seongnam 13120, South Korea
关键词
data collection and processing; task execution; cloud computing; latency; vessel traffic management; maritime Strategy; maritime business management; maritime communication; optimization; scheduling; workflows; SCIENTIFIC WORKFLOWS; ARCHITECTURE; MANAGEMENT; FUTURE;
D O I
10.3390/jmse11112133
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
To ensure safe, effective, and efficient marine operations, the optimization of maritime communication workflows with a task-oriented scheduling framework is of the utmost importance. Navigation, vessel traffic management, emergency response, and cargo operations are all made possible by maritime communication, which necessitates seamless information sharing between ships, ports, coast guards, and regulatory bodies. However, traditional communication methods face challenges in adapting to the dynamic and distributed nature of maritime activities. This study suggests a novel approach for overcoming these difficulties that combines task-oriented scheduling and resource-aware cloud environments to enhance marine communication operations. Utilizing cloud computing offers a scalable, adaptable infrastructure that can manage various computational and communication needs. Even during busy times, effective data processing, improved decision making, and improved communication are made possible by utilizing the cloud. The intelligent allocation and prioritization of communication activities using a task-oriented scheduling framework ensures that urgent messages receive prompt attention while maximizing resource utilization. The proposed approach attempts to improve marine communication workflows' task prioritization, scalability, and resource optimization. In order to show the effectiveness of the proposed approach, simulations were performed in CloudSim. The performance evaluation parameters, i.e., throughput, latency, execution cost, and energy consumption, have been evaluated. Simulation results reflect the efficacy and practical usability of the framework in various maritime communication configurations. By making marine communication methods more durable, dependable, and adaptable to the changing needs of the maritime industry, this study advances maritime communication techniques. The findings of this research have the potential to revolutionize maritime communication, leading to safer, more efficient, and more resilient maritime operations on a large scale.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] A Periodic Task-Oriented Scheduling Architecture in Cloud Computing
    Zhang, Peng
    Li, Yan
    Lin, Hailun
    Wang, Jianwu
    Zhang, Chuang
    2018 IEEE INT CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, UBIQUITOUS COMPUTING & COMMUNICATIONS, BIG DATA & CLOUD COMPUTING, SOCIAL COMPUTING & NETWORKING, SUSTAINABLE COMPUTING & COMMUNICATIONS, 2018, : 788 - 794
  • [2] A Task-Oriented Framework for Networked Wearable Computing
    Galzarano, Stefano
    Giannantonio, Roberta
    Liotta, Antonio
    Fortino, Giancarlo
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2016, 13 (02) : 621 - 638
  • [3] Regressive Whale Optimization for Workflow Scheduling in Cloud Computing
    Reddy, G. Narendrababu
    Kumar, S. Phani
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS, 2019, 18 (04)
  • [4] Comparison of Workflow Scheduling Algorithms in Cloud Computing
    Kaur, Navjot
    Aulakh, Taranjit Singh
    Cheema, Rajbir Singh
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2011, 2 (10) : 81 - 86
  • [5] Multi-Objective Task and Workflow Scheduling Approaches in Cloud Computing: a Comprehensive Review
    Hosseinzadeh, Mehdi
    Ghafour, Marwan Yassin
    Hama, Hawkar Kamaran
    Vo, Bay
    Khoshnevis, Afsane
    JOURNAL OF GRID COMPUTING, 2020, 18 (03) : 327 - 356
  • [6] An Efficient Task Scheduling for Cloud Computing Platforms Using Energy Management Algorithm: A Comparative Analysis of Workflow Execution Time
    Ahmed, Adeel
    Adnan, Muhammad
    Abdullah, Saima
    Ahmad, Israr
    Alturki, Nazik
    Jamel, Leila
    IEEE ACCESS, 2024, 12 : 34208 - 34221
  • [7] Cloud Computing Workflow Framework with Resource Scheduling Mechanism
    Wang Yan
    Wang Jinkuan
    Han Yinghua
    2016 IEEE CHINESE GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC), 2016, : 342 - 345
  • [8] Selective Task Scheduling for Time-targeted Workflow Execution on Cloud
    Jung, In-Yong
    Jeong, Chang-Sung
    2014 IEEE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS, 2014 IEEE 6TH INTL SYMP ON CYBERSPACE SAFETY AND SECURITY, 2014 IEEE 11TH INTL CONF ON EMBEDDED SOFTWARE AND SYST (HPCC,CSS,ICESS), 2014, : 1055 - 1059
  • [9] A Trust Service-Oriented Scheduling Model for Workflow Applications in Cloud Computing
    Tan, WenAn
    Sun, Yong
    Li, Ling Xia
    Lu, GuangZhen
    Wang, Tong
    IEEE SYSTEMS JOURNAL, 2014, 8 (03): : 868 - 878
  • [10] Adaptive Workflow Scheduling on Cloud Computing Platforms with Iterative Ordinal Optimization
    Zhang, Fan
    Cao, Junwei
    Hwang, Kai
    Li, Keqin
    Khan, Samee U.
    IEEE TRANSACTIONS ON CLOUD COMPUTING, 2015, 3 (02) : 156 - 168