Fuzzy logic based resource allocation for isolated and multiple platforms

被引:9
|
作者
Smith, JF [1 ]
Rhyne, RD [1 ]
机构
[1] USN, Res Lab, Washington, DC 20375 USA
关键词
fuzzy logic; genetic algorithms; expert systems; distributed AI algorithms;
D O I
10.1117/12.395092
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Modern naval battle forces generally include many different platforms each with its own sensors, radar, ESM, and communications. The sharing of information measured by local sensors via communication links across the battle group should allow for optimal or near optimal decisions. The survival of the battle group or members of the group depends on the automatic real-time allocation of various resources. A fuzzy logic algorithm has been developed that automatically allocates electronic attack (EA) resources in real-time. The particular approach to fuzzy logic that is used is the fuzzy decision tree, a generalization of the standard artificial intelligence technique of decision trees. The controller must be able to make decisions based on rules provided by experts. The fuzzy logic approach allows the direct incorporation of expertise forming a fuzzy linguistic description, i.e., a formal representation of the system in terms of fuzzy if-then rules. Genetic algorithm based optimization is conducted to determine the form of the membership functions for the fuzzy root concepts. The isolated platform and multiple platform resource manager models are discussed as well as the underlying multi-platform communication model. The resource manager is shown to exhibit excellent performance under many demanding scenarios.
引用
收藏
页码:36 / 47
页数:12
相关论文
共 50 条
  • [21] Designing a Fuzzy-Logic Based Trust and Reputation Model for Secure Resource Allocation in Cloud Computing
    Chandran, Kamalanathan
    Shanmugasudaram, Valarmathy
    Subramani, Kirubakaran
    INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2016, 13 (01) : 30 - 37
  • [22] Joint Resource Allocation for Adaptive Fuzzy Logic Based Coordinated Multi-Cell NOMA Systems
    Zeng, Haiyong
    Zhu, Xu
    Jiang, Yufei
    Wei, Zhongxiang
    ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2019,
  • [23] RETRACTION: Resource allocation with fuzzy logic based network optimization and security analysis in optical communication network
    Jessie Rani, Hannah
    Gupta, Rupal
    Dadhich, Atul
    Gupta, Sachin
    Swetha, G.
    Kolluru, Dakshinamurthy V.
    Subrahmanyam, Kodukula
    OPTICAL AND QUANTUM ELECTRONICS, 2024, 56 (09)
  • [24] Tolerance allocation based on fuzzy logic and simulated annealing
    Ecole Polytechnique, Montreal, Canada
    J Intell Manuf, 6 (487-497):
  • [25] Tolerance allocation based on fuzzy logic and simulated annealing
    Dupinet, E
    Balazinski, M
    Czogala, E
    JOURNAL OF INTELLIGENT MANUFACTURING, 1996, 7 (06) : 487 - 497
  • [26] Optimizing SDN resource allocation using fuzzy logic and VM mapping technique
    Soltani, Mohammad Amin Zare
    Seno, Seyed Amin Hosseini
    Mohajerzadeh, Amirhossein
    COMPUTING, 2025, 107 (01)
  • [27] Fuzzy Based Job Classification and Resource Allocation in IoT
    Hatti, Daneshwari I.
    Sutagundar, Ashok V.
    PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE SYSTEMS AND CONTROL (ICISC 2017), 2017, : 176 - 179
  • [28] Fuzzy logic based resource manager for a team of UAVs
    Smith, J. F., III
    Nguyen, T. H.
    NAFIPS 2006 - 2006 ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1 AND 2, 2006, : 484 - +
  • [29] Information Resource Management Technology Based on Fuzzy Logic
    Vysotska, Victoria
    Berko, Andriy
    Lytvyn, Vasyl
    Kravets, Petro
    Dzyubyk, Lyudmyla
    Bardachov, Yuriy
    Vyshemyrska, Svitlana
    LECTURE NOTES IN COMPUTATIONAL INTELLIGENCE AND DECISION MAKING (ISDMCI 2020), 2020, 1246 : 164 - 182
  • [30] Efficient IaC-Based Resource Allocation for Virtualized Cloud Platforms
    Mukhopadhyay, Nirmalya
    Tewari, Babul P.
    ADVANCED NETWORK TECHNOLOGIES AND INTELLIGENT COMPUTING, ANTIC 2021, 2022, 1534 : 200 - 214