Gateway Clustering Framework for the Integration of Heterogeneous Aviation Information Networks

被引:0
|
作者
Liu, Hui [1 ]
Zhang, Jun
Cheng, L. L. [2 ]
机构
[1] Beihang Univ, Dept Elect & Informat Engn, Beijing, Peoples R China
[2] City Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China
基金
美国国家科学基金会; 中国博士后科学基金;
关键词
LOAD DISTRIBUTION; WIRELESS; ACCESS; MANAGEMENT; SURVEILLANCE; AIRPORT;
D O I
10.1109/TAES.2012.6237592
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
The integration of heterogeneous aviation information networks (HAIN) has recently attracted significant attention among researchers. An important topic requiring discussion is the method by which timely and accurate information may be acquired to ensure aviation safety and facilitate risk evaluation. This paper proposes a distributed gateway clustering framework, whereby gateways collaborate and cooperate with each other to achieve load balancing and cooperative communication for the integration of HAIN. Unlike traditional approaches, in the framework, a cooperative architecture is presented for HAIN interoperability and load preference is taken into account to cater to the specialized nature of HAIN through describing load matrix. Two approaches are proposed for load allocation: 1) the load preference allocation (LPA) algorithm at the subnet level in which each subnet is controlled by the same gateway with predictive load assignment by incorporating the historical load information of each subnet; and 2) the gateway cooperative load allocation (GCLA) algorithm at the gateway level aimed to balance the distribution of traffic load among gateways globally. The related parameters of operating efficiency and processing time are used to analyze and evaluate the performance of the proposed load allocation algorithms of the integrated HAIN system. Simulation results are presented to show the effectiveness of the proposed framework.
引用
收藏
页码:2282 / 2301
页数:20
相关论文
共 50 条
  • [21] Clustering for heterogeneous information networks with extended star-structure
    Jian-Ping Mei
    Huajiang Lv
    Lianghuai Yang
    Yanjun Li
    [J]. Data Mining and Knowledge Discovery, 2019, 33 : 1059 - 1087
  • [22] Mutual clustering on comparative texts via heterogeneous information networks
    Cao, Jianping
    Wang, Senzhang
    Wen, Danyan
    Peng, Zhaohui
    Yu, Philip S.
    Wang, Fei-yue
    [J]. KNOWLEDGE AND INFORMATION SYSTEMS, 2020, 62 (01) : 175 - 202
  • [23] Gateway framework for home appliance's interoperability based on heterogeneous middleware in residential networks
    Cho, SY
    Seo, DY
    Kim, TY
    [J]. 2002 INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS, DIGEST OF TECHNICAL PAPERS, 2002, : 98 - 99
  • [24] Design and emulation of integration framework for heterogeneous wireless PAN networks
    Kong, In-Yeup
    Hwang, Won-Joo
    [J]. UBIQUITOUS COMPUTING SYSTEMS, PROCEEDINGS, 2006, 4239 : 368 - 383
  • [25] An Efficient Gateway Node Selection Method for Clustering in Heterogeneous Mobile Ad-hoc Networks
    Panse, Trishna
    Panse, Prashant
    [J]. WIRELESS PERSONAL COMMUNICATIONS, 2024, 135 (01) : 113 - 126
  • [26] Clustering on heterogeneous networks
    Huang, Yue
    Gao, Xuedong
    [J]. WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2014, 4 (03) : 213 - 233
  • [27] Intelligent Gateway for Heterogeneous Networks Environment in Remote Monitoring of Greenhouse Facility Information Collection
    Wang Xin
    Wang Yu
    Zhang Yuanyuan
    Ni Xindong
    Wang Shumao
    [J]. IFAC PAPERSONLINE, 2018, 51 (17): : 217 - 222
  • [28] A fast clustering algorithm based on embedding technology for heterogeneous information networks
    Chen, Li-Min
    Yang, Jing
    Zhang, Jian-Pei
    [J]. Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2015, 37 (11): : 2634 - 2641
  • [29] A node clustering algorithm for heterogeneous information networks based on node embeddings
    Liu, Dongjiang
    Li, Leixiao
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 83 (2) : 3745 - 3766
  • [30] Clustering via Meta-path Embedding for Heterogeneous Information Networks
    Zhang, Yongjun
    Yang, Xiaoping
    Wang, Liang
    [J]. 11TH IEEE INTERNATIONAL CONFERENCE ON KNOWLEDGE GRAPH (ICKG 2020), 2020, : 188 - 194