Assessing the Complexity of Intelligent Parks' Internet of Things Big Data System

被引:3
|
作者
Liu, Jialu [1 ]
Guo, Renzhong [2 ]
Cai, Zhiming [1 ]
Liu, Wenjian [1 ]
Du, Wencai [1 ]
机构
[1] City Univ Macau, Inst Data Sci, Macau 999078, Peoples R China
[2] Shenzhen Univ, Sch Architecture & Urban Planning, Res Inst Smart Cities, Shenzhen 518060, Peoples R China
关键词
SMART CITIES; CITY;
D O I
10.1155/2021/5528135
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Today, intelligence in all walks of life is developing at an unexpectedly fast speed. The complexity of the Internet of Things (IoT) big data system of intelligent parks is analyzed to unify the information transmission of various industries, such as smart transportation, smart library, and smart medicine, thereby diminishing information islands. The traditional IoT systems are analyzed; on this basis, a relay node is added to the transmission path of the data information, and an intelligent park IoT big data system is constructed based on relay cooperation with a total of three hops. Finally, the IoT big data system is simulated and tested to verify its complexity. Results of energy efficiency analysis suggest that when the power dividing factor is 0.5, 0.1, and 0.9, the energy efficiency of the IoT big data system first increases and then decreases as alpha(0) increases, where the maximum value appears when alpha(0) is about 7 J. Results of outage probability analysis demonstrate that the system's simulation result is basically the same as that of the theoretical result. Under the same environment, the more hop paths the system has, the more the number of relays is; moreover, the larger the fading index m, the better the system performance, and the lower the outage possibility. Results of transmission accuracy analysis reveal that the IoT big data system can provide a result that is the closest to the actual result when the successful data transmission probability is 100%, and the parameter lambda values are between 0.01 and 0.05; in the meantime, the delay of successful data transmission is reduced gradually. In summary, the wireless relay cooperation transmission technology can reduce the outage probability and data transmission delay probability of the IoT big data system in the intelligent park by adding the multihop path, thereby improving the system performance. The above results can provide an experimental basis for exploring the complexity of IoT systems in intelligent parks.
引用
收藏
页数:12
相关论文
共 50 条
  • [41] A Big Data Correlation Orchestrator for Internet of Things
    Mozumdar, Mohammad
    Shahbazian, Amir
    Nhat-Quang Ton
    2014 IEEE WORLD FORUM ON INTERNET OF THINGS (WF-IOT), 2014, : 304 - 308
  • [42] Big Data Classification and Internet of Things in Healthcare
    Rghioui, Amine
    Lloret, Jaime
    Oumnad, Abedlmajid
    INTERNATIONAL JOURNAL OF E-HEALTH AND MEDICAL COMMUNICATIONS, 2020, 11 (02) : 20 - 37
  • [43] Big Sensed Data challenges in the Internet of Things
    Hassanein, Hossam S.
    Oteafy, Sharief M. A.
    2017 13TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING IN SENSOR SYSTEMS (DCOSS), 2017, : 207 - 208
  • [44] The role of big data analytics in Internet of Things
    Ahmed, Ejaz
    Yaqoob, Ibrar
    Hashem, Ibrahim Abaker Targio
    Khan, Imran
    Ahmed, Abdelmuttlib Ibrahim Abdalla
    Imran, Muhammad
    Vasilakos, Athanasios V.
    COMPUTER NETWORKS, 2017, 129 : 459 - 471
  • [45] Big data, the Internet of things, and the interconnected society
    Liu, Yu-li
    Chou, Yuntsai Jessica
    TELECOMMUNICATIONS POLICY, 2018, 42 (04) : 277 - 281
  • [46] Big Data Privacy in the Internet of Things Era
    Perera, Charith
    Ranjan, Rajiv
    Wang, Lizhe
    Khan, Samee U.
    Zomaya, Albert Y.
    IT PROFESSIONAL, 2015, 17 (03) : 32 - 39
  • [47] Medical Internet of Things and Big Data in Healthcare
    Dimitrov, Dimiter V.
    HEALTHCARE INFORMATICS RESEARCH, 2016, 22 (03) : 156 - 163
  • [48] Application of the Integration of the Internet of Things and Big Data
    Wang, Yingli
    PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON MECHANICAL, ELECTRONIC, CONTROL AND AUTOMATION ENGINEERING (MECAE 2018), 2018, 149 : 249 - 254
  • [49] The Internet of Things and Big Data: Future Trends
    Carvalho, Goncalo
    Bernardino, Jorge
    2017 12TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2017,
  • [50] Deep Learning in Big Data and Internet of Things
    Tomar, Dimpal
    Tomar, Pradeep
    Kaur, Gurjit
    INFORMATION, COMMUNICATION AND COMPUTING TECHNOLOGY, ICICCT 2018, 2019, 835 : 70 - 81