Intelligent Data Aggregation Framework for Resource Constrained Remote Internet of Things Applications

被引:0
作者
Abhijith, H., V [1 ]
Babu, H. S. Ramesh [2 ]
机构
[1] Visvesvarya Technol Univ, Dept Informat Sci & Engn, Sai Vidya Inst Technol, Bangalore, Karnataka, India
[2] Visvesvarya Technol Univ, Dept Comp Sci & Engn, Sai Vidya Inst Technol, Bangalore, Karnataka, India
关键词
Wireless sensor networks; Internet of Things; intelligent boundary determination; sensor nodes; data aggregation; INFORMATION; EFFICIENT;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Internet of Things (IoT) is a technology that can connect everything to the Internet. IoT can be used in a wide range of applications which includes remote applications like Underwater networks. Remote applications involve the deployment of several low-power, low-cost interconnected sensor nodes in the specific region. With a massive amount of devices connected to the IoT and the considerable amount of data associated with it, there remain concerns about data management. Also, the amount of data generated in an extensive IoT-based remote sensing network is usually enormous for the servers to process, and many times data generated are redundant. Hence there is a need for designing a framework that addresses both aggregations of data and security-related issues at various aggregation points. In this paper, we are proposing an intelligent data aggregation mechanism for IoT-based remote sensing networks. This method avoids redundant data transmission by adapting spatial aggregation techniques. The proposed method was tested through simulations, and the results prove the efficiency of the proposed work.
引用
收藏
页码:146 / 151
页数:6
相关论文
共 17 条
[1]  
Abhijith HV, 2015, IEEE INT ADV COMPUT, P149, DOI 10.1109/IADCC.2015.7154688
[2]  
Abhijith H.V., 2018, P 3 INT C INT THINGS
[3]   A Review of Aggregation Algorithms for the Internet of Things [J].
Al-Doghman, Firas ;
Chaczko, Zenon ;
Jiang, Jianming .
2017 25TH INTERNATIONAL CONFERENCE ON SYSTEMS ENGINEERING (ICSENG), 2017, :480-487
[4]  
Chen J., 2017, ACM WORKSH DEP ISS W
[5]  
Chieh-Chuan-Hsiao, 2009, CHIRON ENERGY EFFICI
[6]   A Cluster-Based Data Fusion Technique to Analyze Big Data in Wireless Multi-Sensor System [J].
Din, Sadia ;
Ahmad, Awais ;
Paul, Anand ;
Rathore, Muhammad Mazhar Ullah ;
Jeon, Gwanggil .
IEEE ACCESS, 2017, 5 :5069-5083
[7]  
Heinzelman W.B., 2000, Ph.D. thesis
[8]  
Intanagonwiwat C., 2000, P ACM MOBICOM, P56, DOI DOI 10.1145/345910.345920
[9]  
Krishnamachari B, 2004, IEEE IPCCC, P717
[10]   Negotiation-based protocols for disseminating information in wireless sensor networks [J].
Kulik, J ;
Heinzelman, W ;
Balakrishnan, H .
WIRELESS NETWORKS, 2002, 8 (2-3) :169-185