Open Access   Article Go Back

Dynamic Information Validation Scheme in Internet of Things: Software Agent based Approach

Sharanappa P. H.1 , Mahabaleshwar S. Kakkasageri2

Section:Research Paper, Product Type: Journal Paper
Volume-9 , Issue-7 , Page no. 1-10, Jul-2021

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v9i7.110

Online published on Jul 31, 2021

Copyright © Sharanappa P. H., Mahabaleshwar S. Kakkasageri . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Sharanappa P. H., Mahabaleshwar S. Kakkasageri, “Dynamic Information Validation Scheme in Internet of Things: Software Agent based Approach,” International Journal of Computer Sciences and Engineering, Vol.9, Issue.7, pp.1-10, 2021.

MLA Style Citation: Sharanappa P. H., Mahabaleshwar S. Kakkasageri "Dynamic Information Validation Scheme in Internet of Things: Software Agent based Approach." International Journal of Computer Sciences and Engineering 9.7 (2021): 1-10.

APA Style Citation: Sharanappa P. H., Mahabaleshwar S. Kakkasageri, (2021). Dynamic Information Validation Scheme in Internet of Things: Software Agent based Approach. International Journal of Computer Sciences and Engineering, 9(7), 1-10.

BibTex Style Citation:
@article{H._2021,
author = {Sharanappa P. H., Mahabaleshwar S. Kakkasageri},
title = {Dynamic Information Validation Scheme in Internet of Things: Software Agent based Approach},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2021},
volume = {9},
Issue = {7},
month = {7},
year = {2021},
issn = {2347-2693},
pages = {1-10},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5356},
doi = {https://doi.org/10.26438/ijcse/v9i7.110}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v9i7.110}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5356
TI - Dynamic Information Validation Scheme in Internet of Things: Software Agent based Approach
T2 - International Journal of Computer Sciences and Engineering
AU - Sharanappa P. H., Mahabaleshwar S. Kakkasageri
PY - 2021
DA - 2021/07/31
PB - IJCSE, Indore, INDIA
SP - 1-10
IS - 7
VL - 9
SN - 2347-2693
ER -

VIEWS PDF XML
319 450 downloads 140 downloads
  
  
           

Abstract

The Internet of Things (IoT) and its various application domains are drastically changing people`s lives by providing intelligent services that will eventually become an intrinsic part of their daily environment. The data flows received from various actuators and sensors are used to power the IoT services. The accuracy and security of sensor data supplied across the Internet of Things system is a vital aspect in ensuring that IoT services work properly. As a result, data validation in a remote IoT network is becoming increasingly important. Even though the immediate option of establishing duplicate identical systems can provide validation, real-world change limitations can make this difficult, if not impossible. So here in this paper we have proposed an intelligent validation scheme. We have evaluated the performance and effectiveness of proposed scheme by comparing with an existing technique that uses BL and KP-ABE scheme. In terms of time necessary to sense the data, data gathering time, time required to validate the data, and end to end delay, the suggested method outperforms the existing validation methodology.

Key-Words / Index Term

Ingternet of Things, Information Validation, Multi agents

References

[1] I. M. Pires, N. M. Garcia, N, Pombo, F. Florez-Revuelta, N. D. Rodriguez, "Validation Techniques for Sensor Data in Mobile Health Applications", Journal of Sensors, Vol. 2016.
[2] J. Ravichandran, A. I. Arulappan, "Data Validation Algorithm for Wireless Sensor Networks", International Journal of Distributed Sensor Networks, Vol. 2013.
[3] N. A. M. Alduais, J. Abdullah, A. Jamil, L. Audah and R. Alias, "Effect of Data Validation Schemes on the Energy Consumptions of Edge Device in IoT /WSN", In the Proceedings of the 14th International Wireless Communications & Mobile Computing Conference (IWCMC), Limassol, , pp. 77-81, 2018.
[4] N. A. M. Alduais, J. Abdullah, A. Jamil, L. Audah and R. Alias, "Sensor Node Data Validation Techniques for Realtime IoT/WSN Application", In Proceedings of the 14th International Multi-Conference on Systems, Signals & Devices (SSD), Marrakech, , pp. 760-765, 2017.
[5] G. D`Emilia and A. Gaspari, "Data Validation Techniques for Measurements Systems Operating in a Industry 4.0 Scenario a Condition Monitoring Application", 2018 Workshop on Metrology for Industry 4.0 and IoT, Brescia, , pp. 112-116, 2018.
[6] L. Russell, F. Kwamena and R. Goubran, "Towards Reliable IoT: Fog-Based AI Sensor Validation", 2019 IEEE Cloud Summit, Washington, DC, USA, pp. 37-44, 2019.
[7] H. Sandor, B. Genge and Z. Szanto, "Sensor data validation and abnormal behavior detection in the Internet of Things", In the Proceedings of the 16th RoEduNet Conference: Networking in Education and Research (RoEduNet), Targu Mures, pp. 1-5, 2017.
[8] V. Chacko and V. Bharati, "Data Validation and Sensor Life Prediction Layer on Cloud for IoT", In the Proceedings of the IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Exeter, pp. 906-909, 2017.
[9] M. Sutaone, P. Mukherj and S. Paranjape, "Trust-based Cluster head validation and outlier detection technique for Mobile Wireless Sensor Networks", In the Proceedings of the 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, pp. 2066-2070, 2016.
[10] Y. Zhang, C. M. Bingham, M. Gallimore, Z. Yang and J. Chen, "Applied sensor fault detection and validation using transposed input data PCA and ANNs", In the Proceedings of the 2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), Hamburg, pp. 269-274, 2012.
[11] A. Appice, P. Guccione, D. Malerba, A. Ciampi, "Dealing with temporal and spatial correlations to classify outliers in geophysical data streams", Information Sciences: an International Journal, Vol.285(1), pp. 162-180, 2014.
[12] F. Angiulli, F. Fassetti, "Detecting Distance-Based Outliers in Streams of Data", In the Proceedings of the Sixteenth ACM Conference on Information and Knowledge Management, CIKM, Lisbon, Portugal, 2007.
[13] M. Gupta, J. Gao, C. C. Aggarwal and J. Han, "Outlier Detection for Temporal Data: A Survey", IEEE Transactions on Knowledge and Data Engineering, Vol. 26, No. 9, pp. 2250-2267, 2014, doi: 10.1109/TKDE.2013.184.
[14] S. Yuxiang, X. Kunqing, M. Xiujun, J. Xingxing, P. Wen and G. Xiaoping, "Detecting Spatio-temporal Outliers in Climate Dataset: A Method Study", In the Proceedingsof the 2005 IEEE International Geoscience and Remote Sensing Symposium. IGARSS `05., Seoul, Korea (South), 2005.
[15] M. Mathioudakis, N. Bansal, N. Koudas, "Identifying, Attributing and Describing Spatial Bursts", In the Proceedings of the VLDB Endowment, Vol. 3. No. 1, pp. 1091-1102, 2010.
[16] Y. Zhang, N. Meratnia and P. Havinga, "Outlier Detection Techniques for Wireless Sensor Networks: A Survey", In the Proceedingsof the IEEE Communications Surveys & Tutorials, Vol. 12, No. 2, pp. 159-170, Second Quarter 2010.
[17] P. Yang, D. Stankevicius, V. Marozas, Z. Deng, E. Liu, A. Lukosevicius, F. Dong, L. Xu, G. Min, "Lifelogging Data Validation Model for Internet of Things Enabled Personalized Healthcare", IEEE Transactions on Systems, Man and Cybernetics: Systems, Vol. 48, No. 1, pp. 50-64, 2018.
[18] M.S. Kakkasageri, S.S. Manvi, "Information Management in Vehicular Ad hoc Networks: A Review", Journal of Network and Computer Applications, Vol. 39, pp 334-350, 2014.
[19] M. A. Cuguero, M. Christodoulou, J. Quevedo, V. Puig, D. Garcia and M. P. Michaelides, "Combining contaminant event diagnosis with data validation/reconstruction: Application to smart buildings", In the Proceedings of the 22nd Mediterranean Conference on Control and Automation, Palermo, Italy, pp. 293-298, 2014.
[20] Y. Chen, J. Yang and S. Jiang, "Data validation and dynamic uncertainty estimation of self-validating sensor", In the Proceedings of the 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Pisa, Italy, pp. 405-410, 2015.
[21] R. Sharifi, R. Langari, "A Hybrid AANN-KPCA Approach to Sensor Data Validation", In the Proceedings of the seventh WSEAS International Conference on Applied Informatics and Communications, Athens, Greece, pp.85-91, 2007.
[22] P. H. Ibarguengoytia, L. E. Sucar and S. Vadera, "Real time intelligent sensor validation", In the Proceedings of the IEEE Transactions on Power Systems, Vol. 16, No. 4, pp. 770-775, 2001.
[23] J. Rivera-Mejia, E. Arzabala-Contreras and A. G. Leon-Rubio, "Approach to the validation function of intelligent sensors based on error`s predictors", In the Proceedings of the 2010 IEEE Instrumentation & Measurement Technology Conference Proceedings, Austin, TX, USA, pp. 1121-1125, 2010.
[24] B. Mounika, G. Raghu, S. Sreelekha and R. Jeyanthi, "Neural network based data validation algorithm for pressure processes", In the Proceedings of the 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), Kanyakumari, India, pp. 1223-1227, 2014.
[25] Z. Shen and Q. Wang, "Data validation and confidence of self-validating multifunctional sensor",Journal of SENSORS IEEE, Taipei, Taiwan, pp. 1-4, 2012.
[26] Q. Wang, Z. Shen and F. Zhu, "A multifunctional self-validating sensor", In the Proceedings of the 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Minneapolis, MN, USA, pp. 1283-1288, 2013.
[27] Narander Kumar and S. Jitendra Kumar, “Secure Data Validation and Transmission in Cloud and IoT Through Ban Logic and KP-ABE”, International Journal of Sensors, Wireless Communications and Control.
[28] P. H. Sharanappa, M. S. Kakkasageri, "Intelligent Information Gathering Scheme in Internet of Things (IoT)", In the Proceedings of the 11th International Conference on Advanced Computing (ICoAC), Department of Computer Technology, Anna University, MIT Campus, Chennai, India, pp.136-140, 2019.
[29] P. M. Chanal, M. S. Kakkasageri, “Security and Privacy in IoT: A Survey”, Journal of Wireless Personal Communication, Springer, Vol. 115, No. 3, pp.1667–1693, 2020
[30] P. M. Chanal, M. S. Kakkasageri, “Hybrid Algorithm for Data Confidentiality In Internet of Things”, In the Proceedings of the 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), IIT Kanpur, India, 2019.
[31] P. M. Chanal, M. S. Kakkasageri, “Preserving Data Confidentiality in Internet of Things”, Journal of SN Computer Science, Springer, Vol. 2, No. 1, pp. 1-12, 2021.