Trustworthy Wireless Sensor Networks for Monitoring Humidity and Moisture Environments

Wireless sensors networks (WSNs) are characterized by flexibility and scalability in any environment. These networks are increasingly used in agricultural and industrial environments and have a dual role in data collection from sensors and transmission to a monitoring system, as well as enabling the management of the monitored environment. Environment management depends on trust in the data collected from the surrounding environment, including the time of data creation. This paper proposes a trust model for monitoring humidity and moisture in agricultural and industrial environments. The proposed model uses a digital signature and public key infrastructure (PKI) to establish trust in the data source, i.e., the trust in the sensor. Trust in data generation is essential for real-time environmental monitoring and subsequent analyzes, thus timestamp technology is implemented here to further ensure that gathered data are not created or changed after the assigned time. Model validation is performed using the Castalia network simulator by testing energy consumption at the receiver and sender nodes and the delay incurred by creating or validating a trust token. In addition, validation is also performed using the Ascertia TSA Crusher application for the time consumed to obtain a timestamp from the free TSA. The results show that by applying different digital signs and timestamps, the trust entity of the WSN improved significantly with an increase in power consumption of the sender node by up to 9.3% and receiver node by up to 126.3% for a higher number of nodes, along with a packet delay of up to 15.6% and an average total time consumed up to 1.186 s to obtain the timestamp from the best chosen TSA, which was as expected.

[1]  S. A. Imam,et al.  Design issues for wireless sensor networks and smart humidity sensors for precision agriculture: A review , 2015, 2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI).

[3]  K. Lakshmisudha,et al.  Smart Precision based Agriculture using Sensors , 2016 .

[4]  Xinping Guan,et al.  Industrial high-speed wireless synchronous data acquisition system with real-time data compression , 2013 .

[5]  Wei Yang,et al.  DCE: A Distributed Energy-Efficient Clustering Protocol for Wireless Sensor Network Based on Double-Phase Cluster-Head Election , 2017, Sensors.

[6]  Micheal Drieberg,et al.  Multi-priority based QoS MAC protocol for wireless sensor networks , 2017, 2017 7th IEEE International Conference on System Engineering and Technology (ICSET).

[7]  Michael Schukat,et al.  Public key infrastructures and digital certificates for the Internet of things , 2015, 2015 26th Irish Signals and Systems Conference (ISSC).

[8]  David Cooper,et al.  Internet X.509 Public Key Infrastructure Certificate and Certificate Revocation List (CRL) Profile , 2008, RFC.

[9]  Muhammad Ali Ramdhani,et al.  Implementation of Automation System for Humidity Monitoring and Irrigation System , 2018 .

[10]  Mohd Javaid,et al.  A Review of the Role of Smart Wireless Medical Sensor Network in COVID-19 , 2020 .

[11]  G. V. Satyanarayana,et al.  Wireless Sensor Based Remote Monitoring System for Agriculture Using ZigBee and GPS , 2013 .

[12]  Zhenguo Chen,et al.  Trust Model of Wireless Sensor Networks and Its Application in Data Fusion , 2017, Sensors.

[13]  Laurence T. Yang,et al.  Cyberentity Security in the Internet of Things , 2013, Computer.

[14]  Ahto Buldas,et al.  Optimally Efficient Accountable Time-Stamping , 2000, Public Key Cryptography.

[15]  V. Uma Rani,et al.  Review of Trust Models in Wireless Sensor Networks , 2014 .

[16]  Dejan Rančić,et al.  Wireless Sensor Network in Agriculture: Model of Cyber Security , 2020, Sensors.

[17]  Mohsen Guizani,et al.  An Efficient Distributed Trust Model for Wireless Sensor Networks , 2015, IEEE Transactions on Parallel and Distributed Systems.

[18]  Mohammed Al-Shalabi COVID-19 Symptoms Monitoring Mechanism using Internet of Things and Wireless Sensor Networks , 2020 .

[19]  Ivan Vulic,et al.  Failure points in the PKI architecture , 2017 .

[20]  Guangjie Han,et al.  Management and applications of trust in Wireless Sensor Networks: A survey , 2014, J. Comput. Syst. Sci..

[21]  Micheal Drieberg,et al.  A QoS MAC protocol for prioritized data in energy harvesting wireless sensor networks , 2018, Comput. Networks.

[22]  Rahul M. Pethe Wireless Sensor Network for Industrial Applications , 2015 .

[23]  Jaime Lloret,et al.  Internet of things: where to be is to trust , 2012, EURASIP J. Wirel. Commun. Netw..

[24]  Gang Qu,et al.  A Privacy-Preserving Trust Model Based on Blockchain for VANETs , 2018, IEEE Access.

[25]  Selçuk Baktir,et al.  Implementing RSA for Wireless Sensor Nodes , 2019, Sensors.

[26]  Stevan Stankovski,et al.  Energy-Efficient Asynchronous QoS MAC Protocol for Wireless Sensor Networks , 2020, Wirel. Commun. Mob. Comput..

[27]  Yingli Zhu,et al.  Applications of wireless sensor network in the agriculture environment monitoring , 2011 .

[28]  P. Vanaja Ranjan,et al.  Critical Event based Multichannel Process Control Monitoring Using WSN for Industrial Applications , 2013 .

[29]  Wei Liu,et al.  Blockchain Trust Model for Malicious Node Detection in Wireless Sensor Networks , 2019, IEEE Access.

[30]  Jirapond Muangprathub,et al.  IoT and agriculture data analysis for smart farm , 2019, Comput. Electron. Agric..

[31]  Prasant Mohapatra,et al.  Trust Computations and Trust Dynamics in Mobile Adhoc Networks: A Survey , 2012, IEEE Communications Surveys & Tutorials.

[32]  Ivan Tot,et al.  A SURVEY OF PKI ARCHITECTURE , 2019 .

[33]  Juan Antonio Gómez Galán,et al.  An Efficient Wireless Sensor Network for Industrial Monitoring and Control , 2018, Sensors.

[34]  N. Abdul Rahim,et al.  Development of wireless sensor network for Harumanis Mango orchard's temperature, humidity and soil moisture monitoring , 2018, 2018 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE).

[35]  Heena Rathore,et al.  Sociopsychological trust model for Wireless Sensor Networks , 2016, J. Netw. Comput. Appl..

[36]  Hjalmar Wennerström Meteorological impact and transmission errors in outdoor wireless sensor networks , 2013 .

[37]  Ivan Vulic,et al.  Classification as an approach to public key infrastructure requirements analysis , 2019, IET Softw..

[38]  Rosdiadee Nordin,et al.  Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review , 2017, Sensors.

[39]  Huafeng Wu,et al.  Agent-based Trust Model in Wireless Sensor Networks , 2007, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007).

[40]  Lei Shu,et al.  BLTM: Beta and LQI Based Trust Model for Wireless Sensor Networks , 2019, IEEE Access.

[41]  Stevan Stankovski,et al.  WebGIS-based suitability evaluation system for Chinese table grape production , 2019, Comput. Electron. Agric..

[42]  Yavuz Ege,et al.  A new wireless asynchronous data communications module for industrial applications , 2013 .

[43]  Meiling Zhu,et al.  Energy-Aware Approaches for Energy Harvesting Powered Wireless Sensor Nodes , 2017, IEEE Sensors Journal.