Abstract
Wireless sensor networks (WSNs) have demonstrated research and developmental interests in numerous fields, like communication, agriculture, industry, smart health, monitoring, and surveillance. In the area of agriculture production, IoT-based WSN has been used to observe the yields condition and automate agriculture precision using various sensors. These sensors are deployed in the agricultural environment to improve production yields through intelligent farming decisions and obtain information regarding crops, plants, temperature measurement, humidity, and irrigation systems. However, sensors have limited resources concerning processing, energy, transmitting, and memory capabilities that can negatively impact agriculture production. Besides efficiency, the protection and security of these IoT-based agricultural sensors are also important from malicious adversaries. In this article, we proposed an IoT-based WSN framework as an application to smart agriculture comprising different design levels. Firstly, agricultural sensors capture relevant data and determine a set of cluster heads based on multi-criteria decision function. Additionally, the strength of the signals on the transmission links is measured while using signal to noise ratio (SNR) to achieve consistent and efficient data transmissions. Secondly, security is provided for data transmission from agricultural sensors towards base stations (BS) while using the recurrence of the linear congruential generator. The simulated results proved that the proposed framework significantly enhanced the communication performance as an average of 13.5% in the network throughput, 38.5% in the packets drop ratio, 13.5% in the network latency, 16% in the energy consumption, and 26% in the routing overheads for smart agriculture, as compared to other solutions.
Keywords
smart agriculture, cluster heads, energy efficiency, data security, signal strength
Introduction
In various domains, the technology of wireless sensor networks (WSN) [1–3] has been used in an efficient way to improve network performances. The main reason to uses different sensors in the environmental field due to their manageable and easy configuration setup [4–7]. Additionally, the sensor nodes operate autonomously and construct the network infrastructure in an ad-hoc manner. In such infrastructure, nodes have not a stable network topology and they can join the more suitable neighbor for data transmission based on some factors. The sensor nodes sense the observing data and forward towards BS with the help of some gateway and cluster heads. These cluster heads have the role of aggregating the received data packets and relay towards BS. The cluster heads effectively construct a single-hop or multi-hop path to BS and work as a focal point in entire data transmission. Furthermore, the cluster heads store the received data in its memory and follow the store and forward mechanism. The end-users access the centralized BS via the Internet or different web-based applications to retrieve the required observing data [8–11].
During data transmission, the deployed sensors can be static or mobile. The static sensors are also referred to as non-adaptive and their constructed routing tables are fixed. While on the other hand, the routing tables of mobile sensors are dynamic and frequently updated when any change incurs in the network topology. The static routing solutions are more secure when compared to dynamic routing; however, the solutions that are based on the static algorithms are not appropriate for large regions and network scalability [12,13]. In recent years, the technology of IoT has been merged a lot with other fields to improved communication in terms of network throughput, resource utilization, and load distribution [14–16]. In IoT, many physical objects are attached to convert the information while using the Internet. Moreover, the technology of WSN provides the foundation for IoT systems and supports in observing and forwarding the conditions for the physical environment [17–19]. Figure 1 illustrates the scenario for smart agriculture based on various sensors, sink nodes, BS, Internet, and users.
The drastic changes in climate negatively impact the agriculture eco-system causing heaving rains, droughts, floods, and abrupt weather conditions [20,21]. These changes are deriving threats to agriculture-related food security in the developing as well as the developed world. The climates related challenges that are faced by agriculture can be overcome by adopting smart agriculture using IoT devices, which can increase agriculture yields and productions. The use of sensors in agriculture has been introduced in the last few decades as an offline data collector [22–24]. The offline sensor infrastructure collects data and provides sufficient information for making good decisions to overcome future yields or for the next year crops, yet they are unable to provide data regarding frequent changes in the environment, threatening the agriculture yields.
This article is aimed at using state of the art IoT based sensor infrastructure to collect data from the environment and securely transfer the data to the BS for efficient decisions. In the proposed framework, wireless agriculture sensors are scattered in the agriculture land for extracting different information related to soil composition, like humidity, temperature, moisture levels, and water level finders. This information is securely transmitted to the cluster heads, which works as memory buffers or storages to forward data towards BS. Upon the reception of data by the BS securely, the BS can provide up to date information to users for an efficient decision with minimum time. The proposed framework offers an energy-efficient and reliable routing to automate agriculture productions with minimum farmer’s burden. The observing data of agricultural sensors are routed towards BS intelligently and securely, which improves the monitoring and productivity of the agricultural land. The simulated experiments for the proposed framework demonstrated outperformed results when compared to existing solutions that are based on different network parameters.
This article is outlined in multiple subsections: Section 2 provides the background work and problem statement, Section 3 explains the proposed framework, Section 4 shows the simulation setup and detailed of parameters, Section 5 provides the experimental results along with discussion, and Section 6 provides the conclusion and the future work in this domain.
Conclusion
The technology of wireless sensor networks performs a vital role in the development of the agriculture domain. This paper presents an energy-efficient and secure IoT based WSN framework for smart agriculture application. The main aim of the proposed framework is to appoint the more suitable cluster heads based on multi-criteria decision function. The decision is based on residual energy, distance to BS, and SNR factors. Additionally, the proposed framework is to adopt a single-hop paradigm for data transmission and decreases the chances of bottlenecks among agriculture sensors and BS. Our proposed framework presents an intelligent decision for data routing and decreases the ratio of energy consumption with improved data delivery performance in the agriculture field. Unlike most of the existing solutions, the proposed framework exploits a mechanism that is based on the SNR factor to determine the strength of signals and it achieves more stable network performance between agriculture sensors and BS. Moreover, the proposed framework offers secure data transmission from agriculture sensors towards BS based on secret keys while using the recurrence of the linear congruential generator. In future work, we aim to analyze the performance of the proposed framework in a mobile-based IoT network and Intelligent Transportation System (ITS).
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The Kavian Scientific Research Association (KSRA) is a non-profit research organization to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.
KSRA research association, as a non-profit research firm, is committed to providing research services in the field of knowledge. The main beneficiaries of this association are public or private knowledge-based companies, students, researchers, researchers, professors, universities, and industrial and semi-industrial centers around the world.
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FULL Paper PDF file:
An Energy-Efficient and Secure IoT-Based WSN Framework: An Application to Smart AgricultureBibliography
author
Year
2020
Title
An Energy Efficient and Secure IoT-Based WSN Framework: An Application to Smart Agriculture
Publish in
Sensors 2020, 20(7), 2081, Received: 9 March 2020 / Revised: 21 March 2020 / Accepted: 4 April 2020 / Published: 7 April 2020
Doi
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Nasim Gazerani was born in 1983 in Arak. She holds a Master's degree in Software Engineering from UM University of Malaysia.
Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.
Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.
