Energy Efficient Resource Allocation Algorithm for Agriculture IoT

The Wireless Sensor Network needs to become a dynamic and adaptive network to conserve energy stored in the wireless sensor network node battery. This dynamic and adaptive network sometimes are called SON (Self Organizing Network). Several SON concepts have been developed such as routing, clustering, intrusion detection, and other. Although several SON concepts already exist, however, there is no concept for SON in dynamic radio configuration. Therefore, the authors’ contribution to this field would be proposing a dynamic and adaptive Wireless Sensor Network node radio configuration. The significance of their work lies in the modelling of the SON network that builds based on our measurement in the real-world jungle environment. The authors propose input parameters such as SNR, the distance between the transmitter and receiver, and frequency as the static parameter. For adaptive parameters, we propose bandwidth, spreading factor, and its most important parameter such as power for data transmission. Using the Levenberg Marquardt Artificial Neural Network (LM-ANN) self-organise Network model, power reduction and optimisation from 20 dBm to 14.9 dBm for SNR 3, to 11.5 dBm for SNR 6, and to 12.9 dBm for SNR 9 all within a 100-m range can be achieved. With this result, the authors conclude that we can use LM-ANN for the wireless sensor network SON model in the jungle environment. 

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Levenberg Marquardt artificial neural network model for self‐organising networks implementation in wireless sensor network

Multiparameter optimization system with DCNN in precision agriculture for advanced irrigation planning and scheduling based on soil moisture estimation

In the recent days, the Internet of Things (IoT) has assumed a significant role in automized farming applications. The farmers can receive frequent information corresponding to the soil moisture, water used, humidity, temperature, moisture, etc., by utilizing actuators and sensor nodes. Various clustering techniques used in wireless sensor network (WSN) applications have achieved energy‐efficient results. However, IoT‐enabled smart farming (SF) applications require scalable networks and long‐distance communication. The existing clustering techniques cannot provide SF solutions, and work related to communication overhead, end‐to‐end delay, latency etc., has not been taken up exhaustively. Therefore, in this article, a cross‐layer‐based hybrid particle Swarm wild horse optimizer (PSWHO) and stable routing technique (CL‐HPWSR) is designed to minimize energy consumption, communication delay, latency etc. in SF applications. Initially, the network is designed to be Bi‐concentric Hexagons. The cross‐layer‐based optimal cluster head (CH) selection mechanism is designed using the hybrid optimization algorithm‐named PSWHO to mitigate excess energy consumption problems in WSN. While clustering, cross‐layer parameters from different layers such as physical, medium access control, and network are used to compute the probability of each sensor node. Moreover, the deep learning‐based routing algorithm extended deep golden eagle neural network (EDGENN) is introduced to explore the optimal route for transmitting the data. The performance of CL‐HPWSR is implemented in Matlab by focusing energy‐efficiency, computational‐efficiency and QoS‐efficiency factors. Finally, in comparison with state‐of‐the‐art‐based SF approaches such as CL‐IoT, FEEC‐IIR, BiHCLR, PSO‐ECHS, and PSO‐C, the CL‐HPWSR has performed better in terms of energy‐efficiency, QoS‐efficiency and computational‐efficiency.

CL‐HPWSR: Cross‐layer‐based energy efficient cluster head selection using hybrid particle swarm wild horse optimizer and stable routing in IoT‐enabled smart farming applications

Group of sensor nodes that are dedicated to perform sensing task is called Wireless Sensor Networks (WSN). Clustering is implemented to make WSN process for Precision Agriculture (PA), energy efficient. A routing protocol is what makes the process efficient. We have proposed a routing protocol with sleep/wake scheduling and VANET broadcasting. Our aim is to implement a protocol and to prove that it is efficient (in terms of energy consumption and throughput) on comparison and analysis with the existing protocols such as Z-Stable Election Protocol and Stable Election Protocol, is what we are

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Optimized zonal stable election protocol

Crop production is significantly decreasing due to inefficient agricultural practices, limited irrigation facilities and lack of technology. Economic conditions of developing countries force farmers to use traditional practices rather than adopting latest technologies which are capable of producing better yield. Practices like Precision Agriculture are being incorporated all over the world to help farmers to get better crop yield. Precision Agriculture is the concept of real-time observation of soil parameters like temperature, water content, moisture etc. In present work, Wireless Sensor Network (WSN) has been implemented to sense and store data of agricultural field. To increase the acceptance of this technology in agriculture, cost effective and energy efficient system is required. Modified Zonal Stable Election Protocol (M-ZSEP) which follows hybrid routing for heterogeneous networks has been realized for agricultural field. WSN collects data through real time monitoring and then transmit it to the Base Station (BS). Data received is then displayed at base station to achieve monitoring of various soil parameters for efficient use of resources. Result indicate that M-ZSEP outperforms traditional protocols in terms of throughput and stability period which in turn will increase the lifetime of nodes and further make proposed network energy efficient.

Energy Efficient WSN for Precision Agriculture – Using Modified Zonal Stable Election Protocol

Internet of Things(IoT) thought is growing in the past few years, and the range of IoT devices is increasing apace. With the advancement of wireless networks, the evolution of cutting-edge data analytics and the decline in the outlay of connected devices, there is a rise in cloud platform adoption, and the market is anticipated to evolve at a positive pace. LoRaWAN is the progressive evolved technology that is anticipated as it holds up a large sector of the billions of approximated IoT. This paper focuses on the network QoS by analyzing the signal quality and channel capacity on the different configuration settings of LoRa. The simulated result demonstrates the utmost combination to achieve maximum channel capacity, SNR, and minimum bit error rate irrespective of the spreading factor, code rate, and bandwidth. Result demonstrates that there are approx. 27.21% more nodes can be active at SF-7 concerning SF-12 and concludes that capacity deteriorates as the SF increases which further concludes that link quality is 27.1% averagely superior in SF-7 region that the SF-12.

Capacity Evaluation and Analysis of Long Range for IoT

The excessive enhance in the number of subscribers in the wireless cell network, due to which the Mobile Network Operators (MNOs) facing the immense issues in giving the high-level executives of the broadband utility.cyc Long-Term Evolution (LTE) has capable of encountering the user’s demands by giving a high level of data rate. The key performance indicators (KPIs) have been recorded and reform the network execution in request to give the high-grade utility and also to attain better resource usage. Accessibility is utilized to figure out the success ratio of the user equipment (UE) in penetrating the cell network. The accessibility is indicated as the possibility that user equipment (UE) will be apt to penetrate the cell network utility for a fixed time duration. In this paper, the ANN tool is used to find out the prediction accuracy level of the accessibility of the wireless cellular network. For this purpose, key performance indicators (KPIs) data are acquired from the real field measurement of approximately 50,000 BTS locations by the Nokia Network Pvt. Ltd., India.

Predicting the Accuracy of Accessibility of LTE Network Using ANN

In the present scenario, there are multiple results to demonstrated the pros of one or more relay nodes help in generating communication in a wireless network. But in experimental scenarios, all nodes do not take participate in every transmission of information; so, we required the number of protocols for partner selection of nodes for generating the proper cooperation. For a cooperative diversity merits, many protocols are needed to provide a transmitting scenario to each and every user nodes with their respective partners that help in decoding the user information with high-SNR probability. Consider that, due to the unwanted noise or disturbances user can not able to transmit the information to their desired destination nodes. So, for the proper transmission without any interferences, user nodes takes the help of ‘n’ other nodes (called relays).

Asmita Singh

Papers

Energy Efficient WSN for Precision Agriculture – Using Modified Zonal Stable Election Protocol

Capacity Evaluation and Analysis of Long Range for IoT

Predicting the Accuracy of Accessibility of LTE Network Using ANN

Partner Selection Based on Different Protocols in Cooperative Network by Using Nakagami-M Function