In real-time scenarios, wireless sensor network (WSN) suffers from severe constraints such as restricted power supply, short communication range, less bandwidth availability, and small memory storage. Owing to these severe constraints, the time complexity, space complexity, and cost complexity of these networks are very high. Hence, deploying a real sensor network environment for the testing of a newly designed protocol is a Herculean task. To overcome this issue, instead of doing live implementation of such networks, simulation modelling is accepted as an alternative approach. This study provides a comprehensive study about existing network simulators along with their advantages and weaknesses. This study also presented a case study for a preferable simulation methodology, i.e. MATLAB/Simulink. Firstly, this case study highlights prominent features of MATLAB/Simulink. Secondly, simulation results of implementing AODV (Adhoc on Demand Vector Protocol) in terms of simulation runtime using four simulators net simulator-2 (NS-2), NS-3, OMNet++, and MATLAB is presented. Thirdly, survey of few very well-known clustering protocols in WSNs is done. This study will prove to be beneficial for researchers of this domain as it surveys the literature over the period 2008–2020 focusing on simulation tools and simulation metrics used by researchers to simulate WSNs.

Ubiquitous computing for remote monitoring is enabling the Internet of Things applications in diverse areas. The potential impact of wireless sensor networks in remote habitat and agricultural monitoring cannot be overemphasised. LoRa (long range) is particularly well suited to applications requiring low operational costs, long-range wireless communication technology, low data rates and low power consumption. For industrial and large-scale deployment of this promising technology, it must be both empirically and theoretically evaluated and proven. For network design purposes and optimised positioning of devices, the authors evaluated long range wireless area network (LoRaWAN) propagation in a tropical vegetative environment. Traditional vegetation propagation models have been compared with the measured data. The free space model best fits their data except for the tree canopy area where the loss was about 56 dB. The result can be used as empirical bases to develop an accurate model and simulation tool for LoRaWAN deployment planning.

The clustering technique is a key routing method for large-scale wireless sensor networks (WSNs), which strongly extends the network's lifetime and scalability. The fundamental protocol of this technique, which is called low energy adaptive clustering hierarchy (LEACH), is proved as a solution that offers good energy efficiency and consequently expands the network lifetime. As the energy efficiency is deteriorated with the network size, LEACH improvements are becoming so substantial to support the scalability in the large-scale WSNs. The authors propose a new dynamic multi-hop clustering protocol. It exploits both the mobility and the multi-hop communication to prolong the lifetime of the mobile WSN. The proposed protocol, called dynamic multi-hop LEACH (DMH-LEACH), combines the dynamic clustering, multi-hop transmissions, and node mobility to improve the energy efficiency of LEACH. They also study the effect of the traffic and energy heterogeneity on the proposed protocol. Finally, they simulate DMH-LEACH protocol for both homogeneous and heterogeneous scenarios. The simulation results show that the proposed protocol allows to better balance the energy consumption for all sensor nodes and considerably extends the network's lifetime.

Energy is the most important resource in the design of wireless sensor networks (WSNs); as a result, most of the research work was done on this topic. It has been proven that the mobility in this kind of network plays an important role in energy conservation. The movement of the Sink is the most interesting type of mobility. In this work, the authors optimise the Sink travel in sensor field using Hilbert curve as an efficient data collection trajectory. The sensor field is organised in clusters and a virtual rendezvous point (VRP) is selected at each cluster for the sojourn of the Sink. The optimal position of the VRP is obtained using their integer linear program which takes into account the optimal transmission range between the Sink and the sensor node. The obtained results showed the supremacy of the Hilbert curve compared to other curves generated by other optimisation approaches and confirm that the solution based on clustering and Hilbert curve has performed well in terms of energy gain.

Wireless sensors are utilised to transmit data through the wireless sensor network. The authors consider wireless sensors with a limited energy capacity that needs the energy to complete the transmission service. To extend the lifetime of the wireless sensor, it is assumed that the renewable energy resource, e.g. solar energy, is collected via the energy harvesting method. In order to provide a better bit error rate or data rate, the energy requirement of a packet may be more than one unit of energy. Furthermore, a packet may leave without finishing the service due to impatience if the patient interval is exceeded. They focus on one wireless sensor with one server and two finite queues: one packet queue and one energy queue. In the authors’ system, there are two classes of impatient customers, and each customer has to consume one or two units of energy to finish the service. First, they derive the analytical model for the considered system and find the steady-state probability distribution and performance measures of interest. Next, the impacts of different system parameters on the performance measures are studied. Last but not least, the analytical results are shown to be in good agreement with the simulation results.