Sensor Network Simulator Research Articles

Experimental Design of Wireless Sensor Network Simulation Teaching Based on OBE Concept

In response to the problem that students cannot effectively master the theoretical knowledge of wireless sensor networks, this study proposes an outcome-based education (OBE) guided teaching method and designs a simulation experiment on wireless sensor networks using the NS3 simulation platform. In the experiment, access point (AP) and station (STA) nodes are set up to present different network environments, and the transmission layer protocols (TCP and UDP) are changed to analyze different network performance. Through the analysis of experimental results, students can gain a vivid understanding of the basic knowledge of wireless sensor networks and achieve the expected teaching goals. This teaching method helps improve students' understanding and application ability of wireless sensor network theory, and promotes their learning and research in related fields.

Image data visualization and communication system based on sensor network simulation and visual feature extraction

In the context of today's information explosion, how to extract useful information from a large amount of image data and convey it to users is a challenging problem. Therefore, this study aims to achieve effective communication of image data by constructing a sensor network simulation and utilizing visual feature extraction methods. The study constructed a sensor network simulation to simulate the working principle of a biosensor system, thereby achieving perception and understanding of image data, and automatically obtaining and processing information from input images. Research on the use of visual feature extraction methods to extract features that describe the content and structure of images, and apply them to the results obtained from sensor network simulation to accurately capture important information in image data. The research aims to convey the extracted feature information to users through visual means, and present the extracted feature information to users in an intuitive graphical form, in order to gain a more intuitive understanding of the meaning and features of image data, improve the ability to understand data and analyze results. By constructing a sensor network to simulate the perception process of image data and using visual feature extraction methods to extract key feature information, this article can effectively convey this information to users through visualization methods. This method provides a new solution for the field of image data visualization communication, which helps to improve the efficiency and accuracy of data communication.

A novel approach for an energy-efficient traffic monitoring system using wireless sensor network and CupCarbon simulator (V 5.0) for a smart city

A novel approach for an energy-efficient traffic monitoring system using wireless sensor network and CupCarbon simulator (V 5.0) for a smart city

A novel approach for an energy-efficient traffic monitoring system using wireless sensor network and CupCarbon simulator (V 5.0) for a smart city

A novel approach for an energy-efficient traffic monitoring system using wireless sensor network and CupCarbon simulator (V 5.0) for a smart city

Enhancing Quality of Service in WSN Through a Routing Algorithm Based on Self-Organizing Maps

Many scholars have focused their attention on Wireless Sensor Networks (WSN) within the last ten years. QoS control, Energy intake, MAC protocols, routing protocols, statistics aggregation, self-organizing net algorithms, Internet of Things (IoT), and so forth are among the research topics that have been thoroughly studied recently. Historically, the potential of artificial intelligence (AI) has not been fully realized due to constraints in data processing capabilities and energy efficiency. Nonetheless, the unique characteristics of neural networks can be harnessed for complex tasks, such as the role of travel advisors. This research aims to combine IoT and WSN technologies to enhance Quality of Service (QoS) parameters including reliability, energy, conservation, system scalability and response time. It provides an overview of the key components and techniques utilized in WSNs to achieve QoS. The objective of the proposed article is to compare the performance of two widely used route paradigms, Energy-Aware Routing and Directed Diffusion, with the proposed routing technique called Sensor Intelligence Routing (SIR). The foundation of Sensor Intelligence Routing (SIR) is the incorporation of neural networks into discrete sensor networks. WSN simulation, OLIMPO (an ad-hoc wireless sensor network simulator for optimal scada-applications) has been used in multiple simulations to examine how well neural networks perform within the system. The results obtained from every routing method have been compared and analyzed. The paper also aims at fostering the use of IoT-based synthetic intelligence techniques.

Collision Mitigation by Dolphin Ant Lion Optimizer Pre-Packet Scheduling Approach

A wireless sensor network (WSN) consists of distributed autonomous sensors deployed over a large geographical area. Wireless Sensor Networks (WSNs) are composed of large-scale sensors that are specifically assigned to do particular tasks, with a significant portion of these tasks involving reporting and monitoring activities. Nevertheless, because to the potential expansion of the network to several sensor nodes, the likelihood of collision is significantly increased. This research presents an innovative approach for conducting collision detection and mitigation in wireless sensor networks (WSN). The first step involves conducting a simulation of Wireless Sensor Networks (WSN), followed by the utilization of the Fractional Artificial Bee Colony (FABC) algorithm for the selection of cluster heads. In this context, the network-based parameter is derived by considering factors such as the Received Signal Strength Index (RSSI), priority level, delivery rate, and energy consumption. The Deep Recurrent Neural Network (DRNN) has been modified to suit the task of collision detection. The training of the deep recurrent neural network (DRNN) is conducted via the Lion Crow Search optimizer (LCSO). Following the completion of collision detection, the subsequent step involves the implementation of a collision mitigation process utilizing a pre-scheduling technique known as Dolphin Ant Lion Optimizer (Dolphin ALO). In this context, the evaluation of fitness encompasses many factors related to collision mitigation, including energy consumption, Sleep Index (SI), delivery rate, priority level, E-waste management, and E-save measures. The approach presented in this study demonstrated superior performance in terms of energy consumption, throughput, Packet Delivery Ratio (PDR), and collision detection rate. Specifically, it achieved the least energy consumption of 0.185, the greatest throughput of 0.815, the highest PDR of 0.815, and the highest collision detection rate of 0.930.

Technology Modules Providing Solutions for Agile Manufacturing

In this paper, we address the most pressing challenges faced by the manufacturing sector, particularly the manufacturing of small and medium-sized enterprises (SMEs), where the transition towards high-mix low-volume production and the availability of cost-effective solutions are crucial. To overcome these challenges, this paper presents 14 innovative solutions that can be utilized to support the introduction of agile manufacturing processes in SMEs. These solutions encompass a wide range of key technologies, including reconfigurable fixtures, low-cost automation for printed circuit board (PCB) assembly, computer-vision-based control, wireless sensor networks (WSNs) simulations, predictive maintenance based on Internet of Things (IoT), virtualization for operator training, intuitive robot programming using virtual reality (VR), autonomous trajectory generation, programming by demonstration for force-based tasks, on-line task allocation in human–robot collaboration (HRC), projector-based graphical user interface (GUI) for HRC, human safety in collaborative work cells, and integration of automated ground vehicles for intralogistics. All of these solutions were designed with the purpose of increasing agility in the manufacturing sector. They are designed to enable flexible and modular manufacturing systems that are easy to integrate and use while remaining cost-effective for SMEs. As such, they have a high potential to be implemented in the manufacturing industry. They can be used as standalone modules or combined to solve a more complicated task, and contribute to enhancing the agility, efficiency, and competitiveness of manufacturing companies. With their application tested in industrially relevant environments, the proposed solutions strive to ensure practical implementation and real-world impact. While this paper presents these solutions and gives an overview of their methodologies and evaluations, it does not go into their details. It provides summaries of comprehensive and multifaceted solutions to tackle the evolving needs and demands of the manufacturing sector, empowering SMEs to thrive in a dynamic and competitive market landscape.

Optimized Low-Powered Wide Area Network within Internet of Things

The Internet of Things (IoT) is rapidly becoming an integral part of everyday life. LPWANs have been introduced to support the billions of internet-connected devices and the data they produce. LPWANs are capable of providing reliable connectivity even in low-density areas and devices consuming a low amount of energy. The exponential increase in the use of IoT applications across the globe will continue to generate more and more data traffic within the IoT network. Hence, it will increase device battery usage that may reduce the battery life expectancy limits. Thus, End Devices (EDs) within the IoT network in the near future will rise up to billions of devices operating in public, industry, and personal networks, generating a necessity for more correct and reliable energy conservation technology. This prompted the research work on an optimized low-powered wide area network within IoT. This paper focuses on three different strategies: LoRa power consumption model design, simulation of IoT wireless sensor networks, and implementation of SF allocation across the wireless sensor network and results analysis. The experiment has been carried out in various stages: firstly running a simulation over a wireless sensor network without optimization using MATLAB Simulink and obtaining the following result of 6.3997e-17 joules power consumption. Secondly, the authors test the network with power optimization using particle swarm optimization algorithms and obtained a better result of 2.5230e-17 joules. The LoRa energy consumption is reduced by 60%. Lastly, different simulation tests of LoRaWAN protocols with respect to throughput, packet loss, delay, data transmission, buffer size, and network density. The results presented on the graph showed that the proposed model outperforms the existing models. Hence, appropriate spreading factor allocation has increased the power efficiency of LoRa end device battery.

Development of a wireless sensor network simulator using energy-efficient traffic routing methods

This document represents possible algorithms and methods for the analysis, optimization, and control of wireless sensor networks. The main goal of the work is to find the optimal implementation of the particle swarm optimization method for solving the problem of improving the energy consumption of such networks. The result of the work is a software package for simulating WSN (Wireless sensor network) networks using all the methods of routing and optimization of WSN networks presented in the work. The usage of a combination of routing schemes and different systems of device state management raises the wireless sensor network lifetime and reduces the power consumption of the network. The developed and presented in the work network simulator allows any developer to design and test different network topologies with various network parameters. Such software will make it easy to design such networks both for large enterprises and independent developers.

Quad-Interleaving Routing Algorithm for Performance Enhancement of Oil and Gas Pipeline Network Monitoring

The pipeline is one of the main modes oftransportation for the oil and gas industry that could be laid offshore and onshore. Pipeline transportation requires close monitoring as a failure in pipelines causes disruption of supply, loss of precious commodities and not to mention irreversible environmental damage will be an essential topic. The major issue in AODV and DSDV is when the network gets more extensive, which causes high packet traffic resulting in high packet loss, energy consumption and passive nodes. This research aims to establish a routing algorithm with better performance focusing on throughput, fairness index, delivery ratio and passive nodes and energy consumption. The study is confined to wireless sensor network simulation on Network Simulator Tool. A technique of quad-interleaving Ad-hoc On- demand Distance Vector (QAODV) routing algorithm has been developed where predefined Alpha, Beta, Charlie and Delta nodes will communicate with the nodes which belong to their family. The results of the developed routing protocol have been compared with standard AODV, DSDV and OLSR routing protocols. The developed routing algorithm has produced a massive improvement in the delivery ratio (25% more), throughput (44% more), passive nodes (71 less), fairness index (0.06 more) and energy consumption (0.22J less).

Enhancing the radar system simulator tool suite to allow the simulation of sensor networks

The number of human-made objects orbiting the Earth is growing steadily. This trend is further accelerating during recent years due to increasing commercialization in the field of satellite operations and an increasing launch rate. Concerning the area of space surveillance and tracking (SST), this leads to higher demands with respect to object observation capabilities. In order to ensure the safe usability of the different Earth orbits for all spacecraft operators, it is of great importance to continuously observe and catalog as many of the human-made objects as possible. This is especially true for inactive and uncontrollable objects, i.e. space debris. Only by maintaining accurate catalogs of the space debris environment, involuntary collisions can be avoided and risks of losing a spacecraft kept low. While the number of space debris objects can only be expected to further increase, it is not trivial to increase the number of observation sites, such as telescopes and radars, or their capabilities to counter this. One way to increase the observation capabilities without constructing new observation sites is to search for possibilities to improve the efficiency with which the existing sensors observe objects.With the goal to study and analyze single sensors, sensor networks, and how they can be used in the most efficient way, a sensor network simulator tool suite has been developed at the Institute of Space Systems of the Technical University of Braunschweig. Originally, the tool suite was developed as a radar system simulator concentrating on the different radar system configurations, such as reflector antennas or phased arrays that are used in a mono- or bistatic mode. Additionally, the corresponding radar performance model is able to simulate a tracking as well as a scanning mode. Building upon this tool suite, it is now extended to include an optical performance model and the possibility to simulate not only ground-based but also space-based sensors. Within this work, the preliminary results obtained with the newly implemented optical performance model are shown.Using the enhanced version of this sensor network simulator tool suite, thorough analyses can now be made using the radar and optical performance models. Sensor networks consisting of radars and telescopes being both ground- or space-based can be studied in different configurations. Thereby, different aspects, such as observation strategies, sensor tasking, or choosing the right location and sensor to reach a certain goal can be investigated.

ZigBee-Based Wireless Sensor Network Topology Design and Comparison in Residential Areas

When designing a wireless sensor network based on ZigBee, it is very important to choose the right network topology, especially in networks with many nodes such as residential areas. Choosing the wrong topology will have an impact on the performance of the wireless sensor network as a whole because it will cause a large delay value. To overcome this, in this study a ZigBee-based wireless sensor network simulation was carried out using an environmental model consisting of several residential units, with one ZigBee device for each house. In addition, three ZigBee network topologies namely mesh, star, and tree are used in this simulation. This is done to determine which topology model will work best in a residential environment. The housing used for the simulation in this study is Citraland Waterfront City Housing which is located in Palu City, Central Sulawesi Province, Indonesia. By using simulations in the Opnet Modeler 14.5 application, it is known that the star topology on the ZigBee network is suitable for application in residential areas with a large number of nodes. This can be seen from the highest throughput values and the lowest media access delay, end-to-end delay, hop number, and packet dropped values compared to tree and mesh topologies.

Traffic Clearance for Ambulance during Pandemic Situation and Road Accidents using LORAWAN Network

Intelligent Transportation System (ITS) plays an important role in handling pandemic situation and disaster management. Due to rapid urbanization, there is a requirement for implementing an effective traffic control system not only to avoid heavy congestion but also to make a better solution for ambulance clearance which would help to save the human life. The proposed work intends to implement an effective traffic control system using Long-Range Wide Area Network (LoRaWAN) that provides seamless traffic clearance for ambulances, so that they reach the hospitals without any delay. Cupcarbon, a Wireless Sensor Network (WSN) simulator, is used to evaluate the performance of the proposed work. The simulation involves a case study considering an accident zone in Coimbatore city and the performance of the proposed system is compared with that of existing systems. The simulation results prove that LoRaWAN can be used to effectively control the traffic lights with a wider coverage range, as compared to existing systems.

State of the Art Systematic Literature Review on Selection of Top Ten WSN Simulators – Part A

The proliferation of technology has led to numerous advancements in various fields, including the field of simulation. Simulators, in particular, have proven to be a valuable tool for researchers and students as they eliminate the need for physical hardware, reduce costs, and increase accessibility for conducting experiments. One of the most significant innovations in this realm is the use of simulators, which are specially designed software programs that mimic real-world scenarios. However, with hundreds of simulators available for various fields, the selection of the appropriate one can be a daunting task. This work presents a systematic literature review on wireless sensor network (WSN) simulators and their selection methodology. A total of 31 literature works since 2016 were reviewed, with the majority of the works conducted in the past 4 years. The study found 52 unique simulators studied about 182 times with repetitive sets in different literatures. Most of the works presented basic and general information about the simulators which does not assist readers in selecting the appropriate and best suitable simulator for their work. Additionally, about 55% of the works did not define any selection criteria or present comparisons among the studied simulators. The majority of literature work either selected simulators based on their frequency of appearance in their studied literature subset or based on their popularity. The results of this study can aid researchers in selecting the appropriate WSN simulator for their experimental work.

Virtual Infrastructure based Routing Algorithm for IoT enabled Wireless Sensor Networks with Mobile Gateway

The IoT technology is seeking the attention of industry and researcher day by day due to its large number of applications and is off monitoring and controlling the object from the remote location. The very basic and important element of IoT is wireless sensor network where sensor nodes are attached with the object and generates the sensory data related to the object an actuator can provide the movement to the object. To make it a success reliable and efficient communication model is the main requirement. To fulfil the objective related to IoT application success in this paper a communication protocol called virtual infrastructure based routing algorithm is proposed. In this proposal a virtual cross region structure is formed in the central of the sensor network, which is called meeting region. In this meeting region the sensor nodes send their generated data and the gateway node receives those data. The problem of energy hole, the mobile gateway node is considered in this proposal. The proposed algorithm is implemented using the standard wireless sensor network simulator tool and compared the performance of the proposed algorithm with the existing algorithm based on some standard performance metrics. The simulation outcome exhibits that the proposed algorithm outperformed the existing algorithms in different performance metrics.

Virtual Infrastructure based Routing Algorithm for IoT enabled Wireless Sensor Networks with Mobile Gateway

The IoT technology is seeking the attention of industry and researcher day by day due to its large number of applications and is off monitoring and controlling the object from the remote location. The very basic and important element of IoT is wireless sensor network where sensor nodes are attached with the object and generates the sensory data related to the object an actuator can provide the movement to the object. To make it a success reliable and efficient communication model is the main requirement. To fulfil the objective related to IoT application success in this paper a communication protocol called virtual infrastructure based routing algorithm is proposed. In this proposal a virtual cross region structure is formed in the central of the sensor network, which is called meeting region. In this meeting region the sensor nodes send their generated data and the gateway node receives those data. The problem of energy hole, the mobile gateway node is considered in this proposal. The proposed algorithm is implemented using the standard wireless sensor network simulator tool and compared the performance of the proposed algorithm with the existing algorithm based on some standard performance metrics. The simulation outcome exhibits that the proposed algorithm outperformed the existing algorithms in different performance metrics.

Node Dynamic Localization and Prediction Algorithm for Internet of Underwater Things

This article investigates the underwater node dynamic localization and prediction problems in a dynamic sensor network. Node localization in the Internet of underwater things is the basis of target tracking and ocean monitoring. At present, most of the node location algorithms assume calm sea and fixed node location. However, the current velocity is uncertain in space and time. The nodes are drifted with the current motion. Therefore, most of the localization algorithms lose efficacy in the actual marine environment. In order to solve the above problems, a node dynamic prediction algorithm is proposed. First, the node mobility model is improved, which is more suitable for the actual marine environment. Second, a frequency-based anchor node prediction algorithm is designed to improve anchor node location accuracy. Third, when the ordinary node receives the signals sent by anchor nodes of different depths, a deep information-based weighted fusion method is designed for the ordinary node localization in order to mine more information in each direction. Finally, location and prediction simulation in sensor networks is carried out. The results show that the proposed node localization and prediction algorithm is more accurate than SMLP and high-precision localization with mobility prediction algorithms and prove the enhanced effect of our method in dynamic marine.

Study of the Impact of Various Objective Functions on the Heterogeneous Wireless Sensor Networks

The Internet of Things has known a rapidly vast implementation. For that reason, many studies have tended to focus on the area of Routing Protocol for Low-Power and Lossy Networks that specified as an IPv6 routing protocol for wireless sensor networks. These studies aim to evaluate various networking characteristics such as communication quality and energy consumption. According to the uniformity of energy assignment for sensor nodes, WSNs can be divided into two categories: homogeneous and heterogeneous networks. However, almost all of the existing research papers deal with the homogeneous class. In this paper, we provide a comprehensive study for the performance of the two comparative objective functions used in RPL: MRHOF and OF0 for the heterogeneous WSN. This study helps to deduce which objective function is the most effective to assure good functioning of RPL in heterogeneous environment. Simulations were done using the Cooja simulator in Contiki operating system, as it is the widely used framework for WSNs that can support simulation of heterogeneous sensor networks. The work also analyzes various parameters: energy consumption, latency, PDR and control traffic overhead (DAO, DIO, DIS and DAO-ACK). The selected metrics taken into consideration are Energy, ETX and HC. The results show that MRHOF acts better than the OF in regard to all parameters except for Control Traffic Overhead.

Designing a Virtual Platform for Modeling Nodes in Wireless Sensor Networks at the Central Processing Unit Level

Wireless sensor network simulation programs provide representation for an actual system, without needing to deploy real testbed which is highly constrained by the available budget, and the direct operations inside physical layer in most of these programs are hidden and work implicitly. This is what motivated us to build a kernel for a virtual simulation platform to be able to simulate protocol operations and algorithms at the node processing unit level, The proposed system aims to observe the execution of operations at the low level of the wireless sensor physical infrastructure with the ability to modify at this level. That give the improvers of wireless sensor nodes the ability to test their ideas without needing to use physical environment. We have built the functionality operations which are related to the platform kernel at several stages. We defined (as a first step) the essential operations inside a virtual microprocessor that uses a partial set pf MIPS instructions, and built the kernel of minimized virtual WSN simulator depending on the proposed microprocessor, that means we can add any number of nodes inside the GUI of the WSN simulator kernel, and these nodes use the proposed virtual microprocessor . Then we improved this platform by adding the instruction set of a real microprocessor that is used in wireless sensor network nodes. Finally, (and to ease and simplify the interaction operation between program GUI of the platform kernel and the user), we have built simplified compiler that allows user to deal with microprocessor GUI inside each node, and to clarify protocol and algorithm operations by a set of orders and functions without needing to deal with low level language (Assembly language) in a direct way. The simulation results have presented high flexibility and performance to this platform in observing the operation sequence inside wireless sensor nodes at assembly level, in addition to focus on some parameters that are related to microprocessor inside each node.

Quantifying the Robustness of Complex Networks with Heterogeneous Nodes

The robustness of a complex network measures its ability to withstand random or targeted attacks. Most network robustness measures operate under the assumption that the nodes in a network are homogeneous and abstract. However, most real-world networks consist of nodes that are heterogeneous in nature. In this work, we propose a robustness measure called fitness-incorporated average network efficiency, that attempts to capture the heterogeneity of nodes using the ‘fitness’ of nodes in measuring the robustness of a network. Further, we adopt the same measure to compare the robustness of networks with heterogeneous nodes under varying topologies, such as the scale-free topology or the Erdős–Rényi random topology. We apply the proposed robustness measure using a wireless sensor network simulator to show that it can be effectively used to measure the robustness of a network using a topological approach. We also apply the proposed robustness measure to two real-world networks; namely the CO2 exchange network and an air traffic network. We conclude that with the proposed measure, not only the topological structure, but also the fitness function and the fitness distribution among nodes, should be considered in evaluating the robustness of a complex network.