Wireless Sensor Network Simulation Research Articles

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

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.

An Enhanced Flower Pollination Algorithm with Gaussian Perturbation for Node Location of a WSN.

Localization is one of the essential problems in internet of things (IoT) and wireless sensor network (WSN) applications. However, most traditional range-free localization algorithms cannot fulfill the practical demand for high localization accuracy. Therefore, a localization algorithm based on an enhanced flower pollination algorithm (FPA) with Gaussian perturbation (EFPA-G) and the DV-Hop method is proposed.FPA is widely applied, but premature convergence still cannot be avoided. How to balance its global exploration and local exploitation capabilities still remains an outstanding problem. Therefore, the following improvement schemes are introduced. A search strategy based on Gaussian perturbation is proposed to solve the imbalance between the global exploration and local exploitation search capabilities. Meanwhile, to fully exploit the variability of population information, an enhanced strategy is proposed based on optimal individual and Lévy flight. Finally, in the experiments with 26 benchmark functions and WSN simulations, the former verifies that the proposed algorithm outperforms other state-of-the-art algorithms in terms of convergence and search capability. In the simulation experiment, the best value for the normalized mean squared error obtained by the most advanced algorithm, RACS, is 20.2650%, and the best value for the mean distance error is 5.07E+00. However, EFPA-G reached 19.5182% and 4.88E+00, respectively. It is superior to existing algorithms in terms of positioning, accuracy, and robustness.

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.

Linguistic Fuzzy Trust Model over Oscillating Wireless Sensor Networks

Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Networks (BTRM-WSN) in terms of the accuracy and the average path length suggested by each model is presented. Both models give quite good and accurate outcomes over oscillating WSNs. Also it must be mentioned that the evaluation environment used here is Trust and Reputation Model Simulator for WSN.

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).

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.
                

IoT-Enabled Precision Agriculture: Developing an Ecosystem for Optimized Crop Management

The Internet of Things (IoT) has the potential to revolutionize agriculture by providing real-time data on crop and livestock conditions. This study aims to evaluate the performance scalability of wireless sensor networks (WSNs) in agriculture, specifically in two scenarios: monitoring olive tree farms and stables for horse training. The study proposes a new classification approach of IoT in agriculture based on several factors and introduces performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The study utilizes COOJA, a realistic WSN simulator, to model and simulate the performance of the 6LowPAN and Routing protocol for low-power and lossy networks (RPL) in the two farming scenarios. The simulation settings for both fixed and mobile nodes are shared, with the main difference being node mobility. The study characterizes different aspects of the performance requirements in the two farming scenarios by comparing the average power consumption, radio duty cycle, and sensor network graph connectivity degrees. A new approach is proposed to model and simulate moving animals within the COOJA simulator, adopting the random waypoint model (RWP) to represent horse movements. The results show the advantages of using the RPL protocol for routing in mobile and fixed sensor networks, which supports dynamic topologies and improves the overall network performance. The proposed framework is experimentally validated and tested through simulation, demonstrating the suitability of the proposed framework for both fixed and mobile scenarios, providing efficient communication performance and low latency. The results have several practical implications for precision agriculture by providing an efficient monitoring and management solution for agricultural and livestock farms. Overall, this study provides a comprehensive evaluation of the performance scalability of WSNs in the agriculture sector, offering a new classification approach and performance assessment metrics for stationary and mobile scenarios in 6LowPAN networks. The results demonstrate the suitability of the proposed framework for precision agriculture, providing efficient communication performance and low latency.

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.

Design of WSN Model with NS2 for Animal Tracking and Monitoring

Tracking and monitoring wild life is a significant ecological issue that cannot be overlooked. Especially getting fundamental indications of wild animal like Tigers is critical and evaluating their wellbeing without harming their habitat is another important task and recording their vital signs by sedating causes stress and injuries in animal. This paper proposes a design of wireless based tracking and health monitoring system for Tigers using WSN and Network simulator 2. The important physiological parameters like temperature of heart beat rate, sound signal, respiration rate, accelerometer signal and GPS data is transmitted and monitored through wireless sensor network (WSN).A sensor network is composed of different sensors which remotely communicate with each other and the information of each node are separated. Each node has ability to communicate among each other or to a specific node to communicate with sink node A Network simulator which acts as simulation tool for network of sensor nodes in tracking and monitoring system is employed to simulate the location and health of tigers. This system empowers veterinarians and forest guards to precisely and accurately take an animal's vital signs and analyses the health and location. We analyze the performance of simulation model by using metrics, such as average throughput of all nodes, end to end delay, packet received, packet dropped and packet delivery ratio (PDR), average good put and energy model.

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.

Survey and Comparative Study of LoRa-Enabled Simulators for Internet of Things and Wireless Sensor Networks.

The Internet of Things (IoT) is one of the most important emerging technologies, spanning a myriad of possible applications, especially with the increasing number and variety of connected devices. Several network simulation tools have been developed with widely varying focuses and used in many research fields. Thus, it is critical to simulate the work of such systems and applications before actual deployment. This paper explores the landscape of available IoT and wireless sensor networks (WSNs) simulators and compares their performance using the Low Power Wide Area Network (LPWAN) communication technology called LoRa (Long Range), which has recently gained a lot of interest. Using a systematic approach, we present a chronological survey of available IoT and WSNs simulation tools. With this, we categorized and content-analyzed published scientific papers in the IoT and WSNs simulation tools research domain by highlighting the simulation tools, study type, scope of study and performance measures of the studies. Next, we present an overview of LoRa/LoRaWAN technology by considering its architecture, transmission parameters, device classes and available simulation tools. Furthermore, we discussed three popular open-source simulation tools/frameworks, namely, NS-3, OMNeT++ (FLoRa) and LoRaSim, for the simulation of LoRa/LoRaWAN networks. Finally, we evaluate their performance in terms of Packet Delivery Ratio (PDR), CPU utilization, memory usage, execution time and the number of collisions.

Hybrid optimization driven deep residual network for attack detection and attack mitigation in wireless sensor networks

Wireless sensor network (WSN) comprises small sensor nodes that have the ability of sensing platform, store and send data. In addition, the sensor nodes pose limited resource such as energy, computing power. Clustering is an effective manner for diminishing energy usage utilized by sensor nodes for sending data from source to base station (BS). The multi-path routing is utilized for routing data amongst nodes. However, the WSN are susceptible to several types of security issues which can degrade network performance. WSN are susceptible to various types of attacks, which degraded the performance of entire network. Hence, the primary purpose of this research is to design and develop attack detection and attack mitigation system in WSN for detecting the attackers. This paper devises an energy efficient and optimization aware deep model for attack detection and mitigation in WSN. Here, the first step is the simulation of WSN nodes. The overall procedure of the proposed model includes simulation of WSN, cluster head selection, routing to BS, Sybil attack detection in BS and finally attack mitigation in BS. The first step is WSN simulation and then the selection of energy efficient cluster head is done using Lower Energy Adaptive Clustering Hierarchy (LEACH) protocol.

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.

Improved Routing Algorithm in IoT Network by TOPSIS method.

Low energy utilization and reliability in packet transmission are factors that seriously affect the performance of Wireless Sensor Network (WSN) and Quality of Service (QoS) in general. Regarding routing strategy, the efficient forwarding methods can cause more throughput, less packet loss with less energy usage. To this purpose multi-attribute, decision-making (MADM) methods are proposed in hop-by-hop sending data scenarios, as the most efficient methods in selecting the reliable path towards the sink node. In such a decision-making environment, various routing metrics are taken into account. This paper compares Wise Route routing protocol and modified-Wise Route (MwiseRoute) by TOPSIS with indexes (signal to noise ratio, residual energy, distance from the node, farness from the sink node) balances by self-sets weights (0.3, 0.5, 0.1,0.1) respectively. The evaluation has been tested on Mixim 3.2 in Omnet++.4.6. The result shows MwiseRoute with TOPSIS is more appropriate in gaining more throughput and significantly decreases packet drop in mac by less power drain. References Aziz, L. and Aznaoui, H. (2020) 'Efficient Routing Approach Using a Collaborative Strategy', Journal of Sensors, 2020, pp. 2547061. doi: 10.1155/2020/2547061 Foubert, B. and Mitton, N. (2021) 'RODENT: a flexible TOPSIS based routing protocol for multi-technology devices in wireless sensor networks', ITU Journal on Future and Evolving Technologies, 2(1). doi. Available at: https://hal.inria.fr/hal-03165426 Ghafoor, K. Z., Kong, L., Sadiq, A. S., Doukha, Z. and Shareef, F. M. 'Trust-aware routing protocol for mobile crowdsensing environments'. IEEE INFOCOM 2018 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 15-19 April 2018, 82-87. Hajji, F. E., Leghris, C. and Douzi, K. (2018) 'Adaptive Routing Protocol for Lifetime Maximization in Multi-Constraint Wireless Sensor Networks', Journal of Communications and Information Networks, 3(1), pp. 67-83. doi: 10.1007/s41650-018-0008-3 Kamble, A. and Patil, B. ( 2020) 'Selection of Cluster Head Techniques in WSN: A Review', 2nd International Conference on IoT, Social, Mobile, Analytics & Cloud in Computational Vision & Bio-Engineering (ISMAC-CVB 2020), 3, pp. 7. doi: http://dx.doi.org/10.2139/ssrn.3734304 Karami, A. 'UTILIZATION AND COMPARISON OF MULTI ATTRIBUTE DECISION MAKING TECHNIQUES TO RANK BAYESIAN NETWORK OPTIONS Master Degree Project in Informatics One year Level ECTS 30 Spring term Year 2011'. Kaur, L. and Malhotra, J. (2015) 'Comparison of Wise Route and Flooding Network Type of Convergecast Routing in Wireless Sensor Network', International Journal of Sensor and Its Applications for Control Systems, 3, pp. 1-10. doi: 10.14257/ijsacs.2015.3.2.01 Kazmi, S., Liscano, R. and Ren, J. (2014) 'Determining Fuzzy Link Quality Membership Functions in Wireless Sensor Networks', Procedia Computer Science, 34, pp. 149-156. doi: https://doi.org/10.1016/j.procs.2014.07.073 Khan, B. M., Bilal, R. and Young, R. (2018) 'Fuzzy-TOPSIS based Cluster Head selection in mobile wireless sensor networks', Journal of Electrical Systems and Information Technology, 5(3), pp. 928-943. doi: https://doi.org/10.1016/j.jesit.2016.12.004 Kim, B.-S., Kim, K.-I., Chang, G., Kim, K. H., Roh, B. and Ham, J.-H. (2019a) 'Comprehensive Survey on Multi Attribute Decision Making Methods for Wireless Ad Hoc Networks', 2019, 20(5), pp. 14. doi. Available at: https://jit.ndhu.edu.tw/article/view/2139 Kim, B., Kim, K.-I., Chang, G., Kim, K. H., Roh, B. and Ham, J. (2019b) 'Comprehensive Survey on Multi Attribute Decision Making Methods for Wireless Ad Hoc Networks', Journal of Internet Technology, 20, pp. 1575-1588. doi: Kodali, R. K. and Malothu, V. K. 'MIXIM framework simulation of WSN with QoS'. 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), 25-27 May 2016, 128-131. Odu, G. O. (2019) 'Weighting methods for multi-criteria decision making technique', 23 No. 8 (2019). doi: 10.4314/jasem.v23i8.7 Shelebaf, A. and Tabatabaei, S. (2020) 'A Novel Method for Clustering in WSNs via TOPSIS Multi-criteria Decision-Making Algorithm', Wireless Personal Communications, 112(2), pp. 985-1001. doi: 10.1007/s11277-020-07087-7 Smolka, T. a. s. (2011) 'MiXiM Tutorial', pp. 8. doi: Temur, G. T. (2016) 'A novel multi attribute decision making approach for location decision under high uncertainty', Applied Soft Computing, 40, pp. 674-682. doi: https://doi.org/10.1016/j.asoc.2015.12.027 Varga, A. and Hornig, R. (2008) An overview of the OMNeT++ simulation environment.

Intrusion Detection Algorithm and Simulation of Wireless Sensor Network under Internet Environment

As an effective security protection technology, intrusion detection technology has been widely used in traditional wireless sensor network environments. With the rapid development of wireless sensor network technology and wireless sensor network applications, the wireless sensor network data traffic also grows rapidly, and various kinds of viruses and attacks appear. Based on the temporal correlation characteristics of the intrusion detection dataset, we propose a multicorrelation-based intrusion detection model for long- and short-term memory wireless sensor networks. The model selects the optimal feature subset through the information gain feature selection module, converts the feature subset into a TAM matrix using the multicorrelation analysis algorithm, and inputs the TAM matrix into the long- and short-term memory wireless sensor network module for training and testing. Aiming at the problems of low detection accuracy and high false alarm rate of traditional machine learning-based wireless sensor network intrusion detection models in the intrusion detection process, a wireless sensor network intrusion detection model combining two-way long- and short-term memory wireless sensor network and C5.0 classifier is proposed. The model first uses the hidden layer of the bidirectional long- and short-term memory wireless sensor network to extract the features of the intrusion detection data set and finally inputs extracted features into the C5.0 classifier for training and classification. In order to illustrate the applicability of the model, the experiment selects three different data sets as the experimental data sets and conducts simulation performance analysis through simulation experiments. Experimental results show that the model had better classification performance.