Wireless Sensor Network Simulation Research Articles

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.

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.

Research on time synchronization of linear pulse-coupled oscillators model with delay in nearest neighbor wireless multi-hop networks

Time synchronicity works as a popular requirement in wireless sensor networks. Pulse-coupled oscillators similar to firefly flashing and synchronization via discrete pulse coupling are widely used in wireless sensor networks. In this article, we have studied the time synchronization with communication delay in the nearest neighbor network of distributed sensors, based on the pulse-coupled oscillators model of synchronicity achieved by biological systems. First, we present a linear pulse-coupled oscillators model with coupling delay and the model is used to analyze the wireless sensor networks synchronization with communication delay. Second, we mathematically analyze the firing behaviors in the linear pulse-coupled oscillators network using the delayed excitatory coupling and track the synchronization process of the two and multi-oscillators and obtain the synchronization conditions from the regression mapping. Finally, through the proposed model implementation in the wireless sensor networks simulation framework, we demonstrate that the multi-oscillators system can be synchronized from a random starting stage distribution under linear phase responding functions and the nearest neighbor communication. The results show that our approach can achieve clock synchronization in wireless sensor networks with delayed nearest neighbor communication.

WITHDRAWN: First wave of covid-19 in India using IoT for identification of virus

Internet of Things (IoT) are evolving rapidly and making it possible for many uses, such as manufacturing, military, education and health, to link different intelligent objects. Coronavirus has recently spread widely around the globe and no effective therapies are currently available. It is also very necessary to avoid infection and to control the symptoms, such as fever and shortness of breath. As Coronavirus is a disease that is circulating very rapidly and the social distancing to deter an outbreak is very significant, it is essential to provide a system that is intelligent enough to monitor the effects of individuals with little direct contact. This document contains an IoT-based and wireless sensor network architecture and simulation of the COVID-19 Monitoring Mechanism (CSMM) for the monitoring of people in their quarantine, particularly the elderly who are living under chronic diseases and immune failure, and are therefore more likely to contract severe diseases. The mechanism relies on patient health data remotely. A doctor or care practitioner may carry out the monitoring process. For starters, where there is high fire or trouble breathing, this can conveniently be used for a detected urgent or irregular situation. The process will then give a warning to the health care provider or practitioner, sending urgent SMS with time and condition to act without any delays to save the patient's life.

Parallel sine cosine algorithm for the dynamic deployment in wireless sensor networks

All along, people have a high enthusiasm for the research of optimization algorithm. A large number of new algorithms and methods have emerged. The sine cosine algorithm (SCA) is an excellent algorithm that has appeared in recent years. It is a stochastic optimization algorithm based on population. Compared with the existing algorithms, SCA is a suitable solution to different optimization problems, especially the optimization of unimodal functions. It is qualified to optimize real-world problems with unknown and limited search space. But sometimes it does not perform satisfactorily when dealing with some specific problems, such as optimization of multimodal functions or composite functions. This paper presents a parallel version of the sine cosine algorithm (PSCA) with three communication strategies. Different strategies can be selected according to the type of optimization function to achieve better results. We have repeatedly tested different types of functions, and the results show that the proposed PSCA can solve the optimization problem more specifically. In the simulation of wireless sensor network (WSN) dynamic deployment optimization, it is found that using this method can get the ideal sensor node distribution, which makes PSCA’s performance in solving other practical problems worth looking forward to.

Wireless Sensor Networks Simulation Model to Compute Verification Time in Terms of Groups for Massive Crowd

Wireless Sensor Networks Simulation Model to Compute Verification Time in Terms of Groups for Massive Crowd

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.

Software-in-Loop Simulation Environment for Electromagnetic Underwater Wireless Sensor Networks over STANAG 5066 Protocol

In this work, the development of a software-in-loop platform to carry out Underwater Wireless Sensor Network (UWSN) simulations using a real-time STANAG 5066 stack is presented. The used protocol stack is part of a real-world implementation of an underwater wireless node based on ElectroMagnetic (EM) Underwater Radio Frequency Communication (EM-URFC), framed within Spanish Government’s project HERAKLES. The main objective of this work was to assess the suitability of this software-in-loop approach for carrying out realistic UWSN simulations. In addition to a detailed description of the simulation process, several simulations considering an illustrative network topology are performed, analyzing the impact of different critical parameters on the network performance. The conclusions suggest that the developed software-in-loop platform is suitable to carry out UWSN network tests using a real-world implementation of the STANAG 5066 stack. Moreover, other real-time protocol stacks may be easily adapted with minor modifications.

Toward accurate clock drift modeling in Wireless Sensor Networks simulation

The protocols used in Wireless Sensor Networks are subject to very strict temporal synchronization constraints. Radio Duty Cycle (RDC) protocols in particular are characterized by their very high synchronization accuracy requirements. In these protocols, synchronization errors are primarily caused by the natural clock drift observed in real nodes. The impact of the clock drift on the desynchronization issues can be investigated by the use of low-level node simulators.In this paper, we show the limitation of the COOJA simulator to evaluate the impact of the clock drift. We show that its current mote execution model does not faithfully reproduce the requested clock drift. We identify the root cause of these inaccuracies and present a new algorithm that is able to precisely reproduce any requested clock drifts in simulation. On the basis of our understanding, we build a mathematical model of the clock drift error allowing previous authors to estimate the error caused by clock drift inaccuracies in their studies and its impact on their results.To demonstrate the new algorithm, we consider a well-documented RDC protocol issue where the clock drift would cause periodic communication blackouts. This phenomenon was observed on real nodes, but was previously impossible to reproduce by simulation. Our new algorithm not only allows to reproduce the blackouts but also provides additional insights that help to confirm the initial analysis of the phenomenon. Finally, we use our algorithm to implement dynamic clock drift models to simulate the behavior of a clock drift evolving through time. We illustrate this using our linear model to push a RDC protocol to its limits.

Simulation of Cloud Platform Supporting Wireless Sensor Network

WSN has been an area of interest for a lot of researchers as well as the industry specialist due to its high usage in healthcare, military applications and in robotics. The focus area of WSN has been energy consumption. Integration of Cloud Computing in WSN has been observed by couple of research scholars as Cloud has been observed to be struggling against the power management issue. This paper presents a novel solution of power management in Cloud computing which uses the concept of clustering borrowed from WSN. The jobs are grouped or Clustered as per the algorithmic architecture of WSN and the minimization of migration is attempted using Genetic Algorithm (GA). Artificial Neural Network (ANN) is used as a conjunction to GA for energy efficiency. MATLAB is used as a simulation tool and consumed energy has been evaluated as the major evaluation parameter.

Reproducibility model for wireless sensor networks parallel simulations

Several wireless sensor networks (WSNs) simulations run in parallel computer architectures to improve their scalability. The main problem with this strategy is guaranteeing the reproducibility transparently to simulation users. We present a reproducible model for WSNs parallel simulations. The model uses a chunk partition strategy, in which all simulation elements are wrapped into chunks and simulated sequentially inside each chunk. We can simulate multiple chunks in parallel as often as possible by adding seed and a pseudo-random number generator in each of them, thus ensuring the same results. This model was integrated into the JSensor simulator and validated accordingly. An important aspect is that the new reproducibility model does not alter the simulation’s semantics, and it is transparent to the developer. The results demonstrated that our model could guarantee the reproducibility of stochastic WSNs parallel simulations performed in different computer systems with different threads.

Deployment techniques in wireless sensor networks: a survey, classification, challenges, and future research issues

Wireless sensor networks (WSNs) have been considered as one of the fine research areas in recent years because of vital role in numerous applications. To process the extracted data and transmit it to the various location, a large number of nodes must be deployed in a proper way because deployment is one of the major issues in WSNs. Hence, the minimum number of node deployment to attain full coverage is of enormous significance for research. The prime agenda of the presented paper is to categorize various coverage techniques into four major parts: computational geometry-based techniques, force-based techniques, grid-based techniques, and metaheuristic-based techniques. Additionally, several comparisons amid these schemes are provided in view of their benefits and drawbacks. Our discussion weighs on the classification of coverage, practical challenges in the deployment of WSNs, sensing models, and research issues in WSNs. Moreover, a detailed analysis of performance metrics and comparison among various WSNs simulators is listed. In conclusion, standing research issues along with potential work guidelines are discussed.

An Efficient Ray-Tracing Based Model Dedicated to Wireless Sensor Network Simulators for Smart Cities Environments

This article presents an efficient ray-tracing site-specific channel model compatible with wireless sensor network (WSN) simulator applications for smart cities. It relies on two 2D approaches dedicated to the main propagation modes; i.e. horizontal and vertical. The first is based on a pre-processing of the propagation environment, involving the calculation of an exact visibility graph. Computed from the discrete geometry concept called the super-cover model, it is improved to reduce its size and is used to very efficiently compute the most significant propagation paths in 3D. The specific WSN context, characterized by the sensor's radio range and mobility, is exploited to limit the size of the propagation environment and to pre-compute and store a set of visibility graphs, which are finally loaded and used on demand. The second approach is an over-rooftop model that re-uses the super-cover model to very efficiently extract the vertical profile containing the sensors, and proposes an original solution for the electrical field prediction where there are multiple diffractions in the transition zone. The results are validated against measurements, and show markedly better performance compared to others recent ray-tracing models. Finally, integration of the proposed overall solution for channel modeling in a WSN simulator is proposed, and interest in using such a model compared to conventional statistical models is demonstrated.

WSN Simulators Evaluation: an Approach Focusing on Energy Awareness

The large number of Wireless Sensor Networks (WSN) simulators available nowadays, differ in their design, goals, and characteristics. Users who have to decide which simulator is the most appropriate for their particular requirements, are today lost, faced with a panoply of disparate and diverse simulators. Hence, it is obvious the need for establishing guidelines that support users in the tasks of selecting a simulator to suit their preferences and needs. In previous works, we proposed a generic and novel approach to evaluate networks simulators, considering a methodological process and a set of qualitative and quantitative criteria. In particularly, for WSN simulators, the criteria include relevant aspects for this kind of networks, such as energy consumption modelling and scalability capacity. The aims of this work are: (i) describe deeply the criteria related to WSN aspects; (ii) extend and update the state of the art of WSN simulators elaborated in our previous works to identify the most used and cited in scientific articles; and (iii) demonstrate the suitability of our novel methodological approach by evaluating and comparing the three most cited simulators, specially in terms of energy modelling and scalability capacities. Results show that our proposed approach provides researchers with an evaluation tool that can be used to describe and compare WSN simulators in order to select the most appropriate one for a given scenario

Tone-Based Contention Resolution for Multi-hop Wireless Sensor Networks

Medium access control protocols with common active period (AP MACs) are frequently used in wireless sensor networks (WSNs) with medium-load traffic requirements. In this class of low duty-cycle contention-based protocols, sensor nodes synchronously alternate between active periods (used for data exchange) and sleep periods (used for energy conservation). The key component of AP MAC protocols is the contention resolution mechanism (CRM), which should provide channel access to as many nodes as possible, while eliminating, or at least minimizing the chance of date message collisions. Current AP MAC protocols commonly employ CRMs based on the traditional CSMA scheme, possibly extended with RTS–CTS handshake mechanism, which are known to be energy inefficient under heavy traffic conditions, especially in dense multi-hop WSNs. In this paper, we propose a collision-free and energy-efficient CRM, specially designed for application in AP MACs. The proposed CRM, referred to as AP/TONE protocol, replaces RTS-CTS control packets with short RF tones for exchanging elementary status information among neighbouring nodes. At the top of the tone-based signalling mechanism, AP/TONE implements a distributed two-phase multi-round contention resolution procedure. In the first phase, the network is partitioned into non-interfering clusters by selectively blocking sending/receiving status of contending nodes. In the second phase, the existing intra-cluster tone-based CRM is used to make the final selection. The performance of the proposed approach was evaluated by simulation of a multi-hop WSN with varying traffic parameters and node density. The obtained results show that AP/TONE achieves significantly higher throughput with reduced energy consumption with respect to CSMA-based approaches.

Cluster Based Techniques LEACH and Modified LEACH using Optimized Technique EHO in WSN

In the last few years, the Internet of Things (IoT) and the advance wireless networks are becoming very prominent in various domains. Wireless Sensors are facing problems of frequent energy loss which affects to the lifetime of the entire network. There are number of researchers who are working on such energy losses which occur in the wireless sensor nodes by using various approaches. One such method is Low- energy adaptive clustering hierarchy (LEACH) and its number of methods. Despite of various methods of LEACH, there is still immense scope of research as it is highly used in sensor nodes for different scenarios. The emerging growth of energy aware wireless sensor networks for a long time leads to various problems related to the lifetime of nodes in the wireless environment. In our research paper, a new and performance aware approach named Elephant Herd Optimization based Cluster Head Selection is devised and simulated so that the optimization level can be achieved. The nature inspired soft computing approaches are always beneficial for the use of optimization and reduction of various problems which can occur during energy optimization and this is the main focus which is considered in this research work. The main fundamental concept of the cluster head shuffling using EHO and other methods of key exchange are simulated in Contiki-Cooja which is an open source simulator for wireless sensor networks

Coverage Optimization and Simulation of Wireless Sensor Networks Based on Particle Swarm Optimization

As a new type of measurement and control network, wireless sensor networks (WSNs) technology has the characteristics of diversity and wide practicability. Based on the characteristics of WSNs, wireless sensor networks are widely used in military and civil industries. However, due to the frequent changes in the basic topology of wireless sensor networks and the relatively small number of corresponding network nodes, the efficiency of the nodes is the reason for its further development. Therefore, the node distribution strategy and the corresponding network coverage optimization strategy of wireless sensor networks are of great significance to achieve energy saving and network life extension. In order to solve the above WSNs problems, this paper will analyze and simulate the coverage optimization of wireless sensor networks based on Improved Particle Swarm Optimization algorithm. Firstly, this paper will analyze the structure characteristics of wireless sensor networks, complete the WSNs network coverage model and get the corresponding functions. Then this paper innovatively proposes “external dispersion method” to solve the problem of local area overlap in WSNs network coverage. At the same time, it innovatively proposes “free-particle swarm optimization” to solve the local convergence of conventional particle swarm optimization. At the end of this paper, simulation experiments are carried out to compare the optimal particle swarm optimization algorithm with the traditional particle swarm optimization algorithm. The experiments show that the proposed algorithm has obvious advantages in convergence and coverage.