Sensor Network Simulator Research Articles

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.

Decentralized Online Learning Methods Based on Weight-Balancing Over Time-Varying Digraphs

This paper considers decentralized online optimization problems over a graph, where the allocated objective function of each agent is revealed over time and is only known for the corresponding agent in hindsight. Moreover, the graph is directed and time varying. In order to solve the problem, a decentralized stochastic subgradient online learning method is proposed over time-varying digraphs. However, the directed graph could generate an asymmetric weight matrix, which is not doubly stochastic matrix. To overcome this difficulty, we employ a weight-balancing technique. By choosing appropriate learning rates, we show that our proposed method can achieve logarithmic regret under strong convexity. Moreover, under convexity, the square-root regret can also be achieved. In addition, numerical simulations in sensor networks for solving the online distributed estimation problem illustrate the theoretical results.

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.

Gateway placement and traffic load simulation in sensor networks

AbstractBecause of the wide variety of possible application fields and the spread of smart devices, the research of wireless sensor networks has become an increasingly important area in the last decade. During the design of these networks, several important aspects have to be considered, for example the lifetime of the network, expected battery usage, or robustness of the installed system. In this paper a simulation environment is introduced that enables the testing of different information spreading methods on the network and provides suggestions for gateway placements with different objectives.

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

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.

Framework for the Simulation of Sensor Networks Aimed at Evaluating In Situ Calibration Algorithms.

The drastically increasing availability of low-cost sensors for environmental monitoring has fostered a large interest in the literature. One particular challenge for such devices is the fast degradation over time of the quality of their data. Therefore, the instruments require frequent calibrations. Traditionally, this operation is carried out on each sensor in dedicated laboratories. This is not economically sustainable for dense networks of low-cost sensors. An alternative that has been investigated is in situ calibration: exploiting the properties of the sensor network, the instruments are calibrated while staying in the field and preferably without any physical intervention. The literature indicates there is wide variety of in situ calibration strategies depending on the type of sensor network deployed. However, there is a lack for a systematic benchmark of calibration algorithms. In this paper, we propose the first framework for the simulation of sensor networks enabling a systematic comparison of in situ calibration strategies with reproducibility, and scalability. We showcase it on a primary test case applied to several calibration strategies for blind and static sensor networks. The performances of calibration are shown to be tightly related to the deployment of the network itself, the parameters of the algorithm and the metrics used to evaluate the results. We study the impact of the main modelling choices and adjustments of parameters in our framework and highlight their influence on the results of the calibration algorithms. We also show how our framework can be used as a tool for the design of a network of low-cost sensors.

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.

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.

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

محاكاة شبكات الاستشعار اللاسلكية للوسائط المتعددة WMSN

أصبحت شبكات استشعار الوسائط المتعددة اللاسلكية (WMSNs) شائعة على نطاق واسع بسبب توفر أجهزة استشعار متعددة الوسائط سهلة الاستخدام ومنخفضة التكلفة قادرة على استرداد ونقل محتوى الوسائط المتعددة مثل الصوت والصور وتدفق الفيديو. اتبعت محاكاة WMSN التقنيات والأدوات المستخدمة بشكل أساسي بواسطة شبكات الاستشعار اللاسلكية المماثلة (WSN). هذا ، لسوء الحظ ، لم يكن كافيًا لطبيعة البيانات الكثيفة لشبكات WMSN. لذلك ، لا يزال من الصعب توفير أطر محاكاة كافية لشبكات WMSN. تقدم هذه الورقة مسحًا لأطر المحاكاة والأدوات المتاحة لشبكات WMSN. يتم عرض التحديات التي تواجه عملية المحاكاة لأول مرة. بعد ذلك ، يتم تقديم ومراجعة سمات محاكاة WMSN المثالية. كما تم عرض ومناقشة النموذج العام لبيئات محاكاة WMSN. أخيرًا ، يتم تقديم مسح مفصل لأطر وأدوات المحاكاة المتاحة. يتم أيضًا تقديم الأدوات الموروثة من شبكة الاستشعار اللاسلكية (WSN) وتلك المصنوعة خصيصًا لشبكات WMSN.

A Review on Wireless Sensor Network Simulation Tools

Wireless Sensor Networks (WSNs) were increasing developing enthusiasm for as a long way returned as years; WSN assignments of a Every sensor network incorporates gazing and estimating sure marvels, as well as turning in collected data. Sensor network require applying distinctive strategies utilized in stressed out and wireless network. Simulation tool for wireless sensor system are steadily being utilized to contemplate sensor networks and to check new programs and Protocols in this developing research field. It is valuable to researcher to verify new though and dissect with proposed algorithm in virtual environment and assist to keep away from expensive hardware usage and time utilization too. This paper gives a whole overview and comparisons of various wireless sensor network simulators with the intention to help researchers with choosing the best simulator on hand for a selected application environment.

A local algorithm to approximate the global clustering of streams generated in ubiquitous sensor networks

In ubiquitous streaming data sources, such as sensor networks, clustering nodes by the data they produce gives insights on the phenomenon being monitored. However, centralized algorithms force communication and storage requirements to grow unbounded. This article presents L2GClust, an algorithm to compute local clusterings at each node as an approximation of the global clustering. L2GClust performs local clustering of the sources based on the moving average of each node’s data over time: the moving average is approximated using memory-less statistics; clustering is based on the furthest-point algorithm applied to the centroids computed by the node’s direct neighbors. Evaluation is performed both on synthetic and real sensor data, using a state-of-the-art sensor network simulator and measuring sensitivity to network size, number of clusters, cluster overlapping, and communication incompleteness. A high level of agreement was found between local and global clusterings, with special emphasis on separability agreement, while an overall robustness to incomplete communications emerged. Communication reduction was also theoretically shown, with communication ratios empirically evaluated for large networks. L2GClust is able to keep a good approximation of the global clustering, using less communication than a centralized alternative, supporting the recommendation to use local algorithms for distributed clustering of streaming data sources.

Intelligent Communication in Wireless Sensor Networks

Wireless sensor networks (WSN) are designed to collect information by means of a large number of energy-limited battery sensor nodes. Therefore, it is important to minimize the energy consumed by each sensor, in order to extend the network life. The goal of this work is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent is sent to each sensor in order to process the information and to cooperate with neighboring sensors while mobile agents (MA) can be used to reduce information shared between source nodes (SN) and send them to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the multi-agent system (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the sensors of the network have been grouped into sectors. For each MA, we have established an optimal itinerary, consuming a minimum amount of energy with data aggregation efficiency in a minimum time. Successive simulations in large-scale wireless sensor networks through the SINALGO (published under a BSD license) simulator show the performance of the proposed method, in terms of energy consumption and package delivery rate.

Methods of life cycle increase for the Internet of things

Subject of Research. The paper proposes models that make it possible to extend the Internet of things life cycle as a result of the sensory field clustering and the transfer of the interaction functions from the base station to the head node of the cluster. The efficiency of the clustered wireless sensor network was evaluated in comparison with the nonclustered one in terms of the residual energy parameter and the network lifetime. Methods. The Internet of things sensory field clustering method was used. The method is based on the idea of​equiprobable rotation of the head nodes, taking into account the level of nodes residual energy and the distance from the sensor devices to the head node. The time division multiple accessmechanism in the interaction of sensory devices with the head node of the cluster minimizes the probability of data transmission collision. Simulation modeling provides a tool for selecting clustering parameters while providing the required characteristics of the functioning of the Internet of things. Main Results. A wireless sensor network simulation model is proposed, which can find application in the Internet of things designing tasks. Estimations are given demonstrating the clustering expediency of the Internet of things sensory field at sensory field sizes exceeding the distance from the most remote node to the base station. Practical Relevance.Sensor field clustering provides the increase of the Internet of things life cycle. The proposed models will be useful in the early stages of the Internet of things design.

Leach performance analysis varying the percentage of cluster head

The LEACH protocol is a “standard” protocol used in the analysis and simulation of wireless sensor networks. This article analyzes the effect of varying parameter values in the LEACH protocol. In particular, the case of varying cluster head node assignments to , , and of the total nodes of the network. Specifically, it shows the energy effect of this variation and the corresponding data traffic analysis, showing simulation results that illustrate the behavior resulting from this variation by using an approach of time-division multiplexing on the clusters.

A Lightweight Intrusion Detection Method Based on Fuzzy Clustering Algorithm for Wireless Sensor Networks

For resource-constrained wireless sensor networks (WSNs), designing a lightweight intrusion detection technology has been a hot and difficult issue. In this paper, we proposed a lightweight intrusion detection method that was able to directly map the network status into sensor monitoring data received by base station, so that base station can sense the abnormal changes in the network. Our method is highlighted by the fusion of fuzzy c-means algorithm, one-class SVM, and sliding window procedure to effectively differentiate network attacks from abnormal data. Finally, the proposed method was tested on the wireless sensor network simulation software EXata and in real applications. The results showed that the intrusion detection method in this paper could effectively identify whether the abnormal data came from a network attack or just a noise. In addition, extra energy consumption can be avoided in all sensor monitoring nodes of the sensor network where our method has been deployed.

Identification of Location Spoofing in Wireless Sensor Networks in Non-Line-of-Sight Conditions

Location spoofing and non-line-of-sight (NLOS) propagation are two leading reasons of serious localization errors in wireless networks. Previous studies have managed to identify these two factors separately. However, when present in the same system, these two factors can cause localization errors in a similar manner, making the identification difficult. In this paper, we address the problem of identifying location spoofing in NLOS conditions. We first carry out a geometric analysis on NLOS and derive a bound that can be used to differentiate NLOS from location spoofing. Based on the bound, we propose an identification method. We show that the proposed method is secure against different types of spoofing attacks including those from individuals and from multiple collaborative attackers. In particular, it can be used to identify the well-known “perfect location spoofing.” Simulation in wireless sensor networks indicates that our method can achieve a high accuracy with 0 false positive on identifying individual attacks and perfect location spoofing in NLOS conditions.