Wireless Sensor Network Simulation Research Articles

A Performance Simulation Tool for the Analysis of Data Gathering in Both Terrestrial and Underwater Sensor Networks

Wireless sensor networks (WSNs) have greatly contributed to human-associated technologies. The deployment of WSNs has transcended several paradigms. Two of the most significant features of WSNs are the intensity of deployment and the criticalness of the applications that they govern. The tradeoff between volume and cost requires justified investments for evaluating the multitudes of hardware and complementary software options. In underwater sensor networks (USNs), testing any technique is not only costly but also difficult in terms of full deployment. Therefore, evaluation prior to the actual procurement and setup of a WSN and USN is an extremely important step. The spectrum of performance analysis tools encompassing the test-bed, analysis, and simulation has been able to provide the prerequisites that these evaluations require. Simulations have proven to be an extensively used tool for analysis in the computer network field. A number of simulation tools have been developed for wired/wireless radio networks. However, each simulation tool has several restrictions when extended to the analysis of WSNs. These restrictions are largely attributed to the unique nature of each WSN within a designated area of research. In addition, these tools cannot be used for underwater environments with an acoustic communication medium, because there is a wide range of differences between radio and acoustic communications. The primary purpose of this paper is to present, propose, and develop a discrete event simulation designed specifically for mobile data gathering in WSNs. In addition, this simulator has the ability to simulate 2-D USNs. This simulator has been tailored to cater to both mobile and static data gathering techniques for both topologies, which are either dense or light. The results obtained using this simulator have shown an evolving efficient simulator for both WSNs and USNs. The developed simulator has been extensively tested in terms of its validity and scope of governance.

MODELING AND SIMULATION OF THRESHOLD ANALYSIS FOR PVFS IN WIRELESS SENSOR NETWORKS

Wireless sensor networks (WSNs) suffer serious damage from false positive and negative attacks due to their hardware restrictions. The sensor network causes both unnecessary energy consumption and information loss through false reports and normal reports, which include false message authentication codes (MACs). A probabilistic voting-based filtering scheme (PVFS) effectively detects the two types of attacks through a pre-defined threshold, which is the number of detected false MACs in a report. Since the threshold significantly influences the ability to detect attacks, the sensor network should be simulated to ensure proper function. In this paper, we describe the development and simulation of a PVFS-based WSN using a discrete event system specification. The experimental results showed that PVFS with a threshold of 2 reduced energy usage by about 16% and improved the detected false reports as compared with a PVFS with a threshold of 3.

Near-Ground Channel Modeling for Distributed Cooperative Communications

A computationally efficient near-ground field prediction model is proposed to facilitate realistic wireless sensor network (WSN) simulations. In this model, using the principle of Fresnel zones, path loss is split into three segments. Certain propagation mechanisms dominate in each part. The distances that define the edges of each section are derived theoretically. The model is validated against several experimental datasets obtained in open and forested areas. It is noticed that the proposed model has higher accuracy compared to existing analytical near-ground propagation models. This enhancement is achieved by careful assessment of key features relevant to near-grazing propagation such as diffraction loss due to obstruction of the first Fresnel zone and higher order waves produced by terrain irregularities. Monte Carlo simulations are used to investigate the effects of antenna height, frequency of operation, polarization, and terrain dielectric and roughness properties on WSNs performance. It is realized that antenna height is by far the most influential geometric parameter to low-altitude WSNs connectivity and average number of neighbors.

An Integrated Simulation Module for Cyber-Physical Automation Systems.

The integration of Wireless Sensors Networks (WSNs) into Cyber Physical Systems (CPSs) is an important research problem to solve in order to increase the performances, safety, reliability and usability of wireless automation systems. Due to the complexity of real CPSs, emulators and simulators are often used to replace the real control devices and physical connections during the development stage. The most widespread simulators are free, open source, expandable, flexible and fully integrated into mathematical modeling tools; however, the connection at a physical level and the direct interaction with the real process via the WSN are only marginally tackled; moreover, the simulated wireless sensor motes are not able to generate the analogue output typically required for control purposes. A new simulation module for the control of a wireless cyber-physical system is proposed in this paper. The module integrates the COntiki OS JAva Simulator (COOJA), a cross-level wireless sensor network simulator, and the LabVIEW system design software from National Instruments. The proposed software module has been called “GILOO” (Graphical Integration of Labview and cOOja). It allows one to develop and to debug control strategies over the WSN both using virtual or real hardware modules, such as the National Instruments Real-Time Module platform, the CompactRio, the Supervisory Control And Data Acquisition (SCADA), etc. To test the proposed solution, we decided to integrate it with one of the most popular simulators, i.e., the Contiki OS, and wireless motes, i.e., the Sky mote. As a further contribution, the Contiki Sky DAC driver and a new “Advanced Sky GUI” have been proposed and tested in the COOJA Simulator in order to provide the possibility to develop control over the WSN. To test the performances of the proposed GILOO software module, several experimental tests have been made, and interesting preliminary results are reported. The GILOO module has been applied to a smart home mock-up where a networked control has been developed for the LED lighting system.

Security Estimation in Wireless Sensor Network Simulator

Sensor nodes are low-power and low-cost devices with the requirement of a long autonomous lifetime. Therefore, the nodes have to use the available power carefully and avoid expensive computations or radio transmissions. In addition, as some wireless sensor networks (WSNs) process sensitive data, selecting a security protocol is vital. Cryptographic methods used in WSNs should fulfill the constraints of sensor nodes and should be evaluated for their security and power consumption. WSN engineers use several metrics to obtain estimations prior to network deployment. These metrics are usually related to power and execution time estimation. However, security is a feature that cannot be estimated and it is either “active” or “inactive”, with no possibility of introducing intermediate security levels. This lack of flexibility is a disadvantage in real deployments where different operation modes with different security and power specifications are often needed. This paper proposes including a new security estimation metric in a previously proposed framework for WSN simulation and embedded software (SW) performance analysis. This metric is called Security Estimation Metric (SEM) and it provides information about the security encryption used in WSN transmissions. Results show that the metric improves flexibility, granularity and execution time compared to other cryptographic tests.

Wireless sensor network simulation frameworks: A tutorial review: MATLAB/Simulink bests the rest

A Wireless Sensor Network (WSN) is a distributed set of sensors deployed to work together for collective sensing and possible data processing. A WSN can be used to monitor environmental behavior and structural integrity in a variety of application fields, thus becoming an integral part of the consumer electronics of smart buildings in smart cities. Due to ever-increasing population growth, along with limited natural resources, smart cities are expected to be the wave of the future. For instance, WSNs are widely used in industrial settings with machine monitoring and play an important role in monitoring the structural integrity of large buildings and bridges. This article focuses on existing WSN simulation frameworks that could be integrated with realtime hardware prototypes. We analyze and compare various such simulation frameworks, and we determine a suitable simulation environment that supports specific software packages.

A Cooja-Based Tool for Coverage and Lifetime Evaluation in an In-Building Sensor Network

Contiki’s Cooja is a very popular wireless sensor network (WSN) simulator, but it lacks support for modelling sensing coverage, focusing instead on network connectivity and protocol performance. However, in practice, it is the ability of a sensor network to provide a satisfactory level of coverage that defines its ultimate utility for end-users. We introduce WSN-Maintain, a Cooja-based tool for coverage and network lifetime evaluation in an in-building WSN. To extend the network lifetime, but still maintain the required quality of coverage, the tool finds coverage redundant nodes, puts them to sleep and automatically turns them on when active nodes fail and coverage quality decreases. WSN-Maintain together with Cooja allow us to evaluate different approaches to maintain coverage. As use cases to the tool, we implement two redundant node algorithms: greedy-maintain, a centralised algorithm, and local-maintain, a localised algorithm to configure the initial network and to turn on redundant nodes. Using data from five real deployments, we show that our tool with simple redundant node algorithms and reading correlation can improve energy efficiency by putting more nodes to sleep.

Comparison of simulators for assessing the ability to sustain wireless sensor networks using dynamic network reconfiguration

Wireless sensor networks (WSNs) can be used for a variety of tasks. The goal is to sustain such networks for as long as possible while still maintaining acceptable performance on the task. Evaluating WSNs for such diverse tasks precludes actual deployment and thus requires simulation. In this work, we compare simulators that can model power consumption and allow dynamic reconfiguration of network parameters based on feedback from the end application. The simulation results demonstrate some fundamental differences in out-of-the-box performance in terms of the way the simulators behave and calculate power consumption. With modifications to parameters and behavior, however the simulators’ outputs become more closely aligned. Overall, based on our selection criteria, ns-3 was the best WSN simulator of those evaluated for assessing the sustainability of a WSN in a variety of settings.

GELSenVAC: A Novel Sensor Network Framework for WSN Simulation

Nowadays, Wireless Sensor Networks (WSN) are emerging because of the technological developments in wireless communication and the advancements in miniaturization of sensor hardware nodes. WSN is an Adhoc network with more number of nodes densely deployed. The main focus of any WSN is to maximize the lifetime of the network as the sensor nodes are having limited battery energy and the nodes are unattended. Lifetime of the WSN depends on various parameters such as hardware used, number of nodes, deployment strategies, MAC protocol, routing protocol, sampling rate, sampling time, etc. To determine the lifetime of WSN apriori to real time deployment, simulator software is used for evaluating the impact of various parameters influencing the lifetime. Global Mobile Simulator (GloMoSim) is one such text based simulator software used for simulating wireless networks. GloMoSim is not supporting the required features, viz., sensor specific MAC and routing protocols, energy model for lifetime estimation, and charting facility for WSN Simulation. In this paper, the design of novel easy to use GUI with Energy model based Lifetime estimation supported Sensor network framework with Visualization, Application statistics, and Charting facility tools, GELSenVAC, is proposed and implemented. It consists of hardware support for TelosB, MicaZ motes, Sensor MAC (S-MAC) protocol support in data link layer, energy model for lifetime estimation, facility to view application level statistics, and charting facility to generate lifetime charts, on top of GloMoSim environment. By using this framework, designers can easily simulate their own WSN, estimate the lifetime, and select suitable parameters to increase the lifetime of the network. The designed framework is tested by simulating a WSN. The computed lifetime and the results obtained using the tools supported by this framework are presented.

DETERMINATION of GENERAL PARAMETERS of WSNs DESIGNED for 3-D CLOSED ENVIRONMENTS

Use of Wireless Sensor Networks (WSNs) has become widespread in many critical environments. For example, this technology has come into use in tunnels, mines and so on. In this kind of environments, a WSN system design must be far away from randomness and be done systematically. Therefore simulators play a significant role in a WSN system design. Success of a simulator affects directly success of the system. In this paper, we preferred Castalia simulator which is a successful WSN simulator based on OMNET. Many parameters such as different data size, indoor environment features, and various transmission power levels etc., which have an effect on packet reception ratio (PRR), were examined by Castalia. Finally, we explain how to design a WSN system, and what should be considered in a WSN simulation.

Selected RSSI-based DV-Hop Localization for Wireless Sensor Networks

With the increasing demand on wireless sensor networks (WSNs) applications, acquiring the information of sensor node locations becomes one of the most important issues. Up to now, available localization approaches can be categorized into range-free and range-based methods. Range-free localizations are being pursued as a more cost-effective method. However, range-based schemes have better localization accuracy. This paper proposes the selected RSSI-based DV-Hop localization, which improves localization accuracy from the existing schemes by applying a combined technique that inherits the benefits from both methods. Our proposed technique firstly employs the DV-Hop approach of range-free algorithms, then uses the received signal strength indicator (RSSI) estimation technique of range-based algorithms to estimate the distances of selected hops. This paper also includes basic studies, which have been performed via computer simulations as well as testbed experiments, for distance calculation from RSSI measurement and location estimation in order to prove the credibility of our simulator. The proposed technique is implemented and tested via our developed WSN simulation model. Results in terms of distance error in comparison with traditional DV-Hop, RDV-Hop, and weighted RSSI algorithms show significant performance improvement by using our proposed method for both low-density and high-density wireless sensor network test scenarios.

Parallel and distributed neurocomputing with wireless sensor networks

This paper proposes a novel hardware computing platform for fully parallel and distributed computation of artificial neural network (ANN) algorithms. The proposed idea entails leveraging the existing wireless sensor networks (WSN) technology to serve as a parallel and distributed hardware platform to implement computations for artificial neural network algorithms. Feasibility of the proposed neurocomputing architecture is demonstrated through a simulation-based case study, which uses Kohonen׳s self-organizing map as the neural network algorithm. MATLAB-based PROWLER, which is a protocol and application level simulator for wireless sensor networks, is employed for the simulation study. Findings demonstrated that the proposed neurocomputing architecture was able to train the SOM neural network with competitive accuracy values for the unsupervised clustering task. Conclusions of the simulation study suggest that the WSN-based neurocomputing architecture is a feasible alternative for realizing parallel and distributed computation of artificial neural network algorithms.

SolarCastalia: Solar Energy Harvesting Wireless Sensor Network Simulator

Most existing simulators for WSNs (wireless sensor networks) model battery-powered sensors and provide MAC and routing protocols designed for battery-powered WSNs. Recently, however, increasingly extensive studies of energy harvesting sensor systems require the development of appropriate simulators, but there are few related studies on such simulators. Unlike existing simulators, simulators for energy harvesting WSNs require a new energy model that is integrated with the energy harvesting, rechargeable battery, and energy consuming models. Additionally, the new model must enable applications of the well-known MAC and routing protocols designed for energy harvesting WSNs and have a convenient user-friendly interface. In this work, we design and implement a user-friendly simulator for solar energy harvesting WSNs.

Transmission Protocol Simulation Framework For The Resource-Constrained Wireless Sensor Network

Abstract In this paper a prototype framework for simulation of wireless sensor network and its protocols are presented. The framework simulates operation of a sensor network with data transmission, which enables simultaneous development of the sensor network software, its hardware and the protocols for wireless data transmission. An advantage of using the framework is converging simulation with the real software. Instead of creating a model of the sensor network node, the same software is used in real sensor network nodes and in the simulation framework. Operation of the framework is illustrated with examples of simulations of selected transactions in the sensor network.

TeaCP: A Toolkit for Evaluation and Analysis of Collection Protocols in Wireless Sensor Networks

We present TeaCP, a prototype toolkit for the evaluation and analysis of collection protocols in both simulation and experimental environments running on TinyOS. Our toolkit consists of a testing system, which runs a collection protocol of choice, and an optional SD card-based logging system, which stores the logs generated by the testing system. The SD card datalogger allows a wireless sensor network (WSN) to be deployed flexibly in various environments, especially where wired transfer of data is difficult. Using the saved logs, TeaCP evaluates a wide range of performance metrics, such as reliability, throughput, and delay. TeaCP further allows visualization of packet routes and the topology evolution of the network, under both static and dynamic conditions, even in the face of transient disconnections. Through simulation of an intra-car WSN and real lab experiments, we demonstrate the functionality of TeaCP for comparing the performance of two prominent collection protocols, the Collection Tree Protocol (CTP) and the Backpressure Collection Protocol (BCP). We also present the usage of TeaCP as a high level diagnosis tool, through which an inconsistency of the BCP implementation for the CC2420 radio chips is identified and resolved.

OPNET-based modeling and simulation of mobile Zigbee sensor networks

Modeling and simulation can help to validate and evaluate the performance of wireless sensor networks (WSNs) within specific applications. In order to resolve the issue of the restriction on node mobility in existing Zigbee WSN simulation models, this paper proposes a Zigbee compliant new simulation model using the OPNET simulator. Based on the Zigbee MAC layer model in OPNET Modeler, we develop a network layer model and propose an improved AODV routing algorithm to support node mobility, both of which are compatible with Zigbee protocols. We further present in details the structure of the network layer process model and the implementation procedures of its kernel functions. Comprehensive performance comparisons are performed between the proposed model and the Zigbee model in OPNET standard libraries. In order to evaluate the effectiveness of the proposed model in the aspect of node mobility support, time intervals between route failure occurrence and route recovery are measured as well. The experimental results show that the proposed simulation model achieves better performance, compared to the original one. In addition, when node mobility causes routing failures, alternative routes can be established quickly by the proposed model.

Design and Simulation of Wireless Sensor Network in NS2

This paper provides a study of how to design and implement Wireless Sensor Network (WSN) in NS2 (Network Simulator version 2).A wireless sensor network (WSN) consists of a number of sensors which are spatially distributed and are capable of computing, communicating and sensing.NS2 is an event-driven simulation tool that is useful in studying the dynamic nature of computer networks.NS2 provides users with executable command ns which take on input argument, which is the name of a Tool Command Language (TCL) simulation scripting file. Network Animator (NAM) is a TCL based animation tool for viewing network simulation traces and real world packet traces. Scripting languages such as AWK (Aho Weinberger Kernighan) script and PERL script can be used to calculate the performance metrics using these trace files. A simple simulation consisting of 17 nodes and calculation of average end-to-end delay and average energy consumption is shown.

Water-Saving Monitoring System Design Based on LabView Simulation Platform

A water-saving irrigation monitoring system was designed based on ZigBee wireless sensor network and LabView simulation platform. This system can solve the problems of unnecessary waste caused by the traditional artificial irrigation water and wiring complex of water-saving control system. The information of each node and data acquisition can be detected by the ZigBee wireless network monitoring system. Upper machine was designed by LabView virtual design platform, and all aspects of organic characteristics of the crop water requirement rule were combined through the fuzzy control decision support system. The date of the irrigation water would be directed, and achieved a fine management of water and scientific irrigation.

Symphony: a framework for accurate and holistic WSN simulation.

Research on wireless sensor networks has progressed rapidly over the last decade, and these technologies have been widely adopted for both industrial and domestic uses. Several operating systems have been developed, along with a multitude of network protocols for all layers of the communication stack. Industrial Wireless Sensor Network (WSN) systems must satisfy strict criteria and are typically more complex and larger in scale than domestic systems. Together with the non-deterministic behavior of network hardware in real settings, this greatly complicates the debugging and testing of WSN functionality. To facilitate the testing, validation, and debugging of large-scale WSN systems, we have developed a simulation framework that accurately reproduces the processes that occur inside real equipment, including both hardware- and software-induced delays. The core of the framework consists of a virtualized operating system and an emulated hardware platform that is integrated with the general purpose network simulator ns-3. Our framework enables the user to adjust the real code base as would be done in real deployments and also to test the boundary effects of different hardware components on the performance of distributed applications and protocols. Additionally we have developed a clock emulator with several different skew models and a component that handles sensory data feeds. The new framework should substantially shorten WSN application development cycles.

Simulation and Visualization of Wireless Sensor Networks Based on NS2

This paper analyzed wireless sensor network simulation technology. We discussed the principles of wireless sensor network simulation based on NS2 and constructed a visual simulation model for wireless sensor networks. By adding NS2 protocol and setting the sensor nodes and some simple parameters, the system presented the running process and the performance of the network in the form of animation and graphics. The results show that this method simplifies the process of simulation of wireless sensor networks, and improves the efficiency of wireless sensor networks research and development, which provides support for the development of application-oriented networking of wireless sensor networks.