G-Jsim: A GUI tool for wireless sensor networks simulation under J-Sim

“Copyright © [2008] IEEE. Reprinted from 12th Annual IEEE International Symposium on Consumer Electronics (ISCE 2008). ISBN:978-1-4244-2422-1. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”A Wireless Sensor Network is composed of up to thousands of smart sensing nodes with processing unit and memory, sensing unit and wireless communication capabilities. Wireless Sensor Networks application spans from the military applications into almost every field we can think of. Several simulation tools are readily available, among them the J-Sim, a java-based simulator with growing interest by research and network developers alike. We propose to enhance J-Sim functionality with a Guided User Interface for Wireless Sensor Networks that dramatically increases the user-friendliness of the simulator. Also, we provide a free download web page for everyone to benefit

A ranking of the most known freeware and open source discrete-event simulation tools

Freeware and open source simulation software can be of great relevant when applying simulation in companies that do not possess the required monetary resources to invest in traditional commercial software, since these can be unaffordable Even so, there is a lack of papers that contribute to literature with a comparison of opensource and freeware simulation tools. Furthermore, such existing papers fail to establish a proper assessment of these type of tools. In this regard, this paper proposes a study in which several freeware and open source discrete-event general purpose simulation tools were selected and compared, in order to propose a ranking based on the tools' popularity, considering several criteria. For this purpose, 30 criteria were used to assess the score of each tool, leading to a podium composed by SimPy, JSim and JaamSim. Further conclusion and future work are discussed in the last section.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019 and by the Doctoral scholarship PDE/BDE/114566/2016 funded by FCT, the Portuguese Ministry of Science, Technology and Higher Education, through national funds, and co-financed by the European Social Fund (ESF) through the Operational Programme for Human Capital (POCH

An online model composition tool for system biology models

Background: There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results: We present the design and implementation of the Model Composition Tool (Interface) within the PathCaseSB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions: Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well

Automatic Detection of Defects in Applications without Test Oracles

In application domains that do not have a test oracle, such as machine learning and scientific computing, quality assurance is a challenge because it is difficult or impossible to know in advance what the correct output should be for general input. Previously, metamorphic testing has been shown to be a simple yet effective technique in detecting defects, even without an oracle. In metamorphic testing, the application's ``metamorphic properties'' are used to modify existing test case input to produce new test cases in such a manner that, when given the new input, the new output can easily be computed based on the original output. If the new output is not as expected, then a defect must exist. In practice, however, metamorphic testing can be a manually intensive technique for all but the simplest cases. The transformation of input data can be laborious for large data sets, and errors can occur in comparing the outputs when they are very complex. In this paper, we present a tool called Amsterdam that automates metamorphic testing by allowing the tester to easily set up and conduct metamorphic tests with little manual intervention, merely by specifying the properties to check, configuring the framework, and running the software. Additionally, we describe an approach called Heuristic Metamorphic Testing, which addresses issues related to false positives and non-determinism, and we present the results of new empirical studies that demonstrate the effectiveness of metamorphic testing techniques at detecting defects in real-world programs without test oracles

G-Sense: a graphical interface for SENSE simulator

“Copyright © [2009] IEEE. Reprinted from First International Conference on Advances in System Simulation.ISBN:978-1-4244-4863-0. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”Wireless sensor networks greatly benefit from simulation before deployment, since some of these networks may contain thousands of nodes. The new challenges compared to traditional computer networks led to several approaches for network simulation, namely SENSE – Sensor Network Emulator and Simulator. However this approach presents a limited user interface, namely based on text, forcing users to have knowledge on C++ programming language. This paper presents a tool, called G-Sense, that greatly improves SENSE user friendliness, with graphical input of simulation parameters, save and load simulation features, and simulation results management with plot view. This new tool uses SENSE simulation engine in a transparent way, so the user may be focused on the simulation itself, not in the underlying simulation tool. We present G-Sense architecture, usability and extensive experiments for its validation. We believe that this tool will contribute for SENSE adoption for wireless sensor network simulation, clearly improving on its ease of use

A Survey on Wireless Network Simulators

The Network simulator helps the developer to create and simulate new models on an arbitrary network by specifying both the behavior of the network nodes and the communication channels. It provides a virtual environment for an assortment of desirable features such as modeling a network based on a specific criteria and analyzing its performance under different scenarios. This saves cost and time required for testing the functionality and the execution of network. This paper has surveyed various Wireless Network Simulators and compared them

A Survey on Wireless Network Simulators

The Network simulator helps the developer to create and simulate new models on an arbitrary network by specifying both the behavior of the network nodes and the communication channels. It provides a virtual environment for an assortment of desirable features such as modeling a network based on a specific criteria and analyzing its performance under different scenarios. This saves cost and time required for testing the functionality and the execution of network. This paper has surveyed various Wireless Network Simulators and compared them

JMT – Performance Engineering Tools for System Modeling

We present the Java Modelling Tools (JMT) suite, an integrated framework of Java tools for performance evaluation of computer systems using queueing models. The suite offers a rich user interface that simplifies the definition of performance models by means of wizard dialogs and of a graphical design workspace. The performance evaluation features of JMT span a wide range of state-of-the-art methodologies including discrete-event simulation, mean value analysis of product-form networks, analytical identification of bottleneck resources in multiclass environments, and workload characterization with fuzzy clustering. The discrete-event simulator supports several advanced modeling features such as finite capacity regions, load-dependent service times, bursty processes, fork-and-join nodes, and implements spectral estimation for analysis of simulative results. The suite is open-source, released under the GNU general public license (GPL), and it is available for free download at http://jmt.sourceforge.net

LBSim: A simulation system for dynamic load-balancing algorithms for distributed systems.

In a distributed system consisting of autonomous computational units, the total computational power of all the units needs to be utilized efficiently by applying suitable load-balancing policies. For accomplishing the task, a large number of load balancing algorithms have been proposed in the literature. To facilitate the performance study of each of these load-balancing strategies, simulation has been widely used. However comparison of the load balancing algorithms becomes difficult if a different simulator is used for each case. There have been few studies on generalized simulation of load-balancing algorithms in distributed systems. Most of the simulation systems address the experiments for some particular load-balancing algorithms, whereas this thesis aims to study the simulation for a broad range of algorithms. After the characterization of the distributed systems and the extraction of the common components of load-balancing algorithms, a simulation system, called LBSim, has been built. LBSim is a generalized event-driven simulator for studying load-balancing algorithms with coarse-grained applications running on distributed networks of autonomous processing nodes. In order to verify that the simulation model can represent actual systems reasonably well, we have validated LBSim both qualitatively and quantitatively. As a toolkit of simulation, LBSim programming libraries can be reused to implement load-balancing algorithms for the purpose of performance measurement and analysis from different perspectives. As a framework of algorithm simulation can be extended with a moderate effort by following object-oriented methodology, to meet any new requirements that may arise in the future.Dept. of Computer Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .D8. Source: Masters Abstracts International, Volume: 43-05, page: 1747. Adviser: A. K. Aggarwal. Thesis (M.Sc.)--University of Windsor (Canada), 2004