Performance evaluation of the reactor pattern using the OMNeT++ simulator

The design of large-scale, distributed, performance-sensitive systems presents numerous challenges due to their network-centric nature and stringent quality of service (QoS) require-ments. Standardized middleware implementations provide the key building blocks necessary to address these require-ments of the distributed systems. However, middleware are designed to be applicable for a wide range of domains and applications, which results in system developers requiring to choose the right set of building blocks to design their system. To reduce the impact on development costs and time-to-market, decisions on the right set of building blocks to use in systems design must be made as early as possible in system design. This paper addresses this concern by describ-ing a model-driven systems simulation approach to analyze, catch and rectify incorrect system design decisions at design-time. In this paper we focus on model-driven OMNeT++ simulation of the Reactor pattern, which provides event de-multiplexing and handling capability. Our experience with modeling the Reactor shows that this approach can be ex-tended to the performance analysis of other pattern-based blocks and indeed in the long term to the entire composed middleware framework

Performance Modelling of UUM Local Area Network(Wired)

Slow network connection in accessing resources is a common complaint on a computer network that has switches as dominant network equipment, when certain nodes are heavily loaded with clients more than their capacity. In this study a simulation model was developed and validated for the University of Utara Malaysia wired Local Area Network. The effect of network parameters such as the processing time and the packet arrival rate on the performance metrics such as throughput, end to end delay and utilization of the servers and switches on the network was investigated. The analysis of the results from the simulations carried out can assist the management of computer centre that manages the network in identifying the bottleneck node on the network and for future network capacity building

Fibre Channel Switch Modeling at Fibre Channel-2 Level for Large Fabric Storage Area Network Simulations using OMNeT++

Abstract—Typically, in the current enterprise data centers dedicated fabrics or networks are implemented to meet their LAN, Inter-Processor communication and storage traffic requirements. The storage traffic requirements of a group of servers are met through multiple storage area networks based on fibre channel, which has become the standard connection type. Typically, this fibre channel storage area networks are small (maximum of 32 switches/directors in a single fabric) and do not experience any scaling, stability and other performance issues.The advent of I/O consolidation in enterprise data centers for multiple traffic types to converge on to a single fabric or network (typically Ethernet platform) to reduce hardware, energy and management costs has also the potential to allow implementation of large storage area networks based on the fibre channel standards. Large storage area networks are being planned with more than two hundred switches/directors in a single fabric or network in addition to servers and storages connected to the fabric on Ethernet platforms. Even though these large storage area networks are envisioned to operate on Ethernet platform, they still have to satisfy the stringent operating and performance requirement set forth by the fibre channel standards. The two important issues of concern with large storage area networks are scaling and stability. The scaling and stability issues are dependent on the interactions and performance capabilities of various fabric servers located on each switch/director in the fabric in order to provide fabric services. In order to determine the extent of scaling and stability issues of a large fabric first the detailed models of the switch/director addressing the operations of the individual fabric servers are required. Next, the interactions of the switches/directors using the detailed models are to be simulated to study the scaling and stability issues.In this paper, the detailed modeling of the fibre channel switch and the fabric servers using the OMNeT++ discrete event simulator is presented first. Detailed models are developed addressing the behavior of the switch at the level-2 of the fibre channel protocol since this layer addresses the requirements and operations of various mandatory fabric services like fabric build, directory, login, nameserver, management, etc. Next, using the OMNET++ discrete event simulator large fabrics are simulated. The results from the simulation are compared against the test bed traffic and the accuracy is demonstrated. Also, results and analysis of multiple simulations with increasing fabric size are presented

SAFE: Simulation Automation Framework for Experiments

The workflow of a network simulation study requires adherence to best practices in methodology so that results are credible and reproducible by third parties. The opportunities for one to introduce errors start at model description and permeate the process through to the reporting of results. The literature indicates that even publications in respected venues include inadvertent mistakes and poor application of methodology. When experts are liable to fail, it is unreasonable to expect that students would fare any better. This paper presents a system designed to provide guidance for inexperienced users of the popular ns-3 network simulator. SAFE automates the workflow from the initialization of model parameters, to the parallelized execution of experiments, to the processing and persistent storage of output data, and to graphical visualization of results. We discuss the architecture and the implementation of the system in the context of similar contributions in the literature

Simulating sensor networks

Tese de mestrado em Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2010Nos últimos anos, as redes de sensores sem fios conheceram um grande impulso em variadas ´áreas, nomeadamente na monitorização industrial e ambiental e, mais recentemente, na logística e noutras aplicações que envolvem processos de negócio e a chamada Internet das Coisas e dos Serviços. Contudo, e apesar dos avanços que se têm verificado tanto em termos de hardware como de software, estas redes são difíceis de programar, testar e instalar. A simulação de redes de sensores é frequentemente utilizada para testar e depurar aplicações para redes de sensores, pois permite testar a execução de das aplicações em ambientes virtuais. Esta tese aborda um problema que diz respeito a testar estas redes através de simulação: a definição (manual) de modelos. A nossa abordagem aponta para a geração de modelos de simulação directamente a partir de aplicações redes de sensores, em particular, modelos para o simulador VisualSense criados a partir de aplicações escritas em Callas, uma linguagem de programação para as redes de sensores. Para tal, criamos uma ferramenta capaz de gerar modelos que ´e paramétrica pelos modelos de rede e modelos sensores da rede que se pretende modelar, e ainda por um conjunto extensível de parâmetros de simulação. As nossas experiências mostraram resultados encorajadores na simulação de redes de grande escala, uma vez que conseguimos executar simulações com até 5000 nós. À medida que as redes de sensores sem fios começam a ser utilizadas em processos de negócio, a informação que recolhem do ambiente tem cada vez mais influência no decurso dos fluxos de trabalho associados aos processos de negócio. De um modo geral, os testes levados a cabo em fluxos de trabalho fazem uso de informação gravada em fluxos de trabalho executados previamente, tornando difícil testar o sistema como um todo. Em alternativa, e como uma segunda proposta desta tese, propomos testar fluxos de trabalho através da incorporação de resultados obtidos nas simulações das aplicações das redes de sensores. Além de cobrir os casos cobertos pela primeira abordagem, esta técnica permite testar novos fluxos de trabalho, bem como as mudanças ocorridas num determinado fluxo de trabalho por acontecimentos no ambiente.In recent years, Wireless Sensor Networks have gaining momentum in several fields, notably in industrial and environmental monitoring and, more recently, in logistics. However, and in spite of the advances in hardware and software, Wireless Sensor Networks are still hard to program, test, and deploy. Simulation is often used for testing and debugging sensor networks because they allow us to perform deployments in virtual environments. This paper addresses a key problem of testing such networks using simulation: (manual) model definition. Our approach is to generate simulation models directly from WSN applications, in particular, VisualSense simulator models from applications written in Callas, a programming language for WSN. For that purpose, we create a model generator tool that is parameter sable by network and sensor templates, and by an extensible set of simulation parameters. Our experiments show encouraging results on simulating large scale networks, as we are able to handle WSN with as many as 5000 nodes. As Wireless Sensor Networks begin to play some role in business processes, the information they gather from the environment influences the execution of workflows. Generally, the tests carried out on these systems make use of recorded information in earlier workflow executions, making it difficult to test the system as a whole. Alternatively, and as a second proposal of this thesis, we propose testing such workflows by incorporating results obtained from the simulation of sensor network applications. Besides covering the situations described in the first approach, this technique allows the testing of new workflows, as well as the changes made to a given workflow by events in the environment

Universal Smart Grid Agent for Distributed Power Generation Management

"Somewhere, there is always wind blowing or the sun shining." This maxim could lead the global shift from fossil to renewable energy sources, suggesting that there is enough energy available to be turned into electricity. But the already impressive numbers that are available today, along with the European Union's 20-20-20 goal – to power 20% of the EU energy consumption from renewables until 2020 –, might mislead us over the problem that the go-to renewables readily available rely on a primary energy source mankind cannot control: the weather. At the same time, the notion of the smart grid introduces a vast array of new data coming from sensors in the power grid, at wind farms, power plants, transformers, and consumers. The new wealth of information might seem overwhelming, but can help to manage the different actors in the power grid. This book proposes to view the problem of power generation and distribution in the face of increased volatility as a problem of information distribution and processing. It enhances the power grid by turning its nodes into agents that forecast their local power balance from historical data, using artificial neural networks and the multi-part evolutionary training algorithm described in this book. They pro-actively communicate power demand and supply, adhering to a set of behavioral rules this book defines, and finally solve the 0-1 knapsack problem of choosing offers in such a way that not only solves the disequilibrium, but also minimizes line loss, by elegant modeling in the Boolean domain. The book shows that the Divide-et-Impera approach of a distributed grid control can lead to an efficient, reliable integration of volatile renewable energy sources into the power grid

Gridsim: a flexible simulator for grid integration study

Global warming and the increasing cost of fossil fuels have driven researchers to focus on renewable and cleaner sources of energy like wind, water, and solar. These energy sources show promise for sustainability and reduced greenhouse gas emissions, the only disadvantage of them is that they are intermittent and currently expensive. Measuring the impact of integrating new energy sources into an existing grid system is not feasible. Therefore, Modeling and Simulation becomes an indispensable approach. Several tools exist for modeling and simulation of the power grid. They primarily focus on analyzing smart grids and are complex to use for integration studies. Designing and implementing software that allows the users to model and simulate power grid system for integration study is the primary motivation of this thesis. We propose, GridSim, an easy, intuitive software to perform grid integration analysis and its use is illustrated through case studies.smart gridssimulatorspower grid

A Survey on Industrial Control System Testbeds and Datasets for Security Research

The increasing digitization and interconnection of legacy Industrial Control Systems (ICSs) open new vulnerability surfaces, exposing such systems to malicious attackers. Furthermore, since ICSs are often employed in critical infrastructures (e.g., nuclear plants) and manufacturing companies (e.g., chemical industries), attacks can lead to devastating physical damages. In dealing with this security requirement, the research community focuses on developing new security mechanisms such as Intrusion Detection Systems (IDSs), facilitated by leveraging modern machine learning techniques. However, these algorithms require a testing platform and a considerable amount of data to be trained and tested accurately. To satisfy this prerequisite, Academia, Industry, and Government are increasingly proposing testbed (i.e., scaled-down versions of ICSs or simulations) to test the performances of the IDSs. Furthermore, to enable researchers to cross-validate security systems (e.g., security-by-design concepts or anomaly detectors), several datasets have been collected from testbeds and shared with the community. In this paper, we provide a deep and comprehensive overview of ICSs, presenting the architecture design, the employed devices, and the security protocols implemented. We then collect, compare, and describe testbeds and datasets in the literature, highlighting key challenges and design guidelines to keep in mind in the design phases. Furthermore, we enrich our work by reporting the best performing IDS algorithms tested on every dataset to create a baseline in state of the art for this field. Finally, driven by knowledge accumulated during this survey's development, we report advice and good practices on the development, the choice, and the utilization of testbeds, datasets, and IDSs