The state of peer-to-peer network simulators

Networking research often relies on simulation in order to test and evaluate new ideas. An important requirement of this process is that results must be reproducible so that other researchers can replicate, validate and extend existing work. We look at the landscape of simulators for research in peer-to-peer (P2P) networks by conducting a survey of a combined total of over 280 papers from before and after 2007 (the year of the last survey in this area), and comment on the large quantity of research using bespoke, closed-source simulators. We propose a set of criteria that P2P simulators should meet, and poll the P2P research community for their agreement. We aim to drive the community towards performing their experiments on simulators that allow for others to validate their results

e-Surgeon: Diagnosing Energy Leaks of Application Servers

GreenIT has emerged as a discipline concerned with the optimization of software solutions with regards to energy consumption. In this domain, most of the state-of-the-art solutions concentrate on coarse-grained approaches to monitor the energy consumption of a device or a process. However, none of the existing solutions addresses in-process energy monitoring to provide in-depth analysis of a process energy consumption. In this paper, we therefore report on a fine-grained real-time energy monitoring framework we developed to diagnose energy leaks with a better accuracy than the state-of-the-art. Concretely, our approach adopts a 2-layer architecture including OS-level and process-level energy monitoring. OS-level energy monitoring estimates the energy consumption of processes according to different hardware devices (CPU, network, memory). Process-level energy monitoring focuses on Java-based applications and builds on OS-level energy monitoring to provide an estimation of energy consumption at the granularity of classes and methods. We argue that this per-method analysis of energy consumption provides better insights to the application in order to identify potential energy leaks. In particular, our preliminary validation demonstrates that we can diagnose energy hotspots of Jetty application servers and monitor their variations when stressing web applications.L'informatique verte a émergé comme une discipline qui s'intéresse à l'optimisation des solutions logicielles en ce qui concerne la consommation d'énergie. Dans ce domaine, la plupart des solutions de l'état de l'art se concentre sur des approches à gros grains pour contrôler la consommation énergétique d'un matériel ou un processus. Toutefois, aucune des solutions existantes gère la surveillance au niveau processus afin de fournir une analyse en profondeur de la consommation énergétique d'un processus. Dans ce papier, nous proposons un canevas logiciel à grain fin pour surveiller en temps réel la consommation énergétique des applications, et pour diagnostiquer les fuites d'énergie avec une meilleure précision que l'état de l'art. En particulier, notre approche adopte une architecture à 2 couches, une au niveau du système d'exploitation et le suivi de l'énergie au niveau des processus. La couche de surveillance de l'énergie au niveau de l'OS estime la consommation énergétique au niveau du processus selon différents périphériques matériels (processeur, réseau, mémoire). La couche de surveillance de l'énergie au niveau des processus se concentre sur les applications Java et s'appuie sur la couche OS pour fournir une estimation de la consommation d'énergie à la granularité des classes et méthodes. Nous soutenons que cette analyse au niveau des méthodes de la consommation énergétique fournit un meilleur aperçu de l'application afin d'identifier les fuites énergétiques potentielles. En particulier, nos expériences démontrent que nous pouvons diagnostiquer les hotspots énergétique des serveurs d'application Jetty et de surveiller leurs variations lorsque nous mettons sous pression les applications web

Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

A Developer-Friendly “Open Lidar Visualizer and Analyser” for Point Clouds With 3D Stereoscopic View

Light detection and ranging is being a hot topic in the remote sensing field, and the development of robust point cloud processing methods is essential for the adoption of this technology. In order to understand, evaluate, and show these methods, it is a key to visualize their outputs. Several visualization tools exist, although it is usually difficult to find the suited one for a specific application. On the one hand, proprietary (closed source) projects are not flexible enough because they cannot be modified to adapt them to particular applications. On the other hand, current open source projects lack an effortless way to create custom visualizations. For these reasons, we present Olivia, a developer-friendly open source visualization tool for point clouds. Olivia provides the backbone for any type of point cloud visualization, and it can be easily extended and tailored to meet the requirements of a specific application. It supports stereoscopic 3-D view, aiding both the evaluation and presentation of processing methods. In this paper, several cases of study are presented to demonstrate the usefulness of Olivia along with its computational performance.S

Automated Test Input Generation for Android: Are We There Yet?

Mobile applications, often simply called "apps", are increasingly widespread, and we use them daily to perform a number of activities. Like all software, apps must be adequately tested to gain confidence that they behave correctly. Therefore, in recent years, researchers and practitioners alike have begun to investigate ways to automate apps testing. In particular, because of Android's open source nature and its large share of the market, a great deal of research has been performed on input generation techniques for apps that run on the Android operating systems. At this point in time, there are in fact a number of such techniques in the literature, which differ in the way they generate inputs, the strategy they use to explore the behavior of the app under test, and the specific heuristics they use. To better understand the strengths and weaknesses of these existing approaches, and get general insight on ways they could be made more effective, in this paper we perform a thorough comparison of the main existing test input generation tools for Android. In our comparison, we evaluate the effectiveness of these tools, and their corresponding techniques, according to four metrics: code coverage, ability to detect faults, ability to work on multiple platforms, and ease of use. Our results provide a clear picture of the state of the art in input generation for Android apps and identify future research directions that, if suitably investigated, could lead to more effective and efficient testing tools for Android

An evaluation of galaxy and ruffus-scripting workflows system for DNA-seq analysis

>Magister Scientiae - MScFunctional genomics determines the biological functions of genes on a global scale by using large volumes of data obtained through techniques including next-generation sequencing (NGS). The application of NGS in biomedical research is gaining in momentum, and with its adoption becoming more widespread, there is an increasing need for access to customizable computational workflows that can simplify, and offer access to, computer intensive analyses of genomic data. In this study, the Galaxy and Ruffus frameworks were designed and implemented with a view to address the challenges faced in biomedical research. Galaxy, a graphical web-based framework, allows researchers to build a graphical NGS data analysis pipeline for accessible, reproducible, and collaborative data-sharing. Ruffus, a UNIX command-line framework used by bioinformaticians as Python library to write scripts in object-oriented style, allows for building a workflow in terms of task dependencies and execution logic. In this study, a dual data analysis technique was explored which focuses on a comparative evaluation of Galaxy and Ruffus frameworks that are used in composing analysis pipelines. To this end, we developed an analysis pipeline in Galaxy, and Ruffus, for the analysis of Mycobacterium tuberculosis sequence data. Furthermore, this study aimed to compare the Galaxy framework to Ruffus with preliminary analysis revealing that the analysis pipeline in Galaxy displayed a higher percentage of load and store instructions. In comparison, pipelines in Ruffus tended to be CPU bound and memory intensive. The CPU usage, memory utilization, and runtime execution are graphically represented in this study. Our evaluation suggests that workflow frameworks have distinctly different features from ease of use, flexibility, and portability, to architectural designs