Online Collaborative Environment for Designing Complex Computational Systems

Maróti, Miklós; Kereskényi, Róbert; Kecskes, Tamas; Völgyesi, Péter; Lédeczi, Ákos

doi:10.1016/j.procs.2014.05.227

Cited by 32 publications

(14 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Users select models from a library and build their application by composing the models on a visual canvas. Preliminary work has been done in creating this design environment using the Web-based Generic Modeling Environment (WebGME) [21]. Using this web-based tool, users can create TinyOS applications by wiring together components and writing implementations (TinyOS modules) with a text editor provided by the tool.…”

Section: Discussionmentioning

confidence: 99%

Toward rapid prototyping of miniature Capsule Robots

Taddese

Beccani

Susilo

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

Abstract-Minimally invasive robotic surgery techniques are becoming popular thanks to their enhanced patient benefits, including shorter recovery time, better cosmetic results and reduced discomforts. Less invasive procedures would be achieved with the use of Medical Capsule Robots (MCRs). These devices are characterized by low power requirements and small dimensions as well as uncompromising safety. MCRs operate wirelessly in abdominal Minimally Invasive Surgery (MIS) and Natural Orifice Transluminal Endoscopic Surgery (NOTES) or in the Gastrointestinal (GI) tract. The design process of MCRs, however, is expensive and time consuming. A platform for rapid prototyping MCRs is needed so that MCR researchers can reduce development costs and spend more time in studying innovative MCR applications. In this work, we introduce an open source modular platform geared toward rapid prototyping MCRs. To speed up the prototyping process, the MCR is programmed using TinyOS instead of bare-bone C. We present the hardware architecture of the platform, and the motivation for using TinyOS. To show the viability of TinyOS, we present results from an experiment involving sensing, actuation and wireless communication. This work lays the foundation for our future goal of building an integrated design environment for the design, analysis and simulation of MCRs.

show abstract

Section: Discussionmentioning

confidence: 99%

Toward rapid prototyping of miniature Capsule Robots

Taddese

Beccani

Susilo

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

show abstract

“…the metamodel [14]. The client models the deployment situation by utilizing the natural reflections utilizing the Stratum GUI.…”

Section: Proposition Work: Plan and Implementation Of Stratummentioning

confidence: 99%

“…As portrayed in Figure 2a, utilizing the visual interface of Stratum the application designer can build up the data analytics application. As portrayed in our past work [14], the business application work process is planned by hauling and associating the specific structure obstructs for application parts and foundation segments. As appeared in Figure 1, by parsing the client characterized dynamic model tree, the Stratum DSML makes the deployable model (Ansible-specific for our situation) and utilizing NodeJS based module to execute the deployable model and make the framework of the application as depicted in Section.…”

Section: Bassessment Of Rapid Application Prototyping Frameworkmentioning

confidence: 99%

A Comprehensive Study on Design and Implementation of Bigdata-As-A-Service Stratum of Lifecycle Management of Smart Internet of Things Applications

babu¹

2020

IJMTST

View full text Add to dashboard Cite

Smart IoT systems require real-time and robust predictive analytics based on Machine Learning (ML) models. Building Big Data ML models is not only time consuming, but developers also lack the skills required for feature engineering, parameter tuning and model selection.The abundance of ML libraries and systems , data ingestion software, stream and batch processing engines, simulation technologies, and the number of hardware platforms accessible further exacerbates device architecture, fast development, and implementation issues. Finally, IoT's resource limitations demand that analytics engine execution be spread around the cloud edge spectrum. In order to address these challenging obstacles, we deliver Stratum, an event-driven Big Data-as-a-Service solution for IoT Lifecycle Analytics Management. Stratum provides developers with an elegant, declarative process, based on the model-driven architecture philosophy, to define device and network specifications. This paper illustrates the challenges Stratum is tackling, explaining its strengths through case studies in the modern world.

show abstract

“…As shown in Fig. 3, the platform utilizes a web-based metamodeling framework, called WebGME [8], to provide a graphical modeling language for designing power-grids based on concepts from the GridLAB-D simulator. The language also allows modeling different market approaches and attack configurations.…”

Section: A Overviewmentioning

confidence: 99%

Web-Based Platform for Evaluation of Resilient and Transactive Smart-Grids

Neema

Vardhan

Barreto

et al. 2019

2019 7th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES)

View full text Add to dashboard Cite

Today's smart-grids have seen a clear rise in new ways of energy generation, transmission, and storage. This has not only introduced a huge degree of variability, but also a continual shift away from traditionally centralized generation and storage to distributed energy resources (DERs). In addition, the distributed sensors, energy generators and storage devices, and networking have led to a huge increase in attack vectors that make the grid vulnerable to a variety of attacks. The interconnection between computational and physical components through a largely open, IP-based communication network enables an attacker to cause physical damage through remote cyberattacks or attack on software-controlled grid operations via physical-or cyber-attacks. Transactive Energy (TE) is an emerging approach for managing increasing DERs in the smart-grids through economic and control techniques. Transactive Smart-Grids use the TE approach to improve grid reliability and efficiency. However, skepticism remains in their full-scale viability for ensuring grid reliability. In addition, different TE approaches, in specific situations, can lead to very different outcomes in grid operations. In this paper, we present a comprehensive web-based platform for evaluating resilience of smart-grids against a variety of cyber-and physical-attacks and evaluating impact of various TE approaches on grid performance. We also provide several case-studies demonstrating evaluation of TE approaches as well as grid resilience against cyber and physical attacks.

show abstract

Online Collaborative Environment for Designing Complex Computational Systems

Cited by 32 publications

References 8 publications

Toward rapid prototyping of miniature Capsule Robots

Toward rapid prototyping of miniature Capsule Robots

A Comprehensive Study on Design and Implementation of Bigdata-As-A-Service Stratum of Lifecycle Management of Smart Internet of Things Applications

Web-Based Platform for Evaluation of Resilient and Transactive Smart-Grids

Contact Info

Product

Resources

About