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In this paper we discuss a multi-agent cooperative approach for decentralized, coordinated traffic systems. Intersection controllers are equipped with agents, i.e., autonomous software systems which are capable of communicating and cooperating with one another to achieve an individual or global goal. Our approach is based on real-world traffic parameters and constraints, and is meant to be implemented...
Data visualization is an important aspect of data analytics in an age where decisions are all based on information. Approaches in data visualization, particularly those that have the capability of processing large-scale textual datasets and visualize them as structured information in real-time can be useful for monitoring trends in social media. In this article, we present our GPU accelerated project,...
Real time mobile Health applications highly depend on sensor readings to provide high-quality health services. However, real-time sensor readings may be inaccurate and cause abnormal physiological measurements due to internal and external factors. Thus, abnormal readings have a significant impact on the reliability of such applications and consequently affect the patient's life. This paper addresses...
As cloud computing continues to gain momentum, big data analytics are now offered as Software as a Service (SaaS). Besides the heterogeneity and multi-tenancy of the underlying virtualized environment, scheduling such real-time, data-intensive, embarrassingly parallel applications in a SaaS cloud involves another serious challenge: data locality. Consequently, data-aware scheduling policies should...
In this paper we propose event goodput, i.e., the fraction of events which may be successfully managed by a system, as a relevant metric to describe the performance of battery powered real-time sensor networks. Unlike other performance metrics as response, completion, maximum lateness times, all representing fundamental, but different, figures of merit for the description of the behavior of real-time...
Real-time prediction of the air contaminant dispersion is an important issue in hazard assessment and emergency management of air pollution. The conventional atmospheric simulation can seldom give the precise prediction results due to inaccurate input parameters. To improve the accuracy of the prediction of atmospheric model, a real-time data driven atmospheric dispersion simulation based on data...
Time-Sensitive Networking (TSN) is becoming more important in automotive and industrial sectors. There is no clear strategy how to use TSN to improve and migrate the established real-time protocols without excluding legacy devices. This paper presents a realistic concept to integrate TSN into automation networks. We choose Sercos as a deterministic Industrial-Ethernet protocol to be extended with...
Vehicle-to-vehicle (V2V) communication technology based on Wi-Fi technology has recently been used to prevent vehicles from colliding with each other. However, in V2V communications, radio waves cannot be diffracted well enough at intersections at which vehicles cannot detect each other. Therefore, such technology might not prevent traffic accidents from occurring. In this study, we used mobile networks...
The paper presents recent technological advancements that have been made by Siemens PLM in its simulation tools for multi-body analyses and multi-physics simulation in order to run physics-based high fidelity models in real-time. The motivation is enable reuse of simulation models developed during the engineering phase during the validation phase with hardware or humans in the loop. To demonstrate...
This paper proposes an approach to modelling and analysis of distributed real-time actor systems, which is based on the Uppaal statistical model checker (SMC). SMC was chosen because it automatizes simulations, offers a temporal logic language to formalize specifications and exploits statistical techniques to infer quantitative measures about a model. The approach is integrated in a system life-cycle...
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