This paper presents Real-Time Network-on-chip-based architecture Analysis and Simulation tool (ReTiNAS), with a special focus on real-time communications. It allows fast and precise exploration of real-time design choices onto NoC architectures. ReTiNAS is an event-based simulator written in Python. It implements different real-time communication protocols and tracks the communications within the NoC at cycle level. Its modularity allows activating and deactivating different NoC components and easily extending the implemented protocols for more customized simulations and analysis. Further, we use ReTiNAS to perform a comparative study of analysis and simulation for different communication protocols using a wide set of synthetic experiments.
The authors developed a mobile cloud-based clinical decision support system for drug poisoning in children. The system has a Client/Server architecture and provides a mobile application and a web service to be deployed on the Amazon Cloud infrastructure. Physicians benefit from a user interface to input patient data and to receive diagnosis and treatment protocol. The objective of this article is to help doctors, and particularly the beginners to manage and to treat children suffering from drug poisoning when toxicity is known or unknown. To do this, an intelligent system is developed. It is composed of an expert system, used when the toxic drug is known, and a case-based reasoning system applied when the toxic being ingested is unknown
The authors developed a mobile cloud-based clinical decision support system for drug poisoning in children. The system has a Client/Server architecture and provides a mobile application and a web service to be deployed on the Amazon Cloud infrastructure. Physicians benefit from a user interface to input patient data and to receive diagnosis and treatment protocol. The objective of this article is to help doctors, and particularly the beginners to manage and to treat children suffering from drug poisoning when toxicity is known or unknown. To do this, an intelligent system is developed. It is composed of an expert system, used when the toxic drug is known, and a case-based reasoning system applied when the toxic being ingested is unknown
The Network-on-Chip (NoC) provides a viable solution to bus-contention problems in classical Multi/Many core architectures. However, NoC complex design requires particular attention to support the execution of real-time workloads. In fact, it is necessary to take into account task-to-core allocation and inter-task communication, so that all timing constraints are respected. The problem is more complex when considering task-to-main-memory communication, as the main memory is off-chip and usually connected to the network edges, within the 2D-Mesh topology, which generates a particular additional pattern of traffic. In this paper, we tackle these problems by considering the allocation of tasks and inter-taskcommunications, and memory-to-task communications (modeled using Directed Acyclic Graphs DAGs) at the same time, rather than separating them, as it has been addressed in the literature of real-time systems. This problem is highly combinatorial, therefore our approach transforms it at each step, to a simpler problem until reaching the classical single-core scheduling problem. The goal is to find a trade-off between the problem combinatorial explosion and the loss of generality when simplifying the problem. We study the effectiveness of the proposed approaches using a large set of synthetic experiments.
In this paper, we address the problem of analyzing the behavior of a set of real-time tasks on a Network-on-chipbased (NoC) architecture. Our approach is to transform the allocation of tasks and communications within a NoC into a classical real-time allocation problem. It provides an extension of classical bin-packing heuristics to allocate a set of real-time applications modeled using a directed acyclic graphs (DAGs) to a set of processors interconnected through a NoC.The paper describes the schedulability analysis, including allocation and communication. It provides also a comparative study of different allocation and communication algorithms and presents accordingly a set of promising research insights.
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