A Real-Time Container Architecture for Dependable Distributed Embedded Applications

The improved particle filter based simultaneous localization and mapping (SLAM) has been developed for many robotic applications. The main purpose of this article is to demonstrate that recent heterogeneous architectures can be used to implement the FastSLAM2.0 and can greatly help to design embedded systems based robot applications and autonomous navigation. The algorithm is studied, optimized and evaluated with a real dataset using different sensors data and a hardware in the loop (HIL) method. Authors have implemented the algorithm on a system based embedded applications. Results demonstrate that an optimized FastSLAM2.0 algorithm provides a consistent localization according to a reference. Such systems are suitable for real time SLAM applications.

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CompactRIO Based Real Time Implementation of AES Algorithm for Embedded Applications

International Journal of Embedded and Real-Time Communication Systems ◽

10.4018/ijertcs.2019040102 ◽

2019 ◽

Vol 10 (2) ◽

pp. 19-36

Author(s):

El Adib Samir ◽

Raissouni Naoufal

Keyword(s):

Power Consumption ◽

Real Time ◽

Software Design ◽

System Architecture ◽

Advanced Encryption Standard ◽

Time Cost ◽

Security Applications ◽

Aes Algorithm ◽

Embedded Applications ◽

Different Levels

For real-time embedded applications, several factors (time, cost, power) that are moving security considerations from a function-centric perspective into a system architecture (hardware/software) design issue. The National Institute of Standards and Technology (NIST) adopts Advanced Encryption Standard (AES) as the most widely used encryption algorithm in many security applications. The AES algorithm specifies 10, 12 and 14 rounds offering different levels of security. Although the number of rounds determines the strength of security, the power consumption issue has risen recently, especially in real-time embedded systems. In this article, the authors present real time implementation of the AES encryption on the compactRIO platform for a different number of AES rounds. The target hardware is NI cRIO-9022 embedded real-time controller from National Instruments (NI). The real time encryption processing has been verified successfully. The power consumption and encryption time experimental results are presented graphically for 10, 12 and 14 rounds of processing.

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Embedded Real-Time Linux for Cable Robot Control

Volume 1: 22nd Computers and Information in Engineering Conference ◽

10.1115/detc2002/cie-34506 ◽

2002 ◽

Cited By ~ 4

Author(s):

Frederick M. Proctor ◽

William P. Shackleford

Keyword(s):

Open Source ◽

Real Time ◽

Open Source Software ◽

Hard Disk Drives ◽

Source Model ◽

Disk Drives ◽

Deterministic Scheduling ◽

Cable Robot ◽

Real Time Computing ◽

Embedded Applications

Linux is a version of the Unix operating system distributed according to the open source model. Programmers are free to adapt the source code for their purposes, but are required to make their modifications or enhancements available as open source software as well. This model has fostered the widespread adoption of Linux for typical Unix server and workstation roles, and also in more arcane applications such as embedded or real-time computing. Embedded applications typically run in small physical and computing footprints, usually without fragile peripherals like hard disk drives. Special configurations are required to support these limited environments. Real-time applications require guarantees that tasks will execute within their deadlines, something not possible in general with the normal Linux scheduler. Real-time extensions to Linux enable deterministic scheduling, at task periods at tens of microseconds. This paper describes embedded and real-time Linux, and an application for distributed control of a Stewart Platform cable robot. Special Linux configuration requirements are detailed, and the architecture for teleoperated control of the cable robot is presented, with emphasis on the resolved-rate control of the suspended platform.

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Real-time accelerometer coupled Self-Mixing laser displacement sensor for embedded applications

2012 IEEE Sensors ◽

10.1109/icsens.2012.6411493 ◽

2012 ◽

Cited By ~ 2

Author(s):

U. Zabit ◽

O. D. Bernal ◽

A. Chamorro-Coloma ◽

T. Bosch ◽

U. Zabit ◽

...

Keyword(s):

Real Time ◽

Displacement Sensor ◽

Laser Displacement Sensor ◽

Embedded Applications

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A hybrid real-time agent platform for fault-tolerant, embedded applications

Autonomous Agents and Multi-Agent Systems ◽

10.1007/s10458-017-9378-4 ◽

2017 ◽

Vol 32 (2) ◽

pp. 252-274 ◽

Cited By ~ 2

Author(s):

A. O. Erlank ◽

C. P. Bridges

Keyword(s):

Real Time ◽

Fault Tolerant ◽

Agent Platform ◽

Embedded Applications

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Towards Fully Jitterless Applications: Periodic Scheduling in Multiprocessor MCSs Using a Table-Driven Approach

Applied Sciences ◽

10.3390/app10196702 ◽

2020 ◽

Vol 10 (19) ◽

pp. 6702

Author(s):

Eugenia Ana Capota ◽

Cristina Sorina Stangaciu ◽

Mihai Victor Micea ◽

Daniel-Ioan Curiac

Keyword(s):

Real Time ◽

Multiprocessor Systems ◽

Preemptive Scheduling ◽

Algorithm Performance ◽

Safety Critical ◽

Time Table ◽

Scheduling Method ◽

Embedded Applications ◽

Special Case ◽

Mixed Criticality

In mixed criticality systems (MCSs), the time-triggered scheduling approach focuses on a special case of safety-critical embedded applications which run in a time-triggered environment. Sometimes, for these types of MCSs, perfectly periodical (i.e., jitterless) scheduling for certain critical tasks is needed. In this paper, we propose FENP_MC (Fixed Execution Non-Preemptive Mixed Criticality), a real-time, table-driven, non-preemptive scheduling method specifically adapted to mixed criticality systems which guarantees jitterless execution in a mixed criticality time-triggered environment. We also provide a multiprocessor version, namely, P_FENP_MC (Partitioned Fixed Execution Non-Preemptive Mixed Criticality), using a partitioning heuristic. Feasibility tests are proposed for both uniprocessor and homogenous multiprocessor systems. An analysis of the algorithm performance is presented in terms of success ratio and scheduling jitter by comparing it against a time-triggered and an event-driven method in a non-preemptive context.

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