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Researchers in the real-time community have accumulated an enormous theoretical background on scheduling policies and respective assessment criteria. Lots of surveys and textbooks are available which classify the varying approaches. In contrast to this abundance of policies and strategies the availability of real-time scheduling for given platforms is rather low. Still more frustrating is the lack...
CPU-GPU heterogeneous systems have become a mainstream platform in both server and embedded domains with ever increasing demand for powerful accelerator. In this paper, we present parallelization techniques that exploit both data and task parallelism of LBP based face detection algorithm on an embedded heterogeneous platform. By running tasks in a pipelined parallel way on multicore CPUs and by offloading...
Implementation of a frequency measurement device based on ARM-embedded computer viz. Raspberry Pi is presented. This device is used as a part of a wide area frequency measurement system implemented at Indian Institute of Technology Bombay. Free and open source software is used including Linux based operating system patched with a realtime development framework. This serves as a low-cost high performance...
Retinal blood vessels damaged from diabetic retinopathy can cause vision loss. Diabetic Retinopathy (DR) detection, poor quality retinal image makes more difficult the analysis for ophthalmologist. In this paper presents a new automatic method of blood vessels extraction with a real time process using optimized matched filter with minimum cross entropy threshold. Minimum cross entropy threshold is...
This 1-Page Demonstration paper is included in the track “Multimedia Systems and Applications”. The work has been already published in [1] and [2]. The main idea of the demonstration is to show how the Virtual Architecture ARTICo3 works within a high performance wireless sensor node called HiReCookie. The selected demo includes an image processing application with several filters running as different...
The use of real-time operating systems for small micro controllers creates two major problems. The former refers to the way interruptions must be handled so that deadlines can be complied with. The latter regards the fact that there may be tasks that will not synchronize with events generated by multiple objects such as semaphores, mutexes, messages or interrupts. The present article discusses several...
With the advent of large high volume data, we have seen need for real time analytic techniques like Complex Event Processing. This paper extends a Complex Event Processing Engine to support real time identification of technical chart patterns from streaming data. Technical chart patterns are known interesting recurring patterns on time series data, and they are used by experts in time series data...
Ultrasonic imaging applications require real-time acquisition and processing of huge volume of data. Subsequently, reducing the data storage becomes an essential requirement for applications involving ultrasound technology. Compression of the acquired data significantly reduces the storage and also helps in faster data processing. Furthermore, computationally efficient data compression enables real-time...
Predicting performance metrics for cloud services is critical for real-time service assurance. We demonstrate a platform for estimating real-time service-level metrics. Statistical learning methods on device statistics are used to predict metrics for services running on these devices.
Recent Graphics Processing Units (GPUs) have employed cache memories to boost performance. However, cache memories are well known to be harmful to time predictability for CPUs. For high-performance real-time systems using GPUs, it remains unknown whether or not cache memories should be employed. In this paper, we quantitatively compare the performance for GPUs with and without caches, and find that...
In this paper, we propose an accurate approximation framework for separable edge-preserving filtering. Naïve implementation of edge-preserving filtering, such as bilateral filtering and non-local means filtering, consumes enormous computational costs. Separable implementation of such filters is an efficient approximation method for real-time filtering. The accuracy of the conventional separable representation,...
Future generations of mobile phones, including advanced video and digital communication layers, represent a great challenge in terms of real-time embedded systems. Programmable multicomponent architectures can provide suitable target solutions combining flexibility and computation power. The aim of our work is to develop a fast and automatic prototyping methodology dedicated to signal processing application...
Performance analysis of a process plays a significant role in improving the overall efficiency of any system. Usually, this task is accomplished either by system level commands or user space applications, based on proc file system. These existing user space based mechanisms are limited in application and often fail to provide the required process specific data to user. In order to avoid this limitation,...
Many-core systems are increasingly used in real-time settings to meet the performance requirements of advanced applications such as the classification and tracking of dynamic objects for autonomous driving [1] or the generation of safe trajectories through rough terrain [2]. Task sets of these applications are often mixtures of short running, low latency tasks, such as the various filtering steps...
As virtualization technology becomes ever more capable, large-scale distributed applications are increasingly deployed in virtualized environments such as data centers and computational clouds. Many large-scale applications have soft real-time requirements and benefit from low and predictable latency, even in the presence of diverse traffic patterns between virtualized hosts. In this paper, we examine...
Graphics processing units (GPUs) are being widely used as co-processors in many application domains to accelerate general-purpose workloads that are computationally intensive, known as GPGPU computing. Real-time multi-tasking support is a critical requirement for many emerging GPGPU computing domains. However, due to the asynchronous and non-preemptive nature of GPU processing, in multi-tasking environments,...
In heterogeneous computing systems MinMin and MaxMin are widely used in assigning independent tasks to processors. For N tasks to be assigned to N processors these approaches are known to run in O (KN2) time. An algorithmic improvement that asymptotically decreases the running time complexity of MinMin to O(KN logN) without affecting its solution quality is proposed in [1]. The newly proposed MinMin...
This paper targets to relate the latency and performance among the Linux CAN drivers that is Socket CAN and RTCAN which are the open source CAN drivers. Linux is one of the open source kernel which is moreover a cost effective and is the best alternative compared with other expensive patented RTOS. Socket CAN is added to Linux kernel mainline which is idealized by most CAN developers, however RTCAN...
Developing correct, efficient, and maintainable real-time control software for cyber-physical systems is a notoriously difficult interdisciplinary challenge. Ever more complex control algorithms and the advent of multi-core hardware in embedded systems have made this challenge even harder. Component-based software development promises to help reduce the complexity and to increase the timing predictability...
People tracking is a crucial component of many intelligent video surveillance systems and recent developments in embedded computing architectures and algorithms allow us to design compact, lightweight and energy efficient systems aimed at tackling this problem. In particular, the advent of cheap RGBD sensing devices enables to exploit depth information as additional cue. In this paper we propose a...
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