Real-time Application Domains Research Articles

Attenuating majority attack class bias using hybrid deep learning based IDS framework

In real-time application domains, like finance, healthcare and defence, delay in service or stealing information may lead to unrecoverable consequences. So, early detection of intrusion is important to prevent security breaches. In recent days, anomaly-based intrusion detection using Hybrid Deep Learning approaches are becoming more popular. The most used benchmark datasets in the literature are NSL-KDD and UNSW-NB15, and these datasets are imbalanced. The models built on imbalanced datasets may lead to biased results towards majority classes by neglecting the minority class, even though they are equally important. In many cases, high accuracy is achieved for majority classes in the imbalanced datasets. But, the class-level performances are poor with respect to the minority class. The class balancing will also play an important role in attenuating the bias in prediction for imbalanced datasets. In this paper, a Hybrid Deep Learning Based Intrusion Detection (HDLBID) framework is proposed with CNN-BiLSTM combination. The four techniques, namely, Random Oversampling (ROS), ADASYN, SMOTE, and SMOTE-Tomek, are used for class balancing in the proposed HDLBID framework. The proposed HDLBID with SMOTE-Tomek achieves an overall accuracy of 99.6% with NSL-KDD and 89.02% for UNSW-NB15. It results in an improvement of 13.67% for NSL-KDD and 10.62% for UNSW-NB15 over the existing recent related models. In the proposed HDLBID, in addition to overall accuracy, the class-level F1 score is also calculated. A comparative study is presented to show the effectiveness of balancing dataset compared to imbalanced dataset, and observed that the SMOTE-Tomek class balancing comparatively performed well. An improvement of 37.43% is observed in the U2R class of the NSL-KDD dataset and 61.65% improvement is seen in the Worms class of the UNSW-NB15 dataset, both with SMOTE-Tomek class balancing. Therefore, the proposed HDLBID with SMOTE-Tomek class balancing reports the best results in terms of overall accuracy compared to existing recent related approaches. Also, in terms of class-level analysis, HDLBID reports best results with SMOTE-Tomek over imbalanced version of datasets.

Inculcation of Life Philosophy through DSP Concepts

Engineering education is a training that encompass learning the theoretical knowledge of concepts, and real time application domains. The role of engineering is also bound by ethical values and the understanding of social and cultural values. In this context a new approach has been designed to facilitate learning of life philosophies through Digital Signal Processing (DSP) concepts. To facilitate learning process, skits based on core DSP concepts were developed using simple day to day tools and performed with learners. The concept was introduced with simple analogies. Then students were made to participate in skits corresponding to key concepts. After the skits, learners were educated about the correlation with Life philosophies. Three case studies were taken up for this study. We found that the inculcation of life philosophies through simple skits, helped learners better to understand the concepts as well the moral values of life.

MISS-D: A fast and scalable framework of medical image storage service based on distributed file system

Background and Objective Processing of medical imaging big data is deeply challenging due to the size of data, computational complexity, security storage and inherent privacy issues. Traditional picture archiving and communication system, which is an imaging technology used in the healthcare industry, generally uses centralized high performance disk storage arrays in the practical solutions. The existing storage solutions are not suitable for the diverse range of medical imaging big data that needs to be stored reliably and accessed in a timely manner. The economical solution is emerging as the cloud computing which provides scalability, elasticity, performance and better managing cost. Cloud based storage architecture for medical imaging big data has attracted more and more attention in industry and academia.Methods This study presents a novel, fast and scalable framework of medical image storage service based on distributed file system. Two innovations of the framework are introduced in this paper. An integrated medical imaging content indexing file model for large-scale image sequence is designed to adapt to the high performance storage efficiency on distributed file system. A virtual file pooling technology is proposed, which uses the memory-mapped file method to achieve an efficient data reading process and provides the data swapping strategy in the pool.Result The experiments show that the framework not only has comparable performance of reading and writing files which meets requirements in real-time application domain, but also bings greater convenience for clinical system developers by multiple client accessing types. The framework supports different user client types through the unified micro-service interfaces which basically meet the needs of clinical system development especially for online applications. The experimental results demonstrate the framework can meet the needs of real-time data access as well as traditional picture archiving and communication system.Conclusions This framework aims to allow rapid data accessing for massive medical images, which can be demonstrated by the online web client for MISS-D framework implemented in this paper for real-time data interaction. The framework also provides a substantial subset of features to existing open-source and commercial alternatives, which has a wide range of potential applications.

Electromagnetic articulography (EMA) for real-time feedback application: computational techniques

The application of state-of-the-art signal processing often differs between offline and online real-time application domains. Offline processing techniques may be used to accurately reduce signal noise and spot errors before analysis. However, without the global signal information available to offline processes, such techniques can be difficult to reproduce in online real-time applications. This paper presented methods that were developed to support a state-of-the-art computer-based speech therapy system. These methods included online head correction and low-pass filtering and aimed to reproduce offline processing data quality when using a real-time clinical feedback application. The adequacy of these methods was evaluated relative to the offline processing ‘gold’ standard and in a context of computing a specific kinematic parameter (i.e. articulatory working space). The results showed that the online real-time output values were highly correlated with the offline manually-processed values.

Enhanced Preemptive Global Utility Accrual Real Time Scheduling Algorithms in Multicore Environment

This paper proposed an efficient real time scheduling algorithm using global scheduling paradigm running in multicore environment known as Global Preemptive Utility Accrual Scheduling (GPUAS) algorithm. The existing TUF/UA multiprocessor scheduling algorithms known as Greedy-Global Utility Accrual (G-GUA) and Non Greedy-Global Utility Accrual (NG-GUA) algorithms is seen to overlook the efficiency on its task scheduling algorithm. These algorithms have adapted the task migration attribute considering the load balancing problem in multi core platform. The existing PUAS uniprocessor scheduling algorithm is mapped into the multicore scheduling environment that consists of the global scheduling schemes considering the migration attribute of the executed tasks. The main principal of global scheduling is that it allows the executed tasks to migrate from one processor to the other processors whenever a scheduling event occurs in the system. The proposed GPUAS algorithm inherits the characteristics of PUAS in uniprocessor where it can preempt the highest PUD task at any event that occurs in the system. In this research, the proposed GPUAS algorithm enhanced the existing NG-GUA and G-GUA algorithms. The developed simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. The proposed GPUAS algorithm achieved the highest accrued utility for the entire load range. The proposed GPUAS algorithm is more efficient than the existing algorithms, producing the highest accrued utility ratio and less abortion ratio making it more suitable and efficient for real time application domain.

Spatial and temporal isolation of virtual CAN controllers

Virtualization is a key technology to enable the use of multi-core processors in automotive embedded systems. For side-by-side execution of mixed-criticality applications that access shared communication infrastructures, a secure and safe virtualization of I/O devices is required, which features a complete spatial and temporal isolation of individual virtual interfaces. We extended existing approaches of hardware-based CAN virtualization to achieve a full isolation while maintaining the bounded latencies achieved in previous implementations. It is shown, that even a denial-of-service attack towards one virtual controller does not influence the behavior of other virtual controllers. In addition, the scheduling mechanism implemented to guarantee temporal isolation can be configured to provide differentiated service levels for real-time and best effort application domains.

A Discrete Event Simulation Framework for Utility Accrual Scheduling Algorithm in Uniprocessor Environment

Problem statement: The heterogeneity in the choice of simulation platforms for real time scheduling stands behind the difficulty of developing a common simulation environment. A Discrete Event Simulation (DES) for a real time scheduling domain encompassing event definition, time advancing mechanism and scheduler has yet to be developed. Approach: The study focused on the proposed and the development of an event based discrete event simulator for the existing General Utility Scheduling (GUS) to facilitate the reuse of the algorithm under a common simulation environment. GUS is one of the existing TUF/UA scheduling algorithms that consider the Time/Utility Function (TUF) of the executed tasks in its scheduling decision. The scheduling optimality criteria are based on maximizing accrued utility accumulated from execution of all tasks in the system. These criteria are named as Utility Accrual (UA). The TUF/ UA scheduling algorithms are design for adaptive real time system environment. The developed GUS simulator has derived the set of parameter, events, performance metrics and other unique TUF/UA scheduling element according to a detailed analysis of the base model. Results: The Accrued Utility Ratio (AUR) is investigated and compared to the benchmark of the modeled domain. Successful deployment of the GUS simulator was proven by the generated results. Conclusion: Extensive performance analysis of GUS simulator can be deployed using the developed simulator with low computational overhead. Further enhancements were to extend the developed GUS simulator with detail performance metrics together with a fault tolerance mechanism to support a reliable real time application domain.

An Architecture-Based Adaptation Framework for Soft Real-Time Applications

Real-time systems are increasingly used in dynamic changing environments with variable user needs hosting real-time applications ranging in number and nature over time. However, to the authors’ knowledge, no unified framework exists that is able to cope with those competing real-time concerns across multiple real-time application domains. This paper proposes an architecture-based framework for managing real-time components’ dependence and lifecycle in an effective and uniform way. A real-time component runtime service is proposed here to maintain the global view, control the whole lifecycle of the components, and keep existing real-time components’ promised contracts in the face of run-time changes. This framework is designed to be easily extended with other constraint resolving policies as well as dependence descriptions languages. At end of this paper, the framework is tested by a simulated control application via adaptation and performance aspects.

Run-time Spatial Mapping of Streaming Applications to Heterogeneous Multi-Processor Systems

In this paper, we define the problem of spatial mapping. We present reasons why performing spatial mappings at run-time is both necessary and desirable. We propose what is—to our knowledge—the first attempt at a formal description of spatial mappings for the embedded real-time streaming application domain. Thereby, we introduce criteria for a qualitative comparison of these spatial mappings. As an illustration of how our formalization relates to practice, we relate our own spatial mapping algorithm to the formal model.

Enhanced Utility Accrual Scheduling Algorithms for Adaptive Real Time System

Problem statement: This study proposed two utility accrual real time scheduling algorithms named as Preemptive Utility Accrual Scheduling (PUAS) and Non-preemptive Utility Accrual Scheduling (NUAS) algorithms. These algorithms addressed the unnecessary abortion problem that was identified in the existing algorithm known as General Utility Scheduling (GUS). It is observed that GUS is inefficient for independent task model because it simply aborts any task that currently executing a resource with lower utility when a new task with higher utility requests the resource. The scheduling optimality criteria are based on maximizing accrued utility accumulated from execution of all tasks in the system. These criteria are named as Utility Accrual (UA). The UA scheduling algorithms are design for adaptive real time system environment where deadline misses are tolerable and do not have great consequences to the system. Approach: We eliminated the scheduling decision to abort a task in GUS and proposed to preempt a task instead of being aborted if the task is preemptive able. We compared the performances of these algorithms by using discrete event simulation. Results: The proposed PUAS algorithm achieved the highest accrued utility for the entire load range. This is followed by the NUAS and GUS algorithms. Conclusion: Simulation results revealed that the proposed algorithms were more efficient than the existing algorithm, producing with higher accrued utility ratio and less abortion ratio making it more suitable and efficient for real time application domain.

A time-predictable VLIW processor and its compiler support

Time predictability is an important requirement for real-time embedded application domains such as automotive, air transportation, and multimedia processing. However, the architectural design of mo...

Adaptive variable structure control of a class of non-linear systems

The problem of tuning the parameters of a controller operating in the presence of noise, time-varying parameters, non-linearities, and uncertainties in practice requires the process of continuous adjustment of the parameters influencing the performance. When the diversity of the challenges in the domain of real-time applications is taken into consideration, it becomes apparent that the adopted controller structure must be sufficiently flexible, and its operating principles must be well explained, particularly in accounting for the stability issues. In this paper, a method is proposed for tuning the parameters of controllers whose outputs are linear in the adjustable parameters, utilizing variable structure systems theory. The method discussed constructs the best error measure at the controller output, and uses this quantity with a suitably designed tuning law, which drives the system under control to a predefined sliding regime and maintains the sliding mode. It is shown analytically that the parametric evolution takes place in a finite volume space, indicating that the controller parameters evolve bounded. In the simulation studies, the approach presented has been tested on the control of a double pendulum system and the superior performance of the strategy has been shown under the existence of noisy observations and large non-zero initial errors.

Sliding Time Interval based MAC Protocol and its temporal validation.

In the context of distributed systems, the communication requirements are very different depending on the supported application, the system topology and the environment. The functional electrical stimulation is a critical and real time application domain: communications have to be safe (no loss, neither long nor unexpected delay). Therefore, an important part of this system from an efficiency point of view is the medium access mechanism. To fit with the specific constraints of our context, a new MAC protocol has been designed: STIMAP (Sliding Time Interval based Medium Access Protocol). This article presents a formal validation of this new protocol, allowing the validation of its behavior in an exhaustive way. Copyright © 2007 IFAC

SOCKET-BASED CAN SUPPORT FOR EMBEDDED OPERATING SYSTEMS

The Controller Area Network (CAN) has been adopted as the network communication technology of choice in many real-time application domains. Due to the ever increasing sophistication of contemporary embedded controllers, it becomes both possible and convenient to access this kind of network by means of a well-known and standard application programming interface instead of resorting to an ad hoc framework. This paper describes the addition of CAN support to the eCos embedded real-time operating system, from the device interface layer up to the extension of its network communication modules, based on Berkeley sockets.

A Novel Real Time Scheduling Frame-work for CORBA-Based Applications.

Many real-time application domains can benefit from flexible and open distributed architectures, such as those defined by the CORBA specification. Although CORBA is well-suited for conventional request/response applications, it is not yet suitable for realtime applications due to the lack of key Quality of Service (QoS) features and performance optimizations. This paper explains the design and implementation of a real-time scheduling service that can provide QoS guarantees for deterministic real-time CORBA applications. The scheduling service deals with multiprocessor task scheduling in a distributed environment. It involves a global scheduler and a local scheduler. The global scheduler schedules the tasks based on the Schedulability analysis and the request priority of the tasks. It uses genetic algorithms for intelligent multiprocessor scheduling of the tasks. The Run-Time Scheduler or the Local Scheduler maps client requests for particular servant operations into priorities that are understood by the local OS dispatcher. This Real-time Scheduling Service is implemented as a CORBA object that is responsible for allocating system resources to meet the QoS needs of the applications. It thus brings about extensibility and interoperability in a distributed object system.

ADAPTIVE CLASSIFIER INTEGRATION FOR INVARIANT FACE RECOGNITION (ACIIFR)

The integration of multiple classifiers promises higher classification accuracy and robustness than can be obtained with a single classifier. We address two problems: (a) automatic recognition of human faces using a novel fusion approach based on an adaptive LVQ network architecture, and (b) improve the face recognition up to 100% while maintaining the learning time per face image constant, which is an scalability issue. The learning time per face image of the recognition system remains constant irrespective of the data size. The integration of the system incorporates the "divide and conquer" modularity principles, i.e. divide the learning data into small modules, train individual modules separately using compact LVQ model structure and still encompass all the variance, and fuse trained modules to achieve recognition rate nearly 100%. The concept of Merged Classes (MCs) is introduced to enhance the accuracy rate. The proposed integrated architecture has shown its feasibility using a collection of 1130 face images of 158 subjects from three standard databases, ORL, PICS and KU. Empirical results yield an accuracy rate of 100% on the face recognition task for 40 subjects in 0.056 seconds per image. Thus, the system has shown potential to be adopted for real time application domains.

The design of the TAO real-time object request broker

Many real-time application domains can benefit from flexible and open distributed architectures, such as those defined by the CORBA specification. CORBA is an architecture for distributed object computing being standardized by the OMG. Although CORBA is well-suited for conventional request/response applications, CORBA implementations are not yet suited for real-time applications due to the lack of key quality of service (QoS) features and performance optimizations. This paper makes three contributions to the design of real-time CORBA systems. First, the paper describes the design of TAO, which is our high-performance, real-time CORBA 2.0-compliant implementation that runs on a range of OS platforms with real-time features including VxWorks, Chorus, Solaris 2.x, and Windows NT. Second, it presents TAO's real-time scheduling service that can provide QoS guarantees for deterministic real-time CORBA applications. Finally, the paper presents performance measurements that demonstrate the effects of priority inversion and non-determinism in conventional CORBA implementations and how these hazards are avoided in TAO.

EVALUATION OF REAL-TIME PROBLEM SOLVERS IN DYNAMIC ENVIRONMENTS

There are many real-time application domains in which the world changes during the problem solving process. Several real-time search algorithms have been proposed for problem solving in dynamic environments. However, there has not been any systematic evaluation and comparison of these algorithms. This paper provides a classification of different dynamic worlds. It then provides a detailed model of a dynamic world where changes occur in edge costs around a zero mean. A formal analysis of the model suggests that the static rank ordering of solution paths is preserved in the proposed dynamic model. The paper provides analysis of two real-time search algorithms, namely DYNORAII and RTA*, for the real-time path planning problem. DYNORAII addresses response-time constraints and dynamic world issues simultaneously. We provide new results on the path planning problem in the proposed dynamic model of graphs. We also provide experimental evaluation of DYNORAII and RTA* in their ability to minimize response-times in dynamic environments.

A visual real-time programming language

Software engineering for real-time applications is known to be a hard problem. For years, many people have been taking different steps to tackle this problem. One of these steps was the introduction of visual languages. Visual languages have the potential to ease programming as they are more expressive than the conventional textual languages (Shu, 1988). In the domain of real-time applications, the use of visual languages is mainly restricted to software design languages. Automatic code generators are used to generate a code skeleton, which is filled in with fairly ‘coarse grained’ hand written textual program fragments. In this paper a method is presented to extend existing visual design languages to visual programming languages with a much more powerful visual component.

A Visual Real-Time Programming Language

Software engineering for real-time applications is known to be a hard problem. For years, many people have been taking different eteps to tackle this problem. One of these steps was the introduction of visual languages. Visual languages have the potential to ease programming as they are more expressive than the conventional textual languages (Shu, 1988). In the domain of real time applications, the use of visual languages is mainly restricted to software design languages. Automatic code generators are used to generate a code skeleton, which is filled in with fairly ‘coarse grained’ hand written textual program fragments. In this paper we present a method to extend existing visual design languages to visual programming languages with a much more powerful visual component.