Response Time Analysis Research Articles

The concept of Maximal Unschedulable Deadline Assignment for optimization in fixed-priority scheduled real-time systems

This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it.

Schedulability analysis of DAG tasks with arbitrary deadlines under global fixed-priority scheduling

One of the major sources of pessimism in the response time analysis (RTA) of globally scheduled real-time tasks is the computation of an upper-bound on the inter-task interference. This problem is further exacerbated when intra-task parallelism is permitted because of the complex internal structure of parallel tasks. This paper considers the global fixed-priority (G-FP) scheduling of sporadic real-time tasks when each task is modeled by a directed acyclic graph (DAG) of concurrent subtasks. We present a RTA based on the concept of problem window, a technique that has been extensively used to study the schedulability of sequential task in multiprocessor systems. The problem window approach of RTA usually categorizes interfering jobs in three different groups: carry-in, carry-out and body jobs. In this paper, we propose two novel techniques to derive less pessimistic upper-bounds on the workload produced by the carry-in and carry-out jobs of the interfering tasks. Those new bounds take into account the precedence constraints between subtasks pertaining to the same DAG. We show that with this new characterization of the carry-in and carry-out workload, the proposed schedulability test offers significant improvements on the schedulability of DAG tasks for randomly generated task sets in comparison to state-of-the-art techniques. In fact, we show that, while the state-of-art analysis does not scale with an increasing number of processors when tasks have constrained deadlines, the results of our analysis are barely impacted by the processor count in both the constrained and the arbitrary deadline case.

WCRT Analysis and Evaluation for Sporadic Message-Processing Tasks in Multicore Automotive Gateways

We study the worst case response time (WCRT) analysis and evaluation for sporadic message-processing tasks in a multicore automotive gateway of a controller area network (CAN) cluster. We first build a multicore automotive gateway on CAN clusters. Two WCRT analysis methods for message-processing tasks in the multicore gateway are subsequently presented based on global and partitioned scheduling paradigms. We evaluate the WCRT results of two analysis methods with real message sets provided by the automaker, and present the design optimization guide.

A semi-partitioned model for mixed criticality systems

Many Mixed Criticality algorithms have been developed with an assumption that lower criticality-level tasks may be abandoned in order to guarantee the schedulability of higher-criticality tasks when the criticality level of the system changes. But it is valuable to explore means by which all of the tasks remain schedulable through these criticality level changes. This paper introduces a semi-partitioned model for a multi-core platform that allows all of the tasks to remain schedulable if only a bounded number of cores increase their criticality level. In such a model, some lower-criticality tasks are allowed to migrate instead of being abandoned. Detailed response time analysis for this model is derived. This paper also introduces possible approaches for establishing migration routes. Together with related previous work, an appropriate semi-partitioned model for mixed criticality systems hosted on multi-core platforms is recommended.

User-Centric Thermal Management for Smartphones

For high-performance smartphones, keeping the on-chip temperature under a given critical temperature is a major concern. In order to prevent the temperature from rising above the critical point, modern smartphones widely adopt the dynamic thermal management (DTM) scheme, which limits the maximum CPU frequency when the CPU reaches high temperatures (thus making the CPU temperature drop). In this paper, we propose a novel DTM scheme based on userperceived response time analysis called SmartDTM. Unlike existing DTM schemes that can significantly degrade the quality of user experience, SmartDTM explicitly accounts for the quality of the user experience in making DTM decisions. We divide an execution of a given user-interactive session into two intervals, one where the system response time directly affects the user experience and the other where the system response time does not affect the user experience. In the user-perceived response time interval, our proposed scheme conservatively makes DTM decisions so that the quality of the user experience is not affected by the reduced maximum CPU frequency. On the other hand, in the user-oblivious response time interval, SmartDTM aggressively lowers the CPU frequency so that the CPU temperature can be quickly decreased to a safe level without negatively affecting user experience. Our experimental results on an ODROID-XU+E board show that SmartDTM can improve the performances of user-perceived intervals by 12.2% and 21.4% over the Android’s default DTM policy when the initial temperature was set to 65°C and 70°C, respectively, under the critical temperature of 85°C.

Analysis of response time for patient non-transport by 119 ambulance services

Analysis of response time for patient non-transport by 119 ambulance services

Execution-Efficient Response Time Analysis on Global Multiprocessor Platforms

Response time analysis (RTA) is an important and fundamental tool for analyzing the schedulability of real-time tasks on multiprocessor platforms, and many promising techniques have been developed during the past few years. However, most of the existing researches focus on improving the analysis precision, while less has been done on enhancing the execution efficiency. In this paper, we take, to our best knowledge, the first effort towards improving the efficiency of the state-of-the-art RTA methods for sporadic tasks under both global fixed-priority (G-FP) and global earliest deadline first (G-EDF) scheduling. Specifically, three factors that impact the efficiency of existing global RTA tests are identified: 1) pessimistic initial value when computing the worst-case response time (WCRT) of tasks under both G-FP and G-EDF; 2) conservative interference upper bound under both G-FP and G-EDF; and 3) unnecessary recalculation of WCRTs when there is update of any task WCRT under G-EDF. By addressing these three limitations, we propose two efficient RTA methods for G-FP and G-EDF scheduling, respectively, which achieve better run-time performance but without sacrificing any analysis precision. Experimental evaluations with randomly generated task sets show that the proposed methods exhibit remarkable performance improvements and can save on average 60 and 61 percent run time, as compared to the state-of-the-art technologies under G-FP and G-EDF scheduling, respectively.

Emotion-specific priming effects with marginally perceptible facial expression primes: Evidence from the "leave-one-out" paradigm.

Priming studies investigating the processing of emotional faces under conditions of limited awareness have shown that people can extract more than just valence from masked faces. However, previous results have been inconsistent with regard to the degree of differentiation among negative expressions. Some results have suggested a relevance differentiation (i.e., anger differentiated from fear or sadness) and some have suggested differentiation by arousal (i.e., sadness differentiated from fear or anger); others have not suggested any differentiation beyond valence. It may even be possible that differentiation occurs down to the level of the specific emotion. To gain further insight into emotion differentiation under such conditions, we presented angry, fearful, and sad faces as masked primes in a response priming task with nontarget primes (i.e., primes and targets were from different stimulus sets). More important, in each of four experiments, only 2 of the prime emotions were used as target emotions in a binary emotion categorization task; that is, 1 prime emotion was left out as a target category. The relevance, arousal, and specificity hypotheses make contrasting predictions regarding (a) the presence or absence of focal priming effects (i.e., effects from prime emotions contained in the response set) and (b) the presence or absence of priming effects arising from the prime emotion left out from the response set. Results of conventional analysis of response times as well as diffusion model analyses were most compatible with the specificity hypothesis. However, the particular response set partially determined which information was extracted from masked primes. Results are interpreted in terms of an action-trigger account. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Exact WCRT Analysis for Message-Processing Tasks on Gateway-Integrated In-Vehicle CAN Clusters

A typical automotive integrated architecture is a controller area network (CAN) cluster integrated by a central gateway. This study proposes a novel and exact worst-case response time (WCRT) analysis method for message-processing tasks in the gateway. We first propose a round search method to obtain lower bound on response time (LBRT) and upper bound on response time (UBRT), respectively. We then obtain the exact WCRT belonging to the scope of the LBRT and UBRT with an effective non-exhaustive exploration. Experimental results on a real CAN message set reveal that the proposed exact analysis method can reduce 99.99999% combinations on large-scale CAN clusters.

An IRT-Multiple Indicators Multiple Causes (MIMIC) Approach as a Method of Examining Item Response Latency.

The analysis of response time has received increasing attention during the last decades, since evidence from several studies supported the argument that there is a direct relationship between item response time and test performance. The aim of this study was to investigate whether item response latency affects person's ability parameters, in that it represents an adaptive or maladaptive practice. To examine the above research question data from 8,475 individuals completing the computerized version of the Postgraduate General Aptitude Test (PAGAT) were analyzed. To determine the extent to which response latency affects person's ability, we used a Multiple Indicators Multiple Causes (MIMIC) model, in which every item in a scale was linked to its corresponding covariate (i.e., item response latency). We ran the MIMIC model within the Item Response Theory (IRT) framework (2-PL model). The results supported the hypothesis that item response latency could provide valuable information for getting more accurate estimations for persons' ability levels. Results indicated that for individuals who invest more time on easy items, their likelihood of success does not improve, most likely because slow and fast responders have significantly different levels of ability (fast responders are of higher ability compared to slow responders). Consequently, investing more time for low ability individuals does not prove to be adaptive. The opposite was found for difficult items: individuals spending more time on difficult items increase their likelihood of success, more likely because they are high achievers (in difficult items individuals who spent more time were of significantly higher ability compared to fast responders). Thus, it appears that there is an interaction between the difficulty of the item and person abilities that explain the effects of response time on likelihood of success. We concluded that accommodating item response latency in a computerized assessment model, can inform test quality and test takers' behavior, and in that way, enhance score measurement accuracy.

Errata for Three Papers (2004-05) on Fixed-Priority Scheduling with Self-Suspensions

The purpose of this article is to (i) highlight the flaws in three previously published works [Audsley, 2004a; Audsley, 2004b; Bletsas, 2005] on the worst-case response time analysis for tasks with self-suspensions and (ii) provide straightforward fixes for those flaws, hence rendering the analysis safe.

A Unified Framework for Period and Priority Optimization in Distributed Hard Real-Time Systems

Modern embedded systems, such as automotive, are physically distributed with an increasing number of microcontrollers and buses. They support complex functions such as active safety and autonomous driving features with a high degree of data dependencies. The most common configuration uses periodic activation of tasks and messages coupled with priority-based scheduling. Selecting task and message parameters so that end-to-end deadlines are met can be very challenging, since such deadlines are enforced across a set of microcontrollers and buses. In this paper, we address the problem of optimal selection of task and message activation periods and priorities. Existing approaches cannot scale to large designs and have to settle to optimize period or priority separately, largely due to the complexity of response time analysis techniques. Instead, we present a new, unified framework that simultaneously optimizes period and priority assignment. It avoids the pitfalls of existing approaches by abstracting the response time calculation with the new concept of maximal unschedulable period and deadline assignment. We demonstrate with two industrial case studies that our approach runs magnitudes faster than existing approach on period optimization, while providing substantially better solutions.

The temporal involvement of the left supramarginal gyrus in planning functional grasps: A neuronavigated TMS study

The left supramarginal gyrus (SMG) is a critical structure in tool use actions, including such simple acts as selection of appropriate grasps and, if necessary, their on-line corrections. Yet, its temporal contribution to initial planning of functional grasps of tools is largely unknown. We used MRI-guided, event-related transcranial magnetic stimulation (TMS) to determine the time point when SMG involvement in processing of tools for functional grasp decision was affected most. In Exp. 1, with 15 participants, triple-pulse (10 Hz) TMS was applied to either the left anterior-to-mid SMG (amSMG; subdivisions PFt/PF) or vertex at three different time points: starting from 17 ms (i.e., delivered at 17/117/217 ms), 117 ms (117/217/317 ms) or 217 ms (217/317/417 ms) after stimulus onset. In Exp. 2, with 12 participants, we applied single-pulse TMS to either left amSMG or the left rostral middle frontal gurus (rMFG; area 46) at these same time points relative to stimulus onset. Subject- and item-based analyses of response times (RTs) were performed. Whereas the amSMG and vertex stimulation with triple pulse has revealed differential effects on RTs in general, as well as on tool orientation processing, it gave only vague pointers as to their temporal contributions to the task. Yet, amSMG and rMFG stimulation with single pulse demonstrated that, while the processing in both of these areas can be enhanced at 17 ms and no doubt at 117 ms (as compared to 217 ms), the earliest stimulation facilitated amSMG (vs. rMFG) contribution, and the latest stimulation had the opposite effect, facilitating rMFG (vs. amSMG) contribution to planning functional grasps. These outcomes demonstrate that the critical role of SMG in tool-related actions can be invoked substantially earlier than previously thought.

Forward and backward recall of serial actions: Exploring the temporal dynamics of working memory for instruction.

The ability to flexibly retrieve and implement sequences of actions is essential to motor learning and planning. Recent research has indicated that serial memory for instructions is influenced by presentation modality (spoken vs. visual demonstration) and recall modality (verbal vs. enacted recall). The present study extended this work by investigating the impact of recall direction (forward vs. backward), in addition to that of presentation and recall modality, on working memory for instruction sequences in healthy young adults. Experiment 1 (N = 24) showed that adults were more accurate in backward than forward verbal recall following spoken instructions. In contrast, enacted recall was not influenced by recall direction. Experiment 2 (N = 24) used visual demonstration of instruction sequences and found similar performance levels in forward and backward recall. Experiment 3 (N = 24) replicated the findings from Experiment 1 and 2, along with the previous observation of an advantage for demonstrated over spoken presentation. In addition, the beneficial effects of enacted recall and visual demonstration also emerged in an analysis of response times, specifically in reduced preparation and recall duration. Demonstrated instructions improved maintenance of all items while backward recall enhanced memory of later items in the sequence. These findings provide new insights into the cognitive processes and temporal dynamics of working memory for serial actions and instructions.

Emergence of cooperative route-choice: A model and experiment of compliance with system-optimal ATIS

Advanced Traveler Information Systems (ATIS) aim to supply drivers with individually tailored information. User optimal information provision pushes the road network closer to the theoretical state of User Equilibrium (UE) instead of the System Optimum (SO). We investigate the effects on individual route-choice and consequent collective traffic states of an SO-based ATIS in a mixed within-between group design laboratory experiment. The experiment examines how implicit cooperation between self-interested participants emerges on a simple binary road network by providing them information in the form of system optimally allocated route recommendations and extrinsic incentives for compliance. Collectively, the recommendations were found to be a necessary condition for cooperation. Additional incentives in the form of penalties and rewards for compliance allowed cooperation to emerge much more efficiently. Individually, participants adapt to the new information by adopting four different coping strategies. Analysis of response time suggests that complex signals that include information on the recommended route coupled with incentives for compliance will result in more deliberation and higher rates of compliance. The implications for the behavioral implications on ATIS design and implementation are further discussed.

IMPLEMENTASI METODE INTRUSION DETECTION SYSTEMS (IDS) DAN INTRUSION PREVENTION SYSTEMS (IPS) BERBASIS SNORT SERVER UNTUK KEAMANAN JARINGAN LAN

Abstract - Currently in the world of network is being focused on computer network system, the dangerous and dangerous things from within the network itself. It requires techniques to secure the resources available in computer networks by using Intrusion Detection Systems (IDS) or intrusion detection systems, using an intruder detection system that enables preventive network and information systems (IPS) or backharming systems that will prevent intruder. In this research applied Intrusion Detection System (IDS) and Intrusion Prevention Systems (IPS) as detection and prevention system when intruders on computer network server, using Snort as rule based as alert to do security on computer network. Intrusion Detection Systems (IDS) implemented on Linux operating systems and Intrusion Prevention Systems (IPS) will be implemented with firewalls or iptables. From this research, Intrusion Detection System (IDS) system testing and response time analysis with 3 models of TCP flood attack, UDP Flood, and ICMP Flood. Results issued by the IDS system with 1 client and 2 clients simultaneously perform an attack that produces the same alert accuracy value with an average value of 99.98%. The average value of response time obtained from credit with 1 client is 0.53 seconds and when using 2 clients get an average value of 0.32 seconds. So in conclusion when an intruder detection system (IDS) is shared with 1 client or 2 client performs an attack, the system is able to detect well and produce the same performance in detecting attacks from 1 or more clients. And the results of the intruder deterrent testing system (IPS) is able to block Internet Protocol (IP) by filtering the attacker IP well. Keywords - Computer Network Security, Intrusion Detection Systems (IDS), Intrusion Prevention Systems (IPS), Snort, IP Tables.

Contextual activity based Healthcare Internet of Things, Services, and People (HIoTSP): An architectural framework for healthcare monitoring using wearable sensors

Healthcare industry is gaining a lot of attention due to its technological advancement and the miniaturization in the form of wearable sensors. IoT-driven healthcare industry has mainly focused on the integration of sensors rather than the integration of services and people. Nonetheless, the framework for IoT-driven healthcare applications are significantly lacking. In addition, the use of semantics for ontological reasoning and the integration of mobile applications into a single framework have also been ignored in many existing studies. This work presents the implementation of Healthcare Internet of Things, Services, and People (HIoTSP) framework using wearable sensor technology. It is designed to achieve the low-cost (consumer devices), the easiness to use (interface), and the pervasiveness (wearable sensors) for healthcare monitoring along with the integration of services and agents like doctors or caregivers. The proposed framework provides the functionalities for data acquisition from wearable sensors, contextual activity recognition, automatic selection of services and applications, user interface, and value-added services such as alert generation, recommendations, and visualization. We used the publicly available dataset, PAMAP2 which is a physical activity monitoring dataset, for deriving the contextual activity. Fall and stress detection services are implemented as case studies for validating the realization of the proposed framework. Experimental analysis shows that we achieve, 87.16% accuracy for low-level contextual activities and 84.06%–86.36% for high-level contextual activities, respectively. We also achieved 91.68% and 82.93% accuracies for fall and stress detection services, respectively. The result is quite satisfactory, considering that all these services have been implemented using pervasive devices with the low-sampling rate. The real-time applicability of the proposed framework is validated by performing the response time analysis for both the services. We also provide suggestions to cope with the scalability and security issues using the HIoTSP framework and we intend to implement those suggestions in our future work.

Performance of radon monitors in a purpose-built radon chamber

The purpose of this paper is to benchmark several different radon monitors, by quantifying their accuracy and response time. Radon monitors with different characteristics were tested in a purpose-built radon chamber under reference conditions. The radon concentration in the chamber was controlled and maintained at a stable radon concentration of (2648 ± 85) Bq m−3 to evaluate the accuracy and precision of these monitors. The response time of the monitors was analysed for two time intervals. To assess the response time of the monitors, radon concentration was varied from a theoretical value of 0–6441 Bq m−3 and then from 6441 to 2648 Bq m−3. The results from this study show that general purpose radon monitors are less accurate than those used by radon testing service providers and the research community. All monitors tested reported a mean radon concentration within the ±10% of the reference detector value at the radon equilibrium concentration. Different response time analysis methods were proposed and discussed, and for the particular time intervals analysed, response time was found to be slower for those radon monitors intended for general purpose applications.

Humans and Algorithms for Facial Recognition: The Effects of Candidate List Length and Experience on Performance

These experiments investigated how the candidate list displayed to facial reviewers affects their performance in a one-to-many unfamiliar face matching task. Automated facial recognition systems present the results of a database search and require selection of an image that matches the target. Few studies investigate how humans in combination with facial recognition algorithms perform within different operational contexts. These experiments investigated how the candidate list displayed to facial reviewers affects their performance in a one-to-many unfamiliar face matching task. We tested candidate list length with inexperienced (Experiment 1) and experienced (Experiment 2) facial reviewers. Candidate list length had a large impact on performance, varying with the operational context. However, response-time analyses show that the accurate responses were resolved quickly, with an error-prone guess process implemented after failed search. Long candidate lists (100 images) produced more false alarms, fewer hits, lower decision confidence, and increased response latencies among both inexperienced and experienced facial reviewers.

Analysis of the viscosity dependent parameters of couple stress fluid in porous parallel plates

PurposeThis paper aims to present a detailed analysis to explore the various properties of non-Newtonian couple stress lubricants between parallel porous plates.Design/methodology/approachWith reference to the theories based on micro-continuum analysis, a non-linear, non-Newtonian Reynolds type equation is arrived. The closed form solutions obtained clearly indicate the changes in pressure, load bearing capacity and response time because of variation in viscosity of couple stress fluid.FindingsIt is observed that the viscosity variation factor greatly influences the change in pressure, load carrying capacity and squeezing time.Originality/valueIt is observed that the nature of lubricants with suitable additives greatly helps in overcoming the adverse effect because of porous surface. Reynolds type equation is analysed using appropriate boundary conditions. The expression for pressure distribution arrived at in turn leads to the analysis of load bearing capacity and response time.