Holistic Resource Allocation Under Federated Scheduling for Parallel Real-time Tasks

With the technology trend of hardware and workload consolidation for embedded systems and the rapid development of edge computing, there has been increasing interest in supporting parallel real-time tasks to better utilize the multi-core platforms while meeting the stringent real-time constraints. For parallel real-time tasks, the federated scheduling paradigm, which assigns each parallel task a set of dedicated cores, achieves good theoretical bounds by ensuring exclusive use of processing resources to reduce interferences. However, because cores share the last-level cache and memory bandwidth resources, in practice tasks may still interfere with each other despite executing on dedicated cores. Such resource interferences due to concurrent accesses can be even more severe for embedded platforms or edge servers, where the computing power and cache/memory space are limited. To tackle this issue, in this work, we present a holistic resource allocation framework for parallel real-time tasks under federated scheduling. Under our proposed framework, in addition to dedicated cores, each parallel task is also assigned with dedicated cache and memory bandwidth resources. Further, we propose a holistic resource allocation algorithm that well balances the allocation between different resources to achieve good schedulability. Additionally, we provide a full implementation of our framework by extending the federated scheduling system with Intel’s Cache Allocation Technology and MemGuard. Finally, we demonstrate the practicality of our proposed framework via extensive numerical evaluations and empirical experiments using real benchmark programs.

Production Behavior in Sharia Economy: in the Perspective of Maqashidi Interpretation

<em>In the perspective of sharia economy, production activities are linked to humans and their participation in economic activities. The problem is, then, how the Qur'an views production behavior as processing resources into outputs in order to increase public interests (maslahah) for humankind. This paper focuses on the study on how to picture the concept of production behavior in sharia economy, as understood through the contemporary commentary approach called maqashidi interpretation. This study is a literature research based on a review of texts related to economic recession with a focus on maqashidi interpretation. According to the results of this study, several terms are used to refer to the term 'production' in the Quran, such as 'amal, sina'ah, and other terms mentioned in the verses of the Quran in general. Maqashidi interpretation on production behavior seeks to comprehend the verses referring to production based on public interest values for those working, creating, and manufacturing products. In relation to the maqasid verses of the Quran, production behavior leads to human needs which encompass five preservations, such as preserving religion (hifz al-din), soul (hifz al-nafs), minds and creativity (hifz al-'aql), property and materials (hifz al-mal), and continuity of heredity (hifz al-nasl), all of which aim to benefit Muslims.</em>

A Type of Transportation Problem to be Solved Following the Time Criterion and Considering Vehicle Features

The formulation of classical minimax transport-type problems involves the search for an optimal transportation plan considering only time of delivery of resources. The inevitable additional costs of processing resources at the origin and destination are usually not considered. This approach is fully justified given incommensurability of delivery times of resources along available routes and times of preliminary/subsequent processing of resources. At the same time, in a number of practical problems, the time spent on loading/unloading (for example, when organizing loading of packaged mineral fertilizers from port warehouses onto ships) can be of significant importance. In such cases, when searching for an optimal transportation plan, it is necessary to take into account not only travel times of vehicles used along the set routes, but also the costs of loading and unloading operations, considering the number of available vehicles and their characteristics, for example, payload.In this regard, the objective of the study is not only to develop a method for calculating the optimal transportation plan, but also a method for distributing vehicles, considering their number and features.At the same time, another no less important objective of the study is to substantiate the application of the method of successive reduction of residuals, considering the form of the objective function, which considers not only the main parameters of classical minimax transport-type problems, but also the quantitative characteristics of vehicles involved in the transport operation. It is fundamentally important that the use of the method of successive reduction of residuals determines the polynomial computational complexity of the algorithm, which makes it possible to use it in the operational solution of problems of practical dimension.To solve the problem of distributing available vehicles according to the origin points, considering payload of vehicles, it is proposed to use the method of dynamic programming. An illustrative example of distribution of delivery vehicles, adapted for the use in MS Excel, is considered.

Fast nonlinear model predictive planner and control for an unmanned ground vehicle in the presence of disturbances and dynamic obstacles

This paper presents a solution for the tracking control problem, for an unmanned ground vehicle (UGV), under the presence of skid-slip and external disturbances in an environment with static and moving obstacles. To achieve the proposed task, we have used a path-planner which is based on fast nonlinear model predictive control (NMPC); the planner generates feasible trajectories for the kinematic and dynamic controllers to drive the vehicle safely to the goal location. Additionally, the NMPC deals with dynamic and static obstacles in the environment. A kinematic controller (KC) is designed using evolutionary programming (EP), which tunes the gains of the KC. The velocity commands, generated by KC, are then fed to a dynamic controller, which jointly operates with a nonlinear disturbance observer (NDO) to prevent the effects of perturbations. Furthermore, pseudo priority queues (PPQ) based Dijkstra algorithm is combined with NMPC to propose optimal path to perform map-based practical simulation. Finally, simulation based experiments are performed to verify the technique. Results suggest that the proposed method can accurately work, in real-time under limited processing resources.

Phase of neural oscillations as a reference frame for attention-based routing in visual cortex

Selective attention allows the brain to efficiently process the image projected onto the retina, selectively focusing neural processing resources on behaviorally relevant visual information. While previous studies have documented the crucial role of the action potential rate of single neurons in relaying such information, little is known about how the activity of single neurons relative to their neighboring network contributes to the efficient representation of attended stimuli and transmission of this information to downstream areas. Here, we show in the dorsal visual pathway of monkeys (medial superior temporal (MST) area) that neurons fire spikes preferentially at a specific phase of the ongoing population beta (~20 Hz) oscillations of the surrounding local network. This preferred spiking phase shifts towards a later phase when monkeys selectively attend towards (rather than away from) the receptive field of the neuron. This shift of the locking phase is positively correlated with the speed at which animals report a visual change. Furthermore, our computational modelling suggests that neural networks can manipulate the preferred phase of coupling by imposing differential synaptic delays on postsynaptic potentials. This distinction between the locking phase of neurons activated by the spatially attended stimulus vs. that of neurons activated by the unattended stimulus, may enable the neural system to discriminate relevant from irrelevant sensory inputs and consequently filter out distracting stimuli information by aligning the spikes which convey relevant/irrelevant information to distinct phases linked to periods of better/worse perceptual sensitivity for higher cortices. This strategy may be used to reserve the narrow windows of highest perceptual efficacy to the processing of the most behaviorally relevant information, ensuring highly efficient responses to attended sensory events.

Crisis Map Design Considering Map Cognition

Crisis maps play a significant role in emergency responses. Users are challenged to interpret a map rapidly in emergencies, with limited visual information-processing resources and under time pressure. Therefore, cartographic techniques are required to facilitate their map cognition. In this study, we analyzed the exogenous and endogenous disruptions that users needed to overcome when they were reading maps. The analysis results suggested that cartographers’ taking the stressors into consideration could promote the cognitive fit between cartographers and users, improving map cognition and spatial information supply–demand matching. This paper also elaborates the course of map visual information processing and related graphic variables to visual attention attributes. To improve the users’ map cognition in time-critical emergency situations, crisis map design principles and a methodology were proposed. We developed three fire emergency rescue road maps and performed two evaluations to verify the effectiveness of the principles. Our experiments showed that the principles could effectively facilitate the users’ rapid map perception and proper understanding, by reducing their cognitive load, and could improve the quality of the crisis maps to some extent.

Relationship Between Parent Vowel Hyperarticulation in Infant-Directed Speech and Infant Phonetic Complexity on the Level of Conversational Turns

When speaking to infants, parents typically use infant-directed speech, a speech register that in several aspects differs from that directed to adults. Vowel hyperarticulation, that is, extreme articulation of vowels, is one characteristic sometimes found in infant-directed speech, and it has been suggested that there exists a relationship between how much vowel hyperarticulation parents use when speaking to their infant and infant language development. In this study, the relationship between parent vowel hyperarticulation and phonetic complexity of infant vocalizations is investigated. Previous research has shown that on the level of subject means, a positive correlational relationship exists. However, the previous findings do not provide information about the directionality of that relationship. In this study the relationship is investigated on a conversational turn level, which makes it possible to draw conclusions on whether the behavior of the infant is impacting the parent, the behavior of the parent is impacting the infant, or both. Parent vowel hyperarticulation was quantified using the vhh-index, a measure that allows vowel hyperarticulation to be estimated for individual vowel tokens. Phonetic complexity of infant vocalizations was calculated using the Word Complexity Measure for Swedish. Findings were unexpected in that a negative relationship was found between parent vowel hyperarticulation and phonetic complexity of the immediately following infant vocalization. Directionality was suggested by the fact that no such relationship was found between infant phonetic complexity and vowel hyperarticulation of the immediately following parent utterance. A potential explanation for these results is that high degrees of vowel hyperarticulation either provide, or co-occur with, large amounts of phonetic and/or linguistic information, which may occupy processing resources to an extent that affects production of the next vocalization.

Signal envelope and speech intelligibility differentially impact auditory motion perception

Our acoustic environment contains a plethora of complex sounds that are often in motion. To gauge approaching danger and communicate effectively, listeners need to localize and identify sounds, which includes determining sound motion. This study addresses which acoustic cues impact listeners’ ability to determine sound motion. Signal envelope (ENV) cues are implicated in both sound motion tracking and stimulus intelligibility, suggesting that these processes could be competing for sound processing resources. We created auditory chimaera from speech and noise stimuli and varied the number of frequency bands, effectively manipulating speech intelligibility. Normal-hearing adults were presented with stationary or moving chimaeras and reported perceived sound motion and content. Results show that sensitivity to sound motion is not affected by speech intelligibility, but shows a clear difference for original noise and speech stimuli. Further, acoustic chimaera with speech-like ENVs which had intelligible content induced a strong bias in listeners to report sounds as stationary. Increasing stimulus intelligibility systematically increased that bias and removing intelligible content reduced it, suggesting that sound content may be prioritized over sound motion. These findings suggest that sound motion processing in the auditory system can be biased by acoustic parameters related to speech intelligibility.

Predictable Words Are More Likely to Be Omitted in Fragments–Evidence From Production Data

Instead of a full sentence like Bring me to the university (uttered by the passenger to a taxi driver) speakers often use fragments like To the university to get their message across. So far there is no comprehensive and empirically supported account of why and under which circumstances speakers sometimes prefer a fragment over the corresponding full sentence. We propose an information-theoretic account to model this choice: A speaker chooses the encoding that distributes information most uniformly across the utterance in order to make the most efficient use of the hearer's processing resources (Uniform Information Density, Levy and Jaeger, 2007). Since processing effort is related to the predictability of words (Hale, 2001) our account predicts two effects of word probability on omissions: First, omitting predictable words (which are more easily processed), avoids underutilizing processing resources. Second, inserting words before very unpredictable words distributes otherwise excessively high processing effort more uniformly. We test these predictions with a production study that supports both of these predictions. Our study makes two main contributions: First we develop an empirically motivated and supported account of fragment usage. Second, we extend previous evidence for information-theoretic processing constraints on language in two ways: We find predictability effects on omissions driven by extralinguistic context, whereas previous research mostly focused on effects of local linguistic context. Furthermore, we show that omissions of content words are also subject to information-theoretic well-formedness considerations. Previously, this has been shown mostly for the omission of function words.

BeiDou Short-Message Satellite Resource Allocation Algorithm Based on Deep Reinforcement Learning

The comprehensively completed BDS-3 short-message communication system, known as the short-message satellite communication system (SMSCS), will be widely used in traditional blind communication areas in the future. However, short-message processing resources for short-message satellites are relatively scarce. To improve the resource utilization of satellite systems and ensure the service quality of the short-message terminal is adequate, it is necessary to allocate and schedule short-message satellite processing resources in a multi-satellite coverage area. In order to solve the above problems, a short-message satellite resource allocation algorithm based on deep reinforcement learning (DRL-SRA) is proposed. First of all, using the characteristics of the SMSCS, a multi-objective joint optimization satellite resource allocation model is established to reduce short-message terminal path transmission loss, and achieve satellite load balancing and an adequate quality of service. Then, the number of input data dimensions is reduced using the region division strategy and a feature extraction network. The continuous spatial state is parameterized with a deep reinforcement learning algorithm based on the deep deterministic policy gradient (DDPG) framework. The simulation results show that the proposed algorithm can reduce the transmission loss of the short-message terminal path, improve the quality of service, and increase the resource utilization efficiency of the short-message satellite system while ensuring an appropriate satellite load balance.