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OVERVIEW: This study examines the temporal attributes, barriers, and outcomes of slack time in R&D organizations. The study findings indicate that slack time has a waved occurrence, organically arising from downtimes in core work and uptimes in personal creativity. Endemic overcommitment of employees and high perceived opportunity costs prevent slack time from being used effectively in many organizations, resulting in merely rhetorical slack time. The findings suggest that genuine slack time requires formally allocating resources to pay for discretionary time and insulating employees from urgent demands. The study identifies three main outcomes of genuine slack time: (1) It diversifies creativity sources, leading to a spectrum of innovativeness and applications; (2) it increases employee motivation through autonomy and empowerment; and (3) it functions as a cultural lever signaling trust. The study contributes a nuanced conceptualization of slack time grounded in practitioner experiences and offers insights for managing slack time to foster innovation and employee engagement. PRACTITIONER TAKEAWAYS: Slack time manifests as pockets of free time that arise opportunistically during slow periods in regular work and when employees experience personal momentum. Genuine slack time requires that employees are not 100 percent committed to core work and that they are protected from urgent demands during slack time usage. Slack time boosts employee motivation and retention and can contribute to a balanced early-stage innovation portfolio. [ABSTRACT FROM AUTHOR]

I also share results from a pilot study, which offer insights regarding R&D companies' preferred slack time model, the creative work employees perform during slack time, and the perceived success of slack time programs. Keywords: Slack time; Discretionary time; Creativity; Innovation; Innovation portfolio management EN Slack time Discretionary time Creativity Innovation Innovation portfolio management 34 45 12 11/04/22 20221101 NES 221101 Organizations have to deal with surges of activity, adjust to changes in the external environment, and proactively experiment with the development of innovative products, services, processes, or business models. Regardless of how a company categorizes its innovation initiatives, an innovation portfolio is likely to have different degrees of innovativeness and complexity, which can be used as input to determine if the way the company organizes slack time fits well with its innovation portfolio. [Extracted from the article]

Optimum resources utilization in computing devices especially power is among the prime areas of research from the very beginning of computer systems. However, its importance in the current era has been significantly increased due to the diverse nature of devices and their real time applications. On the other hand, paradigm is shifting towards sustainable resources that are green/environment friendly (low emission) in nature and produce relatively low energy/power. Real time systems (RTS) are relatively power-hungry due to their time constrained nature. So, there is room to investigate the scheduling algorithms (schedulers) with minimum (low) power consumption. On the other hand simulators are the software that mimic the real time environment for various parameter testing without actual implementation that could be costly as well as complex to build in the beginning. In this study, we are intended to develop a simulator for scheduling Real-Time Systems (RTS) with Reduced Power Consumptions (RPC). That is potentially an environment where various algorithms can be tested over different case studies to examine their performance pertaining RPC for RTS. [ABSTRACT FROM AUTHOR]

In recent years, the issue of power consumption in parallel and distributed systems has attracted a great deal of attention. Regarding the ever-increasing development data and computing centers due to the contribution of cloud computing systems in such sectors, power consumption has always been of the concerns due to Carbon dioxide emissions and consequently the Negative impact on the environment. In recent years, the notion of power and also ”Green Computing” has found a crucial spot in the tasks scheduling in cloud data centers. The clustering technique, as well as Dynamic Voltage and Frequency Scaling (DVFS) techniques, have focused on the reduction of the consumption of power particularly, and the optimization of the performance parameters. Concerning scheduling Directed Acyclic Graph (DAG) of a data center processors equipped with the technique of DVFS, this paper proposes a power and time aware algorithm called PATCDD, to apply the combination of the strategies for clustering along with the distribution of slack-time among the tasks of a cluster. The first phase studies the slack time for non-critical tasks of DAG, extends their execution time and reduces the energy consumption without increasing the task’s execution time as a whole. The main idea of the proposed algorithm involves the achievement of a maximum reduction in power consumption in the second phase. To this end, the slack time is distributed among non-critical dependent tasks. Eventually, a set of data established for conducting the examinations and also different parameters of the constructed random DAG were assessed to identify the efficiency of our proposed algorithm. [ABSTRACT FROM AUTHOR]

Equipping mobile platforms with deep learning applications is very valuable. Providing healthcare services in remote areas, improving privacy, and lowering needed communication bandwidth are the advantages of such platforms. Designing an efficient computation engine enhances the performance of these platforms while running deep neural networks (DNNs). Energy-efficient DNN accelerators use skipping sparsity and early negative output feature detection to prune the computations. Spatial DNN accelerators in principle can support computation-pruning techniques compared to other common architectures, such as systolic arrays. These accelerators need a separate data distribution fabric like buses or trees with support for high bandwidth to run the mentioned techniques efficiently and avoid network on chip (NoC)-based stalls. Spatial designs suffer from divergence and unequal work distribution. Therefore, applying computation-pruning techniques into a spatial design, which is even equipped with an NoC that supports high bandwidth for the processing elements (PEs), still causes stalls inside the computation engine. In a spatial architecture, the PEs that perform their tasks earlier have a slack time compared to others. In this article, we propose an architecture with a negligible area overhead based on sharing the scratchpads in a novel way between the PEs to use the available slack time caused by applying computation-pruning techniques or the used NoC format. With the use of our dataflow, a spatial engine can benefit from computation-pruning and data reuse techniques more efficiently. When compared to the reference design, our proposed method achieves a speedup of $\times 1.24$ and an energy efficiency of $\times 1.18$ per inference. [ABSTRACT FROM AUTHOR]

This paper examines the role of human capital and establishments' practices in fostering food industry innovation across 13 low and middle-income countries. We estimate average marginal effects that also control for the variables traditionally recognized as affecting firm-level innovation, such as R&D expenditures. Our results suggest that establishments' human capital endowments, such as top managers' experience in the food industry and employees' education, alone may not be sufficient to achieve high levels of innovation. In fact, human capital endowments are found to be more effective in delivering innovation when they are combined with establishments' best practices such as providing employees slack time i.e., allocation of work-time on self-chosen projects of personal interests. Our key recommendation to food firms is to support employee slack time and human capital endowments as mutually reinforcing drivers of innovation. [ABSTRACT FROM AUTHOR]

Energy consumption and performance metrics have become critical issues for scheduling parallel task-based applications in high-performance computing systems such as cloud datacenters. The duplication and clustering strategy, as well as Dynamic Voltage Frequency Scaling (DVFS) technique, have separately been concentrated on reducing energy consumption and optimizing performance parameters such as throughput and makespan. In this paper, a dual-phase algorithm called EATSDCD which is an energy efficient time aware has been proposed. The algorithm uses the combination of duplication and clustering strategies to schedule the precedence-constrained task graph on datacenter processors through DVFS. The first phase focuses on a smart combination of duplication and clustering strategy to reduce makespan and energy consumed by processors in an effort to execute Directed Acyclic Graph (DAG) while satisfying the throughput constraint. The main idea behind EATSDCD intended to minimize energy consumption in the second phase. After determining the critical path and specifying a set of dependent tasks in non-critical paths, the slack time for each task in non-critical paths was distributed among all dependent tasks in that path. Then, the frequency of DVFS-enabled processors is scaled down to execute non-critical tasks as well as idle and communication phases, without extending the execution time of tasks. Finally, a testbed is developed and different parameters are tested on the randomly generated DAG to evaluate and illustrate the effectiveness of EATSDCD. It was also compared against duplication and clustering-based algorithms and DVFS-based algorithms. In terms of energy consumption and makespan, the results show that our proposed algorithm can save up to 8.3% and 20% energy compared against Power Aware List-based Scheduling (PALS) and Power Aware Task Clustering (PATC) algorithms, respectively. Furthermore, there is 16% improvement over Parallel Pipeline Latency Optimization (PaPilo) algorithm with Encur = 1.2Enmin (G). In comparison with Reliability Aware Scheduling with Duplication (RASD) algorithm, the execution time has been reduced in heterogeneous environments. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University (Natural Science Edition) is the property of Journal of Zhengzhou University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In ubiquitous and mobile computing environments, most of user requests have timing constraints. Therefore, for their execution, real-time scheduling mechanisms should be employed. In such environments, some mechanisms, such as Earliest Deadline First and Least Slack Time Rate (LSTR), are the most used real-time scheduling algorithms today. However, these existing mechanisms cannot guarantee the execution of the most critical user tasks. Furthermore, the results of executed tasks should also be provided to users on time so as to not waste the resources processing these tasks. The existing scheduling mechanisms, such as Dynamic Adjustment with Time Constraint and Dynamic Priority-based Heuristic action (DPH), are not suitable for this due to some limitations. The current paper proposes two new lightweight real-time mechanisms for scheduling input tasks (received requests) and output tasks (execution results) and evaluates their performance. The first mechanism satisfies users based on the classification of similar tasks and the use of the LSTR algorithm. The second mechanism is an improved form of the combination of the LSTR and DPH algorithms, and aims provide users with the maximum number of services by considering a possibility matrix. Extensive simulation experiments on real workload data demonstrate the superiority of the proposed mechanisms over existing algorithms, in terms of the percentage of executed tasks, makespan, and average turnaround time criteria. [ABSTRACT FROM AUTHOR]

Bus holding strategy is an effective way for alleviating inevitable disruptions along a bus route, including decisions on the control point locations and slack duration. However, at present, the locations of the control points and corresponding slack times are largely determined by engineering experience and therefore lack theoretical optimization. The aim of this study is to develop a model which can jointly optimize the locations of the control points and corresponding slack times under a given number of control points. As locations of the upstream control points will influence the downstream operation states, this optimization problem is modeled as a multi-stage decision process. To evaluate the stability and efficiency of a bus system, we calculate the punctuality rate and travel time at each stage by taking into account the uncertainty along the route and propose a reasonable stage-utilization cost combing these two factors. A numerical case study based on a real bus route in Harbin of China is carried out to demonstrate our approach. The impacts of the weighting factor and slack times on the optimal control point plan are also discussed. [ABSTRACT FROM AUTHOR]

The relationship between slack resources and innovation is complex, with the literature linking slack to both breakthrough innovations and resource misallocation. We reconcile these conflicting views by focusing on a novel mechanism: the role slack time plays in the endogenous allocation of time and effort to innovative projects. We develop a theoretical model that distinguishes between periods of high- (work weeks) versus low- (break weeks) opportunity costs of time. Low-opportunity cost time during break weeks may induce (1) lower quality ideas to be developed (a selection effect); (2) more effort to be applied for any given idea quality (an effort effect); and (3) an increase in the use of teams because scheduling is less constrained (a coordination effect). As a result, the effect of an increase in slack time on innovative outcomes is ambiguous, because the selection effect may induce more low-quality ideas, whereas the effort and coordination effect may lead to more high-quality, complex ideas. We test this framework using data on college breaks and on 165,410 Kickstarter projects across the United States. Consistent with our predictions, during university breaks, more projects are posted in the focal regions, and the increase is largest for projects of either very high or very low quality. Furthermore, projects posted during breaks are more complex, and involve larger teams with diverse skills. We discuss the implications for the design of policies on slack time. The online appendices are available at https://doi.org/10.1287/orsc.2018.1215. [ABSTRACT FROM AUTHOR]

Supporting efficient connections by synchronizing vehicle arrival time and passengers' walking time at a transfer hub may significantly improve service quality, stimulate demand, and increase productivity. However, vehicle travel times and walking times in urban settings often varies spatially and temporally due to a variety of factors. Nevertheless, the reservation of slack time and/or the justification of vehicle arrival time at the hub may substantially increase the success of transfer coordination. To this end, this paper develops a model that considers probabilistic vehicle arrivals and passengers walking speeds so that the slack time and the scheduled bus arrival time can be optimized by minimizing the total system cost. A case study is conducted in which the developed model is applied to optimize the coordination of multiple bus routes connecting at a transfer station in Xi'an, China. The relationship between decision variables and model parameters, including the mean and the standard deviation of walking time, is explored. It was found that the joint impact of probabilistic vehicle arrivals and passengers' walking time significantly affects the efficiency of coordinated transfer. The established methodology can essentially be applied to any distribution of bus arrival and passenger walking time. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Copyright of Computer Engineering & Science / Jisuanji Gongcheng yu Kexue is the property of Computer Engineering & Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing. [ABSTRACT FROM PUBLISHER]

Project success includes time, budget, quality, customer satisfaction etc. We are always confronted with time and money in the first place. Activity schedules must consider the available resources to be completed in the right sequence and in time. Companies must maintain competitive cost-time profiles. Execution periods of non-critical project activities have a considerable influence to the amount of locked-up capital. In the paper we have simulated some cases with varied execution periods of noncritical project activities within the slack, and measured cost-time investment. For the visualisation of project cost accumulation we have applied cost-time profile; we have used Cost Time Profiler software. The results show that the differences are significant, bringing a potential for project optimization. [ABSTRACT FROM AUTHOR]

Copyright of Electrotehnica, Electronica, Automatica is the property of ICPE SA (Editura Electra) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In control devices for the Internet of Things (IoT), energy is one of the critical restriction factors. Dynamic voltage scaling (DVS) has been proved to be an effective method for reducing the energy consumption of processors. This paper proposes an energy-efficient scheduling algorithm for IoT control devices with hard real-time control tasks (HRCTs) and soft real-time tasks (SRTs). The main contribution of this paper includes two parts. First, it builds the Hybrid tasks with multi-subtasks of different function Weight (HoW) task model for IoT control devices. HoW describes the structure of HRCTs and SRTs, and their properties, e.g., deadlines, execution time, preemption properties, and energy-saving goals, etc. Second, it presents the Hybrid Tasks' Dynamic Voltage Scaling (HTDVS) algorithm. HTDVS first sets the slowdown factors of subtasks while meeting the different real-time requirements of HRCTs and SRTs, and then dynamically reclaims, reserves, and reuses the slack time of the subtasks to meet their ideal energy-saving goals. Experimental results show HTDVS can reduce energy consumption about 10%-80% while meeting the real-time requirements of HRCTs, HRCTs help to reduce the deadline miss ratio (DMR) of systems, and HTDVS has comparable performance with the greedy algorithm and is more favorable to keep the subtasks' ideal speeds. [ABSTRACT FROM AUTHOR]

We propose to handle execution duration overruns (temporal faults) in real-time embedded systems. When a temporal fault occurs, the slack time can be dynamically determined and assigned to the faulty task in order to complete its treatment. This mechanism improves the temporal robustness of real-time systems. We demonstrate that an approximate slack stealer algorithm like the minimal approximate slack stealer (MASS) algorithm is a good solution for real-time embedded systems. We validate the feasibility of this approach by an implementation on the Lego Mindstorm NXT platform. [ABSTRACT FROM PUBLISHER]

The modification and extension of the Minimax method, in which the slack time s is determined for the maximum frequency f, is presented. A way of the determination of f such that the Minimax method provides the minimum energy consumption is proposed. The possibility and results of the application of the Minimax method in real-time systems with jump-like changes of the supply voltage, as well as in systems with violation of hard deadlines, are demonstrated. [ABSTRACT FROM AUTHOR]