Task period selection to minimize hyperperiod

Brocal, Vicent; Balbastre, Patricia; Ballester, Rafael; Ripoll, Ismael

doi:10.1109/etfa.2011.6059178

Cited by 26 publications

(17 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…One primary driver for high CPU clock-cycles is the poor design of periods of input tasks which lead to a high value of hyper-period. Therefore, the hyper-period optimisation is the focus of many researchers to optimise the power and energy [20,21,29]. As discussed that a high value of hyper-period is produced due to the poor design of tasks' periods, therefore, the period is considered a key parameter in the design of the input tasks for real-time systems.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

et al. 2018

View full text Add to dashboard Cite

Embedded devices are gaining popularity day by day due to the expanded use of Internet of Things applications. However, these embedded devices have limited capabilities concerning power and memory. Thus, the applications need to be tailored in such a way to perform the specified tasks within the constrained resources with the same accuracy. In Real-Time task scheduling, one of the challenging factors is the intelligent modelling of input tasks in such a way that it produces not only logically correct output within the deadline but also consumes minimum CPU power. Algorithms like Rate Monotonic and Earliest Deadline First compute hyper-period of input tasks for periodic repetition of the same set of tasks on CPU. However, at times when the tasks are not adequately modelled, they lead to an enormously high value of hyper-period which result in more CPU cycles and power consumption. Many state-of-the-art solutions are presented in this regard, but the main problem is that they limit tasks from having all possible period values; however, with the vision of Industry 4.0, where most of the tasks will be doing some critical manufacturing activities, it is highly discouraged to prevent them of a certain period. In this paper, we present a resource-aware approach to minimise the hyper-period of input tasks based on device profiles and allows tasks of every possible period value to admit. The proposed work is compared with similar existing techniques, and results indicate significant improvements regarding power consumptions.

show abstract

Section: Related Workmentioning

confidence: 99%

“…Similarly, while computing periods for a given tasks' set, different approaches for reducing the hyper-period are presented in [29,40]. However, the underlying assumption for the validity of such research is that given tasks are executed over a uni-processor platform independently.…”

Section: Related Workmentioning

confidence: 99%

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

et al. 2018

View full text Add to dashboard Cite

show abstract

“…In [15], Borcal et al presented a periodic task model where the periods are defined as ranges (min, max values) and presented an heuristic algorithm for finding the set of periods that gives the minimal lcm. The resulting adjusted periods are natural numbers.…”

Section: Adjustedp Eriodmentioning

confidence: 99%

“…The remaining set of factors can be calculated iteratively with N = N/p 1 . An efficient approach to this problem was presented in [15]. It consists of an heuristic that first computes all the lcm's of a subset of the tasks (those with smaller ranges), and then performs an exhaustive search of this set of candidates on the remaining set of tasks.…”

Section: Problem Statementmentioning

confidence: 99%

Period Selection for Minimal Hyperperiod in Periodic Task Systems

Ripoll

Ballester-Ripoll²

2013

IEEE Trans. Comput.

View full text Add to dashboard Cite

Abstract-Task period and deadline selection are often used to adjust the workload to the available computational resources. This paper presents a method for adjusting the periods of the tasks which obtains the minimal hyper-period. Task periods are modelled as a range of possible periods. The selected periods are not constrained to be natural numbers, but can also be rational numbers. Without this limitation, the resulting hyper-period is much smaller than that of previous works. Hyper-period for natural periods grows exponentially; with rational periods the worst case is quadratic with the largest period. Our finding has practical applications in several fields of real-time scheduling: lowering complexity in table driven schedulers, reducing search space in model checking analysis, generating synthetic workload for statistical analysis of real-time scheduling algorithms, etc.

show abstract

“…Harmonic periods are demanded in a wide spectrum of industrial real-time applications such as avionics, submarines, and robotics [27,108,146,12] as well as control systems with nested feedback loops [51]. Tasks with a harmonic relationship have a smaller hyperperiod [137,25], which is a key concern for time-triggered embedded systems [92].…”

Section: Rate Monotonic Scheduling (Rms)mentioning

confidence: 99%

On the Design of Real-Time Systems on Multi-Core Platforms under Uncertainty

Wang¹

View full text Add to dashboard Cite

To ensure timing constraints, traditional real-time system designs usually adopt a worst-case based deterministic approach. However, such an approach is becoming out of sync with the continuous evolution of IC technology and increased complexity of real-time applications. As IC technology continues to evolve into the deep submicron domain, process variation causes processor performance to vary from die to die, chip to chip, and even core to core. The extensive resource sharing on multicore platforms also significantly increases the uncertainty when executing real-time tasks. The traditional approach can only lead to extremely pessimistic, and thus, unpractical design of real-time systems.Our research seeks to address the uncertainty problem when designing real-time systems on multi-core platforms. We first attacked the uncertainty problem caused by process variation. We proposed a virtualization framework and developed techniques to optimize the system's performance under process variation. We further studied the problem on peak temperature minimization for real-time applications on multi-core platforms. Three heuristics were developed to reduce the peak temperature for real-time systems. Next, we sought to address the uncertainty problem vi in real-time task execution times by developing statistical real-time scheduling techniques. We studied the problem of fixed-priority real-time scheduling of implicit periodic tasks with probabilistic execution times on multi-core platforms. We further extended our research for tasks with explicit deadlines. We introduced the concept of harmonic to a more general task set, i.e. tasks with explicit deadlines, and developed new task partitioning techniques. Throughout our research, we have conducted extensive simulations to study the effectiveness and efficiency of our developed techniques.The increasing process variation and the ever-increasing scale and complexity of real-time systems both demand a paradigm shift in the design of real-time applications. Effectively dealing with the uncertainty in design of real-time applications is a challenging but also critical problem. Our research is such an effort in this endeavor, and we conclude this dissertation with discussions of potential future work.

show abstract

Task period selection to minimize hyperperiod

Cited by 26 publications

References 5 publications

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

An Adaptive Approach Based on Resource-Awareness Towards Power-Efficient Real-Time Periodic Task Modeling on Embedded IoT Devices

Period Selection for Minimal Hyperperiod in Periodic Task Systems

On the Design of Real-Time Systems on Multi-Core Platforms under Uncertainty

Contact Info

Product

Resources

About