A Real-Time Scheduling Algorithm for Embedded Systems With Various Resource Requirements

Chen, Tianzhou; Hu, Wei; Xie, Bin; Yan, Like

doi:10.1109/iwnas.2006.12

Cited by 5 publications

(3 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To cope with ever-increasing task heterogeneity, a series of relevant hybrid scheduling approaches have employed carefully chosen ensembles of scheduling algorithms. From this perspective, three interesting methods attracted our interest: (a) an effective method to combine the offline scheduling techniques with the online ones which is based on the conversion of the offline schedules into task attributes for fixed priority scheduling [ 17 ]; (b) an approach for hybrid scheduling proposed in [ 18 ], where the tasks are divided in sets according to some common features and later scheduled within their own set (each set can have its own scheduling algorithm); and (c) a hybrid preemptive scheme known as Earliest Deadline Zero Laxity (EDZL) [ 19 ] which proposes the use of the global EDF algorithm until one of the tasks reaches zero slack (or zero laxity). In this circumstance, the priority of the mentioned task is immediately raised to the highest level.…”

Section: Related Workmentioning

confidence: 99%

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

Micea

Stangaciu

et al. 2017

Sensors

View full text Add to dashboard Cite

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H2RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H2RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

show abstract

Section: Related Workmentioning

confidence: 99%

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

Micea

Stangaciu

et al. 2017

Sensors

View full text Add to dashboard Cite

show abstract

“…The technological evolution of devices currently provides sufficient performance to implement complex planning strategies on them. These strategies delegate to a realtime operating system embedded in devices, the execution planning, and management of tasks to meet the constraints imposed by the applications [5][6][7]. In environments involving multiple devices, it is possible to establish planning methods that take into account multiprocessing scenarios in one [8,9] or more embedded elements with heterogeneous characteristics [10,11].…”

Section: Related Workmentioning

confidence: 99%

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

Mora

Gil

Lopez

et al. 2015

Mobile Information Systems

View full text Add to dashboard Cite

The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.

show abstract

“…In every Embedded System (ES) platform, the use of threads is crucial due to the efficient handling of scarce resources allowing faster executions in a reasonable fashion [3]. The scheduling policy is a recurrent issue in OS implementation because it affects the execution efficiency directly [4]. It aims to use the target architecture resources rationally according to the application instruction set.…”

Section: Introductionmentioning

confidence: 99%

A Framework Prototype for Multithreaded Implementation Over Micro-Controllers

Nagel¹,

Czekster

Webber³

et al. 2019

JICS

View full text Add to dashboard Cite

Multithreading is pervasive in embedded system applications development. The applications requirements are becoming more rigorous, demanding the execution of concurrent tasks that must also take into account modularity and flexibility. An important part of the operating systems development concerns the implementation of scheduling algorithms. In an embedded system context, it is essential to consider that the scheduling algorithm heavily influences application behavior. Due to restricted and finite hardware resources, it is important to evaluate the use of flexible algorithms to guarantee efficiency. Currently, projects for embedded operating systems do exist for microcontrollers’ devices that implement scheduling algorithms, however, the developer cannot change or add new scheduling policies without implementing kernel tweaks and modifications. The alternatives are not flexible when choosing the scheduling algorithm according to the application needs. This imposes restrictions to many systems, forcing them to run specific static scheduling algorithms because no other options are available. The objective of this work concerns the design and development of a framework that implements a microkernel with a modular scheduler unit, allowing the execution of tailored algorithms according to the application profile. The idea is to provide a flexible platform to conveniently select the most appropriated algorithm. We have employed low capacity hardware to implement multithreading patterns corresponding to sets of concurrent tasks, demonstrating the strengths of adopting our approach. Our results show that the use of modern techniques that combine modularity, multithreading, and scheduling methods for embedded systems yield best executions when compared to its sequential counterparts.

show abstract

A Real-Time Scheduling Algorithm for Embedded Systems With Various Resource Requirements

Cited by 5 publications

References 7 publications

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

Flexible Framework for Real-Time Embedded Systems Based on Mobile Cloud Computing Paradigm

A Framework Prototype for Multithreaded Implementation Over Micro-Controllers

Contact Info

Product

Resources

About