Fixed-Priority Allocation and Scheduling for Energy-Efficient Fault Tolerance in Hard Real-Time Multiprocessor Systems

Wei, Tongquan; Mishra, Piyush; Wu, Kaijie; Han, Liang

doi:10.1109/tpds.2008.127

Cited by 26 publications

(16 citation statements)

References 32 publications

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“…Some works, e.g. [5] [16], [17], [18], [38], have proposed energy-management techniques for task-level redundancy in multi-core systems. [5] and [16] have considered only one faulty execution for each task to preserve the original system reliability, while for many applications (e.g., the applications that are used in harsh environments) a high level of reliability cannot be achieved unless tolerating multiple faulty tasks [9], [10], [17], [18].…”

Section: Related Workmentioning

confidence: 99%

“…Some works have considered different application models, e.g. periodic independent real-time tasks in [17] and [38] and parallel independent applications in [18]. However, these works cannot be applied to tasks with precedence constraints (e.g., task graphs [5], [6], [7]), while we consider hard real-time applications with task precedence constraint and propose a scheduling and energy-management technique for these applications.…”

Section: Related Workmentioning

confidence: 99%

“…To reduce the energy overhead, we propose an energy-management technique that bears the major contributions of the work and is specifically developed for NMR when used for hard realtime multi-core systems (Sections 3 and 4). The main contributions of this work are: i) Considering the dominance of the fault-free execution on faulty executions [6] [8] [38], a two-phase NMR is proposed that achieves minimized energy consumption in the absence of faults while guaranteeing reliability and deadline requirements. ii) A specific type of slack time, called pseudo dynamic slack, is considered in this work.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Two-Phase Low-Energy N-Modular Redundancy for Hard Real-Time Multi-Core Systems

Salehi

Ejlali

Al-Hashimi

2016

IEEE Trans. Parallel Distrib. Syst.

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Abstract-This paper proposes an N-modular redundancy (NMR) technique with low energy-overhead for hard real-time multicore systems. NMR is well-suited for multi-core platforms as they provide multiple processing units and low-overhead communication for voting. However, it can impose considerable energy overhead and hence its energy overhead must be controlled, which is the primary consideration of this paper. For this purpose the system operation can be divided into two phases: indispensable phase and on-demand phase. In the indispensable phase only half-plus-one copies for each task are executed. When no fault occurs during this phase, the results must be identical and hence the remaining copies are not required. Otherwise, the remaining copies must be executed in the on-demand phase to perform a complete majority voting. In this paper, for such a two-phase NMR, an energy-management technique is developed where two new concepts have been considered: i) Block-partitioned scheduling that enables parallel task execution during on-demand phase, thereby leaving more slack for energy saving, ii) Pseudo-dynamic slack, that results when a task has no faulty execution during the indispensable phase and hence the time which is reserved for its copies in the on-demand phase is reclaimed for energy saving. The energymanagement technique has an off-line part that manages static and pseudo-dynamic slacks at design time and an online part that mainly manages dynamic slacks at run-time. Experimental results show that the proposed NMR technique provides up to 29% energy saving and is 6 orders of magnitude higher reliable as compared to a recent previous work.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Two-Phase Low-Energy N-Modular Redundancy for Hard Real-Time Multi-Core Systems

Salehi

Ejlali

Al-Hashimi

2016

IEEE Trans. Parallel Distrib. Syst.

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“…A heuristic algorithm to assign tasks to a set of processing sites by balancing the load over different processors is described in [10]. An Energy-efficient task allocation and scheduling schemes with deterministic faulttolerance capabilities are proposed for symmetric multiprocessor systems when executing tasks with hard real-time constraints is described in [11]. This is achieved by optimally balancing the workload in the system.…”

Section: Related Workmentioning

confidence: 99%

Minimal Task Allocation in Multiprocessors using improved next-fit for RM scheduling

B¹,

Pillai²

2012

IJCA

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Task-processor allocation in multiprocessors can be accomplished efficiently for reducing the required number of processors for the given task set, accounting reduced power consumption with maximum processor utilization. This work is based on next fit algorithm using Rate Monotonic Algorithm (RMA) for a fixed priority system. The work proposes a minimal task allocation algorithm for multiprocessor environment. The proposed method reduces the number of processors required for a given task set using improved next fit algorithm and the same has been evaluated and tested. The proposed algorithm gives better results when there is large number of tasks in the system.

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“…fault detection followed by fault recovery [123]. Examples of techniques that can detect the processor faults timely and effectively are listed below [123,98]:…”

Section: Fault Tolerance/reliability In Real-time Systemsmentioning

confidence: 99%

Energy-aware Fault-tolerant Scheduling for Hard Real-time Systems

Han¹

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Fixed-Priority Allocation and Scheduling for Energy-Efficient Fault Tolerance in Hard Real-Time Multiprocessor Systems

Cited by 26 publications

References 32 publications

Two-Phase Low-Energy N-Modular Redundancy for Hard Real-Time Multi-Core Systems

Two-Phase Low-Energy N-Modular Redundancy for Hard Real-Time Multi-Core Systems

Minimal Task Allocation in Multiprocessors using improved next-fit for RM scheduling

Energy-aware Fault-tolerant Scheduling for Hard Real-time Systems

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