Reliability and temperature constrained task scheduling for makespan minimization on heterogeneous multi-core platforms

Zhou, Jianjiang; Cao, Kun; Cong, Peijin; Wei, Tongquan; Chen, Mingsong; Zhang, Gongxuan; Yan, Jianming; Ma, Yue

doi:10.1016/j.jss.2017.07.032

Cited by 55 publications

(13 citation statements)

References 24 publications

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“…In [17], mixed‐integer linear programming (MILP) formulations have been presented to minimise the makespan of independent task sets with temperature and reliability constraints. The authors of [17] proposed a two‐stage heuristic method which determines the assignment, operation frequency, execution order, and replication in order to minimise the makespan while satisfying thermal situation, reliability, and real‐time constraints. Online learning and Integer Linear Programming (ILP) have been adopted in [18, 19] to reduce the frequency of peak temperature constraint violations.…”

Section: Related Workmentioning

confidence: 99%

Temperature‐aware core management in MPSoCs: modelling and evaluation using MRMs

Taheri¹,

Khonsari²,

Entezari‐Maleki³

et al. 2019

IET Computers & Digital Techniques

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With successive scaling of CMOS technology, power density and cooling costs significantly increase. Consequently, the cooling system of processors can no longer be designed for the worst-case situation in each generation of CMOS technology and there is an essential need for run-time techniques to control the operating temperature. Task scheduling and resource management with respect to thermal constraints are run-time methods used to control the thermal profile of a system. In this study, the authors use Markov Reward Models (MRMs) to model and evaluate a new core thermal management method, which can reduce hotspots and balance the thermal profile of a multi-core system. Although the proposed management method degrades the performance of the system, such as other previously presented methods, it controls the temperature of a die to decrease the temperature variation and hotspots. The proposed approach is assessed on a quad-core system and the experimental results are compared to the results obtained from the proposed MRM to demonstrate the accuracy of the proposed analytical model.

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Section: Related Workmentioning

confidence: 99%

Temperature‐aware core management in MPSoCs: modelling and evaluation using MRMs

Taheri¹,

Khonsari²,

Entezari‐Maleki³

et al. 2019

IET Computers & Digital Techniques

View full text Add to dashboard Cite

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“…Obviously, the general solution of our problem consists of solving three set assignment problems which the sets are related to each other. The set assignment is in the category of combinatorial optimization problem and its NP-hardness is proved in [ 49 , 50 ]. Apparently, for small-scale networks a MILP solver can obtain the optimal solution.…”

Section: Problem Statement and Formulationmentioning

confidence: 99%

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

Vajdi

Zhang

Zhou

et al. 2018

Sensors

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We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

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“…Work°ow scheduling problem is widely considered to be a NP-complete problem. 5,6 These problems may not be able to¯nd the optimal solutions in reasonable time when the problems are solved by mathematical analysis. Therefore, researchers generally use heuristics or meta-heuristics to optimize the NPcomplete problem.…”

Section: Introductionmentioning

confidence: 99%

A Review of Cost and Makespan-Aware Workflow Scheduling in Clouds

Zhang

Zhu

et al. 2019

J CIRCUIT SYST COMP

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Scientific workflow is a common model to organize large scientific computations. It borrows the concept of workflow in business activities to manage the complicated processes in scientific computing automatically or semi-automatically. The workflow scheduling, which maps tasks in workflows to parallel computing resources, has been extensively studied over years. In recent years, with the rise of cloud computing as a new large-scale distributed computing model, it is of great significance to study workflow scheduling problem in the cloud. Compared with traditional distributed computing platforms, cloud platforms have unique characteristics such as the self-service resource management model and the pay-as-you-go billing model. Therefore, the workflow scheduling in cloud needs to be reconsidered. When scheduling workflows in clouds, the monetary cost and the makespan of the workflow executions are concerned with both the cloud service providers (CSPs) and the customers. In this paper, we study a series of cost-and-time-aware workflow scheduling algorithms in cloud environments, which aims to provide researchers with a choice of appropriate cloud workflow scheduling approaches in various scenarios. We conducted a broad review of different cloud workflow scheduling algorithms and categorized them based on their optimization objectives and constraints. Also, we discuss the possible future research direction of the clouds workflow scheduling.

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Reliability and temperature constrained task scheduling for makespan minimization on heterogeneous multi-core platforms

Cited by 55 publications

References 24 publications

Temperature‐aware core management in MPSoCs: modelling and evaluation using MRMs

Temperature‐aware core management in MPSoCs: modelling and evaluation using MRMs

A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

A Review of Cost and Makespan-Aware Workflow Scheduling in Clouds

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