Energy-efficient scheduling with reliability guarantee in embedded real-time systems

Xu, Hongzhi; Li, Renfa; Zeng, Lining; Li, Keqin; Pan, Chen

doi:10.1016/j.suscom.2018.01.005

Cited by 13 publications

(1 citation statement)

References 33 publications

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“…It is a big concern towards environmental sustainability. At present, consumption of computing resources is 3(%) of the earth's power or electricity and possibly to be 10(%) by the year 2023 [5][6][7]. If the same trend continues, the cost of the energy consumed by the cloud server is more in lifetime than its real hardware prices.…”

Section: Introductionmentioning

confidence: 99%

A Novel Heuristic Max Ratio based Workflow Scheduling Algorithm for Cloud

Naik

Kuila

Biswas

et al. 2023

Preprint

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Workflow Scheduling Algorithm (WSA) for the cloud is one of the most trending issues in the research community. This is a Non-deterministic Polynomial (NP) complete problem. WSA has become more challenging due to the computation of valid sequences for dependent tasks by preserving precedence relationships. Here, a novel Heuristic Max Ratio Workflow Scheduling Algorithm (HMRWSA) is designed using the max ratio constraint as transfer delay and computation time of workflow applications. The proposed HMRWSA enhances the performance measure in terms of a number of conflicting objectives such as schedule length, energy consumption, utilization of virtual machines and speed-up ratio. Various scientific or benchmark workflow applications(WA) data sets are used to extensively simulate the algorithm. In terms of schedule length, utilisation, and spreedup ratio, the simulation results are compared to reputed heuristic approaches such as Critical-Path-on-Processor (CPOP), Heuristic Earliest Finish Time-Top (HEFT-T), Heuristic Earliest Finish Time-Button (HEFT-B), Performance Effective Task (PET), and Predict Earliest Finish Time (PEFT).

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Section: Introductionmentioning

confidence: 99%

A Novel Heuristic Max Ratio based Workflow Scheduling Algorithm for Cloud

Naik

Kuila

Biswas

et al. 2023

Preprint

View full text Add to dashboard Cite

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Energy Guarantee Scheme for Real-time Systems with Energy Harvesting Constraints

Ghor

Chetto

2019

Int. J. Autom. Comput.

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Enhanced Efficiency in Fog Computing: A Fuzzy Data-Driven Machine Selection Strategy

Zavieh,

Javadpour,

Ja’fari

et al. 2023

Int. J. Fuzzy Syst.

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With the rapid proliferation of IoT and Cloud networks and the corresponding number of devices, handling incoming requests has become a significant challenge. Task scheduling problems have emerged as a common concern, necessitating the exploration of new methods for request management. This paper proposes a novel approach called the Fuzzy Inverse Markov Data Envelopment Analysis Process (FIMDEAP). Our method combines the strengths of the Fuzzy Inverse Data Envelopment Analysis (FIDEA) and Fuzzy Markov Decision Process (FMDP) techniques to enable the efficient selection of physical and virtual machines while operating in a fuzzy mode. We represent data as triangular fuzzy numbers and employ the alpha-cut method to solve the proposed models. The paper provides a mathematical optimization model for the proposed method and presents a numerical example for illustration. Furthermore, we evaluate the performance of our method in a cloud environment through simulations. The results demonstrate that our approach outperforms existing methods, namely PSO + ACO and FBPSO + FBACO, in terms of key metrics, including energy consumption, execution cost, response time, gain of cost, and makespan.

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Energy-efficient scheduling with reliability guarantee in embedded real-time systems

Cited by 13 publications

References 33 publications

A Novel Heuristic Max Ratio based Workflow Scheduling Algorithm for Cloud

A Novel Heuristic Max Ratio based Workflow Scheduling Algorithm for Cloud

Energy Guarantee Scheme for Real-time Systems with Energy Harvesting Constraints

Enhanced Efficiency in Fog Computing: A Fuzzy Data-Driven Machine Selection Strategy

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