Deadline Aware Energy-Efficient Task Scheduling Model for a Virtualized Server

Garg, Neha; Singh, Damanpreet; Goraya, Major Singh

doi:10.1007/s42979-021-00571-2

Cited by 5 publications

(3 citation statements)

References 26 publications

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“…As shown in Table 1, the virtual machine parameters mainly refer to Alibaba Cloud's Elasticsearch, and the SLA penalty factor is the same. The task set to be scheduled was randomly simulated [8] , with the restriction 𝑏𝑎𝑠𝑒𝑇 𝑖 ∈ [1,10] and 𝐷 𝑖 ∈ [1,6]. Result analysis: Figure 1 shows the iteration efficiency of the algorithms of IGA and GA.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…Task scheduling has been an important problem in the field of cloud services [1][2][3] . Most studies focus on independent tasks scheduling, such as proposing ant colony algorithms [4] , and whale optimization algorithms [5] to reduce costs [6,7] . However, approximate query task scheduling for BDAaaS involves the sequential dependencies between tasks.…”

Section: Introductionmentioning

confidence: 99%

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Task scheduling optimization considering SLA for big data analytics-as-a-service in cloud computing services

Ye,

Cheng,

Jin

2023

Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023)

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Big Data Analytics-as-a-Service (BDAaaS) is an emerging cloud computing service designed to provide big data analytics. BDAaaS offers approximate query services to meet the requirements of fast response but without high accuracy by users. So, service response in Service Agreement Level (SLA) are more stringent and BDAaaS faces greater risk of penalty payout. In this paper, we proposed a task scheduling model that takes SLA into account for the problem of sequential dependencies of some tasks. And a greedy strategy was used to improve the genetic algorithm to solve the model efficiently. Simulation experimental results show that the method in this paper can obtain task scheduling schemes with lower cost and SLA violation rate under limited resources.

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Section: Performance Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Task scheduling optimization considering SLA for big data analytics-as-a-service in cloud computing services

Ye,

Cheng,

Jin

2023

Third International Conference on Green Communication, Network, and Internet of Things (CNIoT 2023)

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show abstract

“…Beloglazov et al [12], as pioneers, designed an energyefficient cloud computing architecture model based on CPU and proposed an energyefficient resource allocation algorithm, but did not consider hardware resources other than CPU. Garg et al [13] considered multiple resources; they first designed a mathematical model to measure the energy consumption in the process of task execution, and then proposed a scheduling algorithm that can minimize the average energy consumption of each task. Mekala et al [14] classified tasks and VMs, and scheduled tasks to corresponding VMs based on the classification results.…”

Section: Related Workmentioning

confidence: 99%

Research on Cloud Task Scheduling Algorithm with Conflict Constraints Based on Branch-and-Price

Xie

Zhang

et al. 2023

Applied Sciences

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The low-energy task scheduling of cloud computing systems is a key issue in the field of cloud computing. Nevertheless, existing works on task scheduling lack consideration of the conflict relationship between tasks and focus on heuristic and other approximate algorithms. Thus, solving the problem of minimizing energy consumption with antiaffinity constraints between tasks and designing an efficient exact algorithm for task scheduling is a major challenge. This paper abstracts the problem into a multidimensional bin packing model with conflict constraints. The model is decomposed by the Lagrange relaxation principle and Dantzig–Wolfe decomposition principle. Moreover, we propose an accurate algorithm based on branch-and-price. The algorithm benefits from a new initial solution generation scheme based on maximum cliques and dominant resource proportion, and a multipattern branching strategy. The efficiency of the proposed branch-and-price algorithm is verified by a number of numerical experiments.

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A quantum inspired hybrid SSA–GWO algorithm for SLA based task scheduling to improve QoS parameter in cloud computing

Jain

Sharma

2022

Cluster Comput

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Deadline Aware Energy-Efficient Task Scheduling Model for a Virtualized Server

Cited by 5 publications

References 26 publications

Task scheduling optimization considering SLA for big data analytics-as-a-service in cloud computing services

Task scheduling optimization considering SLA for big data analytics-as-a-service in cloud computing services

Research on Cloud Task Scheduling Algorithm with Conflict Constraints Based on Branch-and-Price

A quantum inspired hybrid SSA–GWO algorithm for SLA based task scheduling to improve QoS parameter in cloud computing

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