Quality of Service (QoS) Aware Workflow Scheduling (WFS) in Cloud Computing: A Systematic Review

Kaur, Simranjit; Bagga, Pallavi; Hans, Rahul; Kaur, Harpreet

doi:10.1007/s13369-018-3614-3

Cited by 40 publications

(19 citation statements)

References 101 publications

(88 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some studies believe that QoS must distinguish the level and this method has universal significance, but it needs to be refined for the specific problem domain of the grid. From the comprehensive evaluation given in Formula (17) and the judgment function provided in Formula (21), the trustworthiness level is classified through the algorithm flowchart described in Figure 6. The total completion time and total cost in the middle improves the fault tolerance of the scheduling and increases the reliability of the scheduling.…”

Section: B Results Analysismentioning

confidence: 99%

“…The goal of the technological progress in the latter stage is to transform the knowledge form results into application skills, improve the degree of technology diffusion, and enhance the technical adaptability. Collaborative and embedded technology advancement, the knowledge and skills with greater potential are infiltrated and transformed into high-tech patented results, and become the basis and reference for the application of technological advancement and innovation, improving the absorption and utilization of key core technologies, and promoting the pre-stage technology promotes critical technology or applied technology [21].…”

Section: B Results Analysismentioning

confidence: 99%

See 1 more Smart Citation

Grid Quality of Service Trustworthiness Evaluation Based on Bayesian Network

Huang

2020

IEEE Access

View full text Add to dashboard Cite

Quality of Service (QoS) is applied to evaluate the satisfaction level of users using a service and it is a measure and evaluation of the service level of service providers. As one of the significant contents of grid technologies, the QoS has gradually become a focus of current Internet researches. The grid is a network infrastructure that can aggregate decentralized resources to form a higher-level distributed resource sharing environment; the highly dynamic performance presented by the grid system is caused by resource competition and task uncertainty and providing extraordinary QoS is one of the three criteria for evaluating the grid technologies. Bayesian network is a method of graphing knowledge and is a probabilistic model which can be calculated; data from various sources can be synthesized and comprehensively reasoned through this Bayesian network. On the basis of summarizing and analyzing previous research works, this paper expounds the development background, current situation and future challenges of Bayesian network technology, presents the studying status and existing problems of grid QoS trustworthiness evaluation, introduces network optimization analysis method and QoS trustworthiness evaluation algorithm, proposes the Bayesian network-based trustworthiness model, effectiveness function and grid QoS evaluation reasoning process, therefore, establishes grid QoS trustworthiness evaluation model and analyzes Bayesian networkbased QoS trustworthiness evaluation mechanism. The simulation results show that the proposed method can enhance the trustworthiness of service information and improve the rationality of service matching in a dynamic service grid environment. The study results of this paper provide a reference for the further researches on the grid QoS trustworthiness evaluation based on Bayesian network. INDEX TERMS Quality of Service (QoS), Bayesian network, trustworthiness evaluation, simulation experiment.

show abstract

Section: B Results Analysismentioning

confidence: 99%

Section: B Results Analysismentioning

confidence: 99%

Grid Quality of Service Trustworthiness Evaluation Based on Bayesian Network

Huang

2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Smanchat and Viriyapant [10] classify the existing research according to scheduling process, task and resource which complements the workflow classification of grid computing. Kaur et al [11] discuss the heuristic, metaheuristic and hybrid methods about workflow scheduling. Reference [12] focus on using intelligent optimization algorithm to ensure security and obtain a good scheduling scheme at the same time.…”

Section: Related Workmentioning

confidence: 99%

Makespan-Driven Workflow Scheduling in Clouds Using Immune-Based PSO Algorithm

et al. 2020

View full text Add to dashboard Cite

Cloud Computing is becoming more and more popular for solving problems that need high concurrency and a lot of resources. Many traditional areas of research choose to solve their problems through the cloud, and workflow scheduling is one of them. Cloud computing brings many benefits, meanwhile, due to the almost ''infinite'' amount of resources for users, it also brings new challenges for scheduling and optimization, in which cost and makespan are the most concerned issues for workflow scheduling. Users want to obtain a low cost and fast makespan solution. This paper focuses on how to find an optimized solution to achieve better cost-makespan at the same time under the constraint of deadline. In order to solve this problem, an immune particle swarm optimization algorithm (IMPSO) is proposed, which effectively improves the quality and speed of the optimization. The proposed IMPSO overcomes the problem of slow convergence of PSO, which is easy to fall into local optimization. Experiments show the efficiency and effectiveness of the proposed approach. INDEX TERMS Cloud computing, workflow scheduling, immune mechanism, particle swarm algorithm.

show abstract

“…Workflow scheduling is a main issue in cloud computing, execution of inter dependent tasks take place along with considering Quality of Service (QOS) requirements. Quality of Service (QOS) aware workflow scheduling algorithm [23] compared 20-30 of heuristic, meta-heuristic, and hybrid algorithms with their numerous QOS constraints. It was concluded that most algorithms took makespan and cost as the reduction motives, so future work in workflow scheduling must consider fault tolerance along with load balancing, workflows security as well as protection of cloud recourses.…”

Section: Related Workmentioning

confidence: 99%

i- Rosa, Improved Uncertainty Aware Workflow Scheduling Algorithm

Bulchandani¹,

Agrawal²,

Chourasia³

et al. 2019

IJITEE

View full text Add to dashboard Cite

Many applications running in cloud computing environment are workflow applications which contain large number of precedence specific tasks and so require proper schedule in order to complete successfully. Efficient scheduling of workflow applications is a challenging task. In workflows, the uncertainties like ‘uncertain data transfer time’ among dependent tasks and the uncertain task execution time, if ignored may lead to deadline violation. The proposed workflow scheduling algorithms so far unconcerned these uncertainties. This paper presents an improved unceRtainty aware workflow scheduling algorithm abbreviated as i-ROSA, that considers the uncertainties of scheduling workflows such as the uncertain running time of tasks in distributed environment when focused upon gave the superior outcome in way of cost and resource utilization, for DAG when compared with the original algorithm. The compared task scheduling algorithms are implemented in Workflowsim.

show abstract

Quality of Service (QoS) Aware Workflow Scheduling (WFS) in Cloud Computing: A Systematic Review

Cited by 40 publications

References 101 publications

Grid Quality of Service Trustworthiness Evaluation Based on Bayesian Network

Grid Quality of Service Trustworthiness Evaluation Based on Bayesian Network

Makespan-Driven Workflow Scheduling in Clouds Using Immune-Based PSO Algorithm

i- Rosa, Improved Uncertainty Aware Workflow Scheduling Algorithm

Contact Info

Product

Resources

About