Resource scheduling for infrastructure as a service (IaaS) in cloud computing: Challenges and opportunities

Madni, Syed Hamid Hussain; Latiff, Muhammad Shafie Abd; Coulibaly, Yahaya; Abdulhamid, Shafií Muhammad

doi:10.1016/j.jnca.2016.04.016

Cited by 166 publications

(66 citation statements)

References 106 publications

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“…The workflow tasks are assigned based on their functional and non-functional QoS requirements. In cloud technology, load balancing approaches are mainly focusing on the provision of the following criteria [10][11][12][13]:…”

Section: Types and Objectives Of The Scheduling Methods For Load Balamentioning

confidence: 99%

Multicriteria Optimization Method for Load Balancing in Cloud Computing

Alguliyev¹,

İmamverdiyev²,

Abdullayeva³

2017

JPIT

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Section: Types and Objectives Of The Scheduling Methods For Load Balamentioning

confidence: 99%

Multicriteria Optimization Method for Load Balancing in Cloud Computing

Alguliyev¹,

İmamverdiyev²,

Abdullayeva³

2017

JPIT

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“…• Execution Time: is a time in which cloudlets or tasks are running or computing as the demand of the cloud users. It is also known as completion time, which is required for the specific cloudlets or tasks to complete the job [138].…”

Section: Analysis Of Resources and Parameters Used In Current Studiesmentioning

confidence: 99%

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

et al. 2016

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There are two actors in cloud computing environment cloud providers and cloud users. On one hand cloud providers hold enormous computing resources in the cloud large data centers that rent the resources out to the cloud users on a pay-per-use basis to maximize the profit by achieving high resource utilization. On the other hand cloud users who have applications with loads variation and lease the resources from the providers they run their applications within minimum expenses. One of the most critical issues of cloud computing is resource management in infrastructure as a service (IaaS). Resource management related problems include resource allocation, resource adaptation, resource brokering, resource discovery, resource mapping, resource modeling, resource provisioning and resource scheduling. In this review we investigated resource allocation schemes and algorithms used by different researchers and categorized these approaches according to the problems addressed schemes and the parameters used in evaluating different approaches. Based on different studies considered, it is observed that different schemes did not consider some important parameters and enhancement is required to improve the performance of the existing schemes. This review contributes to the existing body of research and will help the researchers to gain more insight into resource allocation techniques for IaaS in cloud computing in the future.

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“…The cloud computing algorithm includes resource management algorithm and workflow task scheduling algorithm. The resource management scheme is that how to rent the resources out to the cloud users on a pay‐per‐use basis to maximize the profit by achieving high‐resource utilization, Madni et al investigate resource management schemes and algorithms and analyses and evaluates these schemes (Madni, Lati, Coulibaly, & Abdulhamid, ; Madni, Latiff, Coulibaly, et al, ). The workflow task scheduling algorithm is a branch of cloud computing scheduling algorithms (Masdari, Valikardan, Shahi, et al, ), which used to map task node to the suitable server and of ordering the task nodes on each server to satisfy some performance criterion.…”

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

A scheduling algorithm for applications in a cloud computing system with communication changes

Shao

Xie

2018

Expert Systems

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This paper proposes a scheduling algorithm to solve the problem of task scheduling in a cloud computing system with time‐varying communication conditions. This algorithm converts the scheduling problem with communication changes into a directed acyclic graph (DAG) scheduling problem for existing fuzzy communication task nodes, that is, the scheduling problem for a communication‐change DAG (CC‐DAG). The CC‐DAG contains both computation task nodes and communication task nodes. First, this paper proposes a weighted time‐series network bandwidth model to solve the indefinite processing time (cost) problem for a fuzzy communication task node. This model can accurately predict the processing time of a fuzzy communication task node. Second, to address the scheduling order problem for the computation task nodes, a dynamic pre‐scheduling search strategy (DPSS) is proposed. This strategy computes the essential paths for the pre‐scheduling of the computation task nodes based on the actual computation costs (times) of the computation task nodes and the predicted processing costs (times) of the fuzzy communication task nodes during the scheduling process. The computation task node with the longest essential path is scheduled first because its completion time directly influences the completion time of the task graph. Finally, we demonstrate the proposed algorithm via simulation experiments. The experimental results show that the proposed DPSS produced remarkable performance improvement rate on the total execution time that ranges between 11.5% and 21.2%. In view of the experimental results, the proposed algorithm provides better quality scheduling solution that is suitable for scientific application task execution in the cloud computing environment than HEFT, PEFT, and CEFT algorithms.

show abstract

Resource scheduling for infrastructure as a service (IaaS) in cloud computing: Challenges and opportunities

Cited by 166 publications

References 106 publications

Multicriteria Optimization Method for Load Balancing in Cloud Computing

Multicriteria Optimization Method for Load Balancing in Cloud Computing

Recent advancements in resource allocation techniques for cloud computing environment: a systematic review

A scheduling algorithm for applications in a cloud computing system with communication changes

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