Virtual machine placement mechanisms in the cloud environments: a systematic review

Zhuang, Haiyan; Ghouchani, Babak Esmaeilpour

doi:10.1108/k-09-2019-0635

Cited by 10 publications

(8 citation statements)

References 83 publications

(95 reference statements)

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“…Several cutting‐edge VMPs were studied in the cloud computing environment. Besides, Zhuang and Ghouchani 30 showed and disputed outstanding problems through an in‐depth examination of over 40 important articles selected from the 320 publications found automatically during the search. Also, Gupta and Pateriya 31 described a variety of VMP strategies and their flaws.…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…Alboaneen et al 29 discovered that when it came to objective functions in VMP, most researchers concentrated on reducing data center energy usage, with some others addressing performance and resource usage concerns. Additionally, in cloud contexts, Zhuang and Ghouchani 30 proposed a systematic literature review of VMP approaches. Several cutting-edge VMPs were studied in the cloud computing environment.…”

Section: Related Work and Motivationmentioning

confidence: 99%

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Nature‐inspired virtual machine placement mechanisms: A systematic review

Kong

He²,

Abnoosian

2022

Concurrency and Computation

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Cloud data centers do not completely use their resources, resulting in resource underutilization. Cloud computing companies primarily leverage virtualization technologies to supply cost-effective service provision. In order to optimize cloud performance, virtual machines (VMs) must be placed among physical machines (PMs). When it comes to concentrating on the issues in the cloud computing environment, effective VM placement (VMP) is one of the primary difficulties that might cost suppliers money. VMP may be applied in a variety of ways in cloud computing. In terms of lowering related processing overhead, consolidating the cloud environment to become a highly on-demand method, balancing the load among PMs, power usage, and refining performance, VMP techniques still require improvement in the computing environment. This study aims to provide a comprehensive overview of VMP approaches. This article provides an up-to-date survey of the most related VMP literature to highlight study possibilities in cloud settings utilizing nature-inspired metaheuristic algorithms. The findings suggest that placing VMs in the most efficient place saves power usage substantially. The key problem is to minimize data center energy usage without compromising performance or breaking service level agreements. Finally, we will discuss and look at what further may be accomplished in this line of science.

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Section: Related Work and Motivationmentioning

confidence: 99%

Section: Related Work and Motivationmentioning

confidence: 99%

Nature‐inspired virtual machine placement mechanisms: A systematic review

Kong

He²,

Abnoosian

2022

Concurrency and Computation

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“…Recently, cloud advancement significantly improved computational history (Polepally and Chatrapati, 2018). The infinite services, the capability to spend money for utilization, removal of an up-front dedication, higher utilization and increasing the utilization of services are considered the advantages of cloud computing (Sharma and Kalra, 2019; Al-Sayed et al , 2020; Zhuang and Ghouchani, 2021).…”

Section: Introductionmentioning

confidence: 99%

Service discovery mechanisms in cloud computing: a comprehensive and systematic literature review

Heidari

Navimipour

2021

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PurposeThe main goal of this paper is to study the cloud service discovery mechanisms. In this paper, the discovery mechanisms are ranked in three major classes: centralized, decentralized, and hybrid. Moreover, in this classification, the peer-to-peer (P2P) and agent-based mechanisms are considered the parts of the decentralized mechanism. This paper investigates the main improvements in these three main categories and outlines new challenges. Moreover, the other goals are analyzing the current challenges in a range of problem areas related to cloud discovery mechanisms and summarizing the discussed service discovery techniques.Design/methodology/approachSystematic literature review (SLR) is utilized to detect, evaluate and combine findings from related investigations. The SLR consists of two key stages in this paper: question formalization and article selection processes. The latter includes three steps: automated search, article selection and analysis of publication. These investigations solved one or more service discovery research issues and performed a general study of an experimental examination on cloud service discovery challenges.FindingsIn this paper, a parametric comparison of the discovery methods is suggested. It also demonstrates future directions and research opportunities for cloud service discovery. This survey will help researchers understand the advances made in cloud service discovery directly. Furthermore, the performed evaluations have shown that some criteria such as security, robustness and reliability attained low attention in the previous studies. The results also showed that the number of cloud service discovery–related articles rose significantly in 2020.Research limitations/implicationsThis research aimed to be comprehensive, but there were some constraints. The limitations that the authors have faced in this article are divided into three parts. Articles in which service discovery was not the primary purpose and their title did not include the related terms to cloud service discovery were also removed. Also, non-English articles and conference papers have not been reviewed. Besides, the local articles have not been considered.Practical implicationsOne of the most critical cloud computing topics is finding appropriate services depending on consumer demand in real-world scenarios. Effective discovery, finding and selection of relevant services are necessary to gain the best efficiency. Practitioners can thus readily understand various perspectives relevant to cloud service discovery mechanisms. This paper's findings will also benefit academicians and provide insights into future study areas in this field. Besides, the drawbacks and benefits of the analyzed mechanisms have been analyzed, which causes the development of more efficient and practical mechanisms for service discovery in cloud environments in the future.Originality/valueThis survey will assist academics and practical professionals directly in their understanding of developments in service discovery mechanisms. It is a unique paper investigating the current and important cloud discovery methods based on a logical categorization to the best of the authors’ knowledge.

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“…Moreover, several important issues should be considered during developing cloud computing applications, including task scheduling, virtual machine placement, reliability, trust, transparency access, bandwidth costs, etc. (Yang et al , 2020; Zhuang and Ghouchani, 2020). To satisfy the cloud clients' requests and meet their needs, diverse types of services need to be offered.…”

Section: Introductionmentioning

confidence: 99%

Toward the efficient service selection approaches in cloud computing

Rahimi

Navimipour

Hosseinzadeh

et al. 2021

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PurposeThis paper follows a systematic literature review (SLR) method covering the published studies until March 2021. The authors have extracted the related studies from different online databases utilizing quality-assessment-criteria. In order to review high-quality studies, 32 papers have been chosen through the paper selection process. The selected papers have been categorized into three main groups, decision-making methods (17 papers), meta-heuristic methods (8 papers) and fuzzy-based methods (7 papers). The existing methods in each group have been examined based on important qualitative parameters, namely, time, cost, scalability, efficiency, availability and reliability.Design/methodology/approachCloud computing is known as one of the superior technologies to perform large-scale and complex computing. With the growing tendency of network service users to utilize cloud computing, web service providers are encouraged to provide services with various functional and non-functional features and supply them in a service pool. In this regard, choosing the most appropriate services to fulfill users' requirements becomes a challenging problem. Since the problem of service selection in a cloud environment is known as a nondeterministic polynomial time (NP)-hard problem, many efforts have been made in recent years. Therefore, this paper aims to study and assess the existing service selection approaches in cloud computing.FindingsThe obtained results indicate that in decision-making methods, the assignment of proper weights to the criteria has a high impact on service ranking accuracy. Also, since service selection in cloud computing is known as an NP-hard problem, utilizing meta-heuristic algorithms to solve this problem offers interesting advantages compared to other approaches in discovering better solutions with less computational effort and moving quickly toward very good solutions. On the other hand, since fuzzy-based service selection approaches offer search results visually and cover quality of service (QoS) requirements of users, this kind of method is able to facilitate enhanced user experience.Research limitations/implicationsAlthough the current paper aimed to provide a comprehensive study, there were some limitations. Since the authors have applied some filters to select the studies, some effective works may have been ignored. Generally, this paper has focused on journal papers and some effective works published in conferences. Moreover, the works published in non-English formats have been excluded. To discover relevant studies, the authors have chosen Google Scholar as a popular electronic database. Although Google Scholar can offer the most valid approaches, some suitable papers may not be observed during the process of article selection.Practical implicationsThe outcome of the current paper will be useful and valuable for scholars, and it can be a roadmap to help future researchers enrich and improve their innovations. By assessing the recent efforts in service selection in cloud computing and offering an up-to-date comparison of the discussed works, this paper can be a solid foundation for understanding the different aspects of service selection.Originality/valueAlthough service selection approaches have essential impacts on cloud computing, there is still a lack of a detailed and comprehensive study about reviewing and assessing existing mechanisms in this field. Therefore, the current paper adopts a systematic method to cover this gap. The obtained results in this paper can help the researchers interested in the field of service selection. Generally, the authors have aimed to specify existing challenges, characterize the efficient efforts and suggest some directions for upcoming studies.

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Virtual machine placement mechanisms in the cloud environments: a systematic review

Cited by 10 publications

References 83 publications

Nature‐inspired virtual machine placement mechanisms: A systematic review

Nature‐inspired virtual machine placement mechanisms: A systematic review

Service discovery mechanisms in cloud computing: a comprehensive and systematic literature review

Toward the efficient service selection approaches in cloud computing

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