A field-based service management and discovery method in multiple clouds context

Zhang, Shuai; Mao, Xinjun; Hou, Fu; Liu, Peini

doi:10.1007/s11704-018-8012-1

Cited by 2 publications

(4 citation statements)

References 8 publications

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“…Also, Zhang et al (2019) suggested a field model of multiple cloud services and the appropriate service discovery mechanism to resolve the discovery problem. The model of Bohr atoms drives the method.…”

Section: Hybrid Mechanismsmentioning

confidence: 99%

“…The servers store the provided information about the services in this mechanism. First, an entity sends the request to the server to ask for a particular service, then it finds proper services and allocates them to the requester entity (Md et al , 2019; Zhang et al , 2019). A set of single or deterministic controllers is required to complete all query processes.…”

Section: Service Discovery Mechanismsmentioning

confidence: 99%

“…The cloud consumer might be charged for the service provision, and payments have to be arranged accordingly. Cloud consumers need service level agreements (SLAs) to determine the cloud provider's technical performance necessities (Zhang et al , 2019). A cloud provider may also list a set of promises not expressly made in the SLAs to consumers, that is, restrictions and commitments that cloud consumers have to accept (Chang et al , 2019; Madni et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Hybrid Mechanismsmentioning

confidence: 99%

Section: Service Discovery Mechanismsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Heidari

Navimipour

2021

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“…Therefore, efficient service discovery in the cloud is a significant challenge and an essential part of any distributed system ( Srirama, Paniagua & Liivi, 2013 ; Navimipour et al, 2014 ; Egbe et al, 2016 ). However, cloud computing managers can automatically or semi-automatically detect services or service information ( Afify et al, 2014 ; Zhang et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

A new SLA-aware method for discovering the cloud services using an improved nature-inspired optimization algorithm

Heidari

Navimipour

2021

PeerJ Computer Science

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Cloud computing is one of the most important computing patterns that use a pay-as-you-go manner to process data and execute applications. Therefore, numerous enterprises are migrating their applications to cloud environments. Not only do intensive applications deal with enormous quantities of data, but they also demonstrate compute-intensive properties very frequently. The dynamicity, coupled with the ambiguity between marketed resources and resource requirement queries from users, remains important issues that hamper efficient discovery in a cloud environment. Cloud service discovery becomes a complex problem because of the increase in network size and complexity. Complexity and network size keep increasing dynamically, making it a complex NP-hard problem that requires effective service discovery approaches. One of the most famous cloud service discovery methods is the Ant Colony Optimization (ACO) algorithm; however, it suffers from a load balancing problem among the discovered nodes. If the workload balance is inefficient, it limits the use of resources. This paper solved this problem by applying an Inverted Ant Colony Optimization (IACO) algorithm for load-aware service discovery in cloud computing. The IACO considers the pheromones’ repulsion instead of attraction. We design a model for service discovery in the cloud environment to overcome the traditional shortcomings. Numerical results demonstrate that the proposed mechanism can obtain an efficient service discovery method. The algorithm is simulated using a CloudSim simulator, and the result shows better performance. Reducing energy consumption, mitigate response time, and better Service Level Agreement (SLA) violation in the cloud environments are the advantages of the proposed method.

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A field-based service management and discovery method in multiple clouds context

Cited by 2 publications

References 8 publications

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

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

A new SLA-aware method for discovering the cloud services using an improved nature-inspired optimization algorithm

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