A Novel Resource Discovery Mechanism using Sine Cosine Optimization Algorithm in Cloud

Moorthy, Rajalakshmi Shenbaga; Pabitha, P.

doi:10.1109/iciccs48265.2020.9121165

Cited by 13 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, resource management technology must successfully find and share resources. Researchers are VOLUME 12, 2024 continually investigating resource management solutions to support the Metaverse's implementation in heterogeneous environments and to provide a dynamic resource allocation framework to synchronize the Metaverse with IoT services and data [109], [110]. On the other hand, developers have also introduced cloud resource discovery mechanisms for the Metaverse environment [111].…”

Section: ) Resources Managementmentioning

confidence: 99%

Roles of Blockchain in the Metaverse: Concepts, Taxonomy, Recent Advances, Enabling Technologies, and Open Research Issues

Elsadig,

Alohali,

Ibrahim

et al. 2024

IEEE Access

View full text Add to dashboard Cite

The Metaverse platform offers 3D immersive experiences through virtual reality, artificial intelligence, and blockchain technologies. Blockchain-based Metaverse has garnered recent interest due to its decentralization, anonymity, and other security features. Integrating blockchain into Metaverse promotes the formation of a shared ecosystem and provides digital asset tracking, privacy protection, and security in both virtual and physical environments. This paper explores the role of blockchain in creating and managing the Metaverse platform. It is intended to provide a helpful reference for researchers and practitioners in the field of the blockchain-based Metaverse. The main topics covered include the concept and characteristics of the Metaverse; its different use cases, architectures, and technologies; Metaverse as a service provider; Metaverse management; Metaverse users and data; and blockchain-based Metaverse in terms of roles, technologies, applications, and challenges. In addition, recent advances in the blockchain-based Metaverse and challenges such as scalability, interoperability, and edge resource sharing will be discussed. The paper will conclude by highlighting open research issues and future directions, including improving immersion, scalability, security, and integration with existing systems.INDEX TERMS Blockchain, metaverse, Internet of Things (IoT), big data, cybersecurity.

show abstract

Section: ) Resources Managementmentioning

confidence: 99%

Roles of Blockchain in the Metaverse: Concepts, Taxonomy, Recent Advances, Enabling Technologies, and Open Research Issues

Elsadig,

Alohali,

Ibrahim

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Finally, Moorthy and Pabitha (2020) proposed a sine coined clustering-based method combined with a cloud-based service discovery mechanism. A metaheuristic algorithm named sine cosine optimization was introduced, which was employed to assess the maximal discovery of services.…”

Section: Decentralized Mechanismmentioning

confidence: 99%

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

Heidari

Navimipour

2021

View full text Add to dashboard Cite

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.

show abstract

“… Moorthy & Pabitha (2020) proposed a sine coined clustering-based method combined with a cloud-based service discovery mechanism. A metaheuristic algorithm called sine cosine optimization is used to evaluate the maximum service discovery.…”

Section: Related Workmentioning

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

View full text Add to dashboard Cite

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.

show abstract

A Novel Resource Discovery Mechanism using Sine Cosine Optimization Algorithm in Cloud

Cited by 13 publications

References 13 publications

Roles of Blockchain in the Metaverse: Concepts, Taxonomy, Recent Advances, Enabling Technologies, and Open Research Issues

Roles of Blockchain in the Metaverse: Concepts, Taxonomy, Recent Advances, Enabling Technologies, and Open Research Issues

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

Contact Info

Product

Resources

About