A Survey on Resource Management for Cloud Native Mobile Computing: Opportunities and Challenges

Huang, Shih-Yun; Chen, Cheng-Yu; Chen, Jen-Yeu; Chao, Han‐Chieh

doi:10.3390/sym15020538

Cited by 16 publications

(6 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The benefits of AI-driven resource management in cloud and edge computing environments have been highlighted in a study by Aryal and Altmann [22]. These benefits include the potential for a more resilient and cost-effective infrastructure, which supports superior operational performance and cost efficiency.…”

Section: Performance Improvementmentioning

confidence: 99%

Empowering Sustainable Industrial and Service Systems through AI-Enhanced Cloud Resource Optimization

Seo,

Yoo,

Lee

2024

Sustainability

View full text Add to dashboard Cite

This study focuses on examining the shift of an application system from a traditional monolithic architecture to a cloud-native microservice architecture (MSA), with a specific emphasis on the impact of this transition on resource efficiency and cost reduction. In order to evaluate whether artificial intelligence (AI) and application performance management (APM) tools can surpass traditional resource management methods in enhancing cost efficiency and operational performance, these advanced technologies are integrated. The research employs the refactor/rearchitect methodology to transition the system to a cloud-native framework, aiming to validate the enhanced capabilities of AI tools in optimizing cloud resources. The main objective of the study is to demonstrate how AI-driven strategies can facilitate more sustainable and economically efficient cloud computing environments, particularly in terms of managing and scaling resources. Moreover, the study aligns with model-based approaches that are prevalent in sustainable systems engineering by structuring cloud transformation through simulation-supported frameworks. It focuses on the synergy between endogenous AI integration within cloud management processes and the overarching goals of Industry 5.0, which emphasize sustainability and efficiency that not only benefit technological advancements but also enhance stakeholder engagement in a human-centric operational environment. This integration exemplifies how AI and cloud technology can contribute to more resilient and adaptive industrial and service systems, furthering the objectives of AI and sustainability initiatives.

show abstract

Section: Performance Improvementmentioning

confidence: 99%

Empowering Sustainable Industrial and Service Systems through AI-Enhanced Cloud Resource Optimization

Seo,

Yoo,

Lee

2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…In today's rapidly evolving technological landscape, organizations are constantly seeking ways to optimize their infrastructure to meet the increasing demands of scalability, flexibility, and efficiency. One approach that has gained significant attention is the MicroServices-Driven Enterprise Architecture Model [1,20].…”

Section: Related Workmentioning

confidence: 99%

“…Implementing MicroServices architecture can bring numerous benefits, but decision makers may face several challenges during the implementation process [17,20]. Here are some challenges that decision makers may face when implementing MicroServices architecture:…”

Section: Challenges That Decision Makers Face When Implementing Micro...mentioning

confidence: 99%

“…Decision makers may face challenges when implementing a MicroServices architecture, including complexity, integration, governance, testing, and organizational change. These challenges can be addressed and overcome, enabling an enterprise to reap the benefits of MicroServices architecture [17][18][19][20].…”

Section: Challenges That Decision Makers Face When Implementing Micro...mentioning

confidence: 99%

See 1 more Smart Citation

MicroServices-driven enterprise architecture model for infrastructure optimization

Abd-Elwahab,

Mohamed,

Shaaban

2023

Futur Bus J

View full text Add to dashboard Cite

Enterprise architecture (EA) is a discipline that is becoming increasingly important for businesses that are undergoing digital transformation. EA encompasses the practice of designing and managing the entire architecture of an organization, including its business processes, information systems, and technology infrastructure. In this paper, we will explore the main objectives of EA in digital transformation and the ways in which EA can help businesses achieve their digital transformation goals. Enterprise architects can use MicroServices technology to enable digital transformation by designing the MicroServices architecture, establishing best practices and standards, supporting tools such as DevOps, aligning with the enterprise's cloud strategy, and enabling data integration. Decision makers can use enterprise architecture with MicroServices to make digital transformation by leveraging the benefits of MicroServices architecture to achieve their digital transformation goals.

show abstract

“…These services are built upon containerization, which encapsulates individual application components and their dependencies into lightweight, isolated containers. This containerization allows for efficient resource utilization [2], facilitates rapid deployment, and ensures consistent behavior across different environments.…”

Section: Introductionmentioning

confidence: 99%

Security in Cloud-Native Services: A Survey

Theodoropoulos,

Rosa,

Benzaid

et al. 2023

JCP

View full text Add to dashboard Cite

Cloud-native services face unique cybersecurity challenges due to their distributed infrastructure. They are susceptible to various threats like malware, DDoS attacks, and Man-in-the-Middle (MITM) attacks. Additionally, these services often process sensitive data that must be protected from unauthorized access. On top of that, the dynamic and scalable nature of cloud-native services makes it difficult to maintain consistent security, as deploying new instances and infrastructure introduces new vulnerabilities. To address these challenges, efficient security solutions are needed to mitigate potential threats while aligning with the characteristics of cloud-native services. Despite the abundance of works focusing on security aspects in the cloud, there has been a notable lack of research that is focused on the security of cloud-native services. To address this gap, this work is the first survey that is dedicated to exploring security in cloud-native services. This work aims to provide a comprehensive investigation of the aspects, features, and solutions that are associated with security in cloud-native services. It serves as a uniquely structured mapping study that maps the key aspects to the corresponding features, and these features to numerous contemporary solutions. Furthermore, it includes the identification of various candidate open-source technologies that are capable of supporting the realization of each explored solution. Finally, it showcases how these solutions can work together in order to establish each corresponding feature. The insights and findings of this work can be used by cybersecurity professionals, such as developers and researchers, to enhance the security of cloud-native services.

show abstract

A Survey on Resource Management for Cloud Native Mobile Computing: Opportunities and Challenges

Cited by 16 publications

References 81 publications

Empowering Sustainable Industrial and Service Systems through AI-Enhanced Cloud Resource Optimization

Empowering Sustainable Industrial and Service Systems through AI-Enhanced Cloud Resource Optimization

MicroServices-driven enterprise architecture model for infrastructure optimization

Security in Cloud-Native Services: A Survey

Contact Info

Product

Resources

About