Performance Metrics of Local Cloud Computing Architectures

Brummett, Travis; Sheinidashtegol, Pezhman; Sarkar, Debadrita; Galloway, Michael

doi:10.1109/cscloud.2015.61

Cited by 8 publications

(4 citation statements)

References 1 publication

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“…• Local Cloud is administered by internal or external sources explicitly intended for a group or institution [17]. Local cloud is deployed in a local network that coordinates with its remote cloud server to promote data privacy.…”

Section: Related Concepts and Technologiesmentioning

confidence: 99%

Mobile Edge Computing: A Survey

Abbas

Zhang

Taherkordi

et al. 2018

IEEE Internet Things J.

2,026

743

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Mobile edge computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks into the mobile base stations. As a promising edge technology, it can be applied to mobile, wireless and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end users. MEC provides seamless integration of multiple application service providers and vendors towards mobile subscribers, enterprises and other vertical segments. It is an important component in the proposed 5G architecture that supports variety of innovative applications and services where ultra low latency is required. However, there are some challenges exists in the MEC eco system. To address these challenges, first off need to understand the network infrastructure of MEC, cloud and cellular network.Some questions and problems are addressed in this thesis that outlines the importance and challenges of MEC deployment. Impact of MEC integration with the traditional mobile and cloud network appears in this paper. A survey has been presented that contributes in general understanding of mobile edge computing (MEC). Readers will have an overview of MEC, such as definition, advantages, architectures and applications. Moreover, related research and future directions are pointed out in this thesis. Finally, security and privacy issues and their possible solutions are also discussed.iii This thesis is dedicated to my late Parents who were my first teachers. Without their support, guidance, and infinite wisdom, I would not have made it this far. My fervor towards professionalism is all colored by them.Also I would like to dedicate with my heart-felt and deepest gratitude to my siblings, I am blessed beyond belief. Their love and support means more to me than they will ever know.iv First and foremost, I thank Allah the Almighty for giving me health, strength and courage to complete my master thesis and eventually my Master in Network and System Administration at UiO.

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Section: Related Concepts and Technologiesmentioning

confidence: 99%

Mobile Edge Computing: A Survey

Abbas

Zhang

Taherkordi

et al. 2018

IEEE Internet Things J.

2,026

743

View full text Add to dashboard Cite

show abstract

“…Central processing unit (CPU) utilization is used as a valuable metric for software performance evaluation in conjunction with other metrics, such as memory and network utilization. In recent years, this metric has become a benchmark for assessing the performance of cloud computing and distributed systems [51][52][53][54][55]. Measuring the CPU utilization metric is crucial for efficiently estimating the processing power required by XR applications hosted on the Holo-Cloud.…”

Section: Processor Utilizationmentioning

confidence: 99%

A Multiuser, Multisite, and Platform-Independent On-the-Cloud Framework for Interactive Immersion in Holographic XR

Neeli,

Tran,

Velazco-Garcia

et al. 2024

Applied Sciences

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Background: The ever-growing extended reality (XR) technologies offer unique tools for the interactive visualization of images with a direct impact on many fields, from bioinformatics to medicine, as well as education and training. However, the accelerated integration of artificial intelligence (AI) into XR applications poses substantial computational processing demands. Additionally, the intricate technical challenges associated with multilocation and multiuser interactions limit the usability and expansion of XR applications. Methods: A cloud deployable framework (Holo-Cloud) as a virtual server on a public cloud platform was designed and tested. The Holo-Cloud hosts FI3D, an augmented reality (AR) platform that renders and visualizes medical 3D imaging data, e.g., MRI images, on AR head-mounted displays and handheld devices. Holo-Cloud aims to overcome challenges by providing on-demand computational resources for location-independent, synergetic, and interactive human-to-image data immersion. Results: We demonstrated that Holo-Cloud is easy to implement, platform-independent, reliable, and secure. Owing to its scalability, Holo-Cloud can immediately adapt to computational needs, delivering adequate processing power for the hosted AR platforms. Conclusion: Holo-Cloud shows the potential to become a standard platform to facilitate the application of interactive XR in medical diagnosis, bioinformatics, and training by providing a robust platform for XR applications.

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“…On the other hand, some articles investigated benchmarking systems at design-time, i.e., performance metrics that can be calculated before the sourcecode is written. Finally, the type 'analytical and measurement' Metric type Articles Performance (de Souza Pinto et al 2018) (van Eyk et al 2018) (Shukla et al 2017) (Aragon et al 2019) (Bermbach et al 2017) (Bondi 2016) (Martinez-Millana et al 2015) (Tekli et al 2011) (Vasar et al 2012) (Franks et al 2011) (Gesvindr & Buhnova 2019) (Ibrahim et al 2018) (Pandey et al 2017) (Ferreira et al 2016) (Ueda et al 2016) (Hadjilambrou et al 2015) (Amaral et al 2015) (Brummett et al 2015 Table 1 Selected articles in the systematic literature review.…”

Section: Benchmark In Software Engineeringmentioning

confidence: 99%

Migration from Monolith to Microservices: Benchmarking a Case Study.

Bjørndal¹,

Mazzara²,

Bucchiarone³

et al. 2021

JOT

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The migration from monolithic to microservice-based systems have become increasingly popular in the last decade.However, the advantages of this type of migration have not been extensively investigated in the literature, to the best of the authors' knowledge. This paper aims to present a methodology and performance indicators to support better assessment on whether the migration from a monolithic to microservice-based architecture is beneficial. A systematic review was conducted to identify the most relevant performance metrics in the literature, validated in a survey with professionals from the industry. Next, this set of metrics, including latency, throughput, scalability, CPU, memory usage, and network utilization -were used in two experiments to evaluate monolithic and microservice versions of the same system. The results reported here contribute to the body of knowledge on benchmarking different software architectures. In addition, this study illustrates how the identified metrics can more precisely assess both monolithic and microservice systems.

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Performance Metrics of Local Cloud Computing Architectures

Cited by 8 publications

References 1 publication

Mobile Edge Computing: A Survey

Mobile Edge Computing: A Survey

A Multiuser, Multisite, and Platform-Independent On-the-Cloud Framework for Interactive Immersion in Holographic XR

Migration from Monolith to Microservices: Benchmarking a Case Study.

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