Reducing Resource Over-Provisioning Using Workload Shaping for Energy Efficient Cloud Computing

Kim, Woongsup; Mvulla, Jaha

doi:10.12785/amis/070552

Cited by 4 publications

(1 citation statement)

References 19 publications

(21 reference statements)

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“…This situation occurs when the developer forgets to terminate the service, which is being charged even if it is not being used, or with repeatedly fails when executing automated scripts, or even when the user instantiates too much resource for little interactive activity (e.g., visualizing data, testing environment, and running short-running commands). Some studies use the overprovision behavior to optimize the resources' utilization in a cloud provider point of view, like the practice of overbooking [79] or for energy consumption optimization [46]. In the user perspective, studies try to create elastic applications to get the most out of cloud elasticity [44], but this requires code refactoring.…”

Section: Chapter 1 Introductionmentioning

confidence: 99%

Monitoring and optimizing the cost of HPC applications on the cloud

Felipe da Cunha Tavares

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First of all, I would like to thank my mother, Silvia Cunha, who has always supported me in all aspects of my life, whether through counseling or aiding me throughout my graduation. Thank you, Mom.Secondly, my advisor, Edson Borin, who has been present in every moment of these two years: in changing the research subject, redefining goals and all many meandering paths, ups and downs that, one at a time, aided in building this work. I always felt that you have been more than a professor, a friend.We met Marcio Assis, my co-advisor, and, a year later, he joined us to aid in the development this work, and has always invaluable to keep us on track.Both contributed a lot in this work, but my growing research interest began with other professors to whom I must also thank: Edna A. Hoshino and Nahri B. Moreano. Two great professors who taught me a lot and encouraged me to be a master.Of course I could not forget my great friend, Lucas Reis, who accompanied me in this journey of leaving our families and friends in Campo Grande and moving to Campinas. He not only accompanied me, but also stood by my side during the hurdles and frustrations of research.Matheus Nuyens also has been a great friend, helping me with this text's revision and proofing, although from another field, endured me talking about computing and math stuffs.However, this time is not only made by work, and I must also thank my brother Marcelo and my old and new friends for the good times: Eva, Fer, Samuel, Luz, Felipe, Tuco, Victória, and many others.Finally, I thank UNICAMP, IC, LMCAD, CEPETRO and HPG team for helping me navigate bureaucracies and providing infrastructure. I also thank Petrobras for their financial support.

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Section: Chapter 1 Introductionmentioning

confidence: 99%

Monitoring and optimizing the cost of HPC applications on the cloud

Felipe da Cunha Tavares

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Analyzing the Merits of Cloud CRM by MEC and ISM

Lin

Chuang

Wang³

2014

Lecture Notes in Electrical Engineering

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Cloud provider capacity augmentation through automated resource bartering

Goher

Bloodsworth

Rasool

et al. 2018

Future Generation Computer Systems

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Growing interest in Cloud Computing places a heavy workload on cloud providers which is becoming increasingly difficult for them to manage with their primary datacenter infrastructures. Resource limitations can make providers vulnerable to significant reputational damage and it often forces customers to select services from the larger, more established companies, sometimes at a higher price. Funding limitations, however, commonly prevent emerging and even established providers from making continual investment in hardware speculatively assuming a certain level of growth in demand. As an alternative, they may strive to use the current inter-cloud resource sharing platforms which mainly rely on monetary payments and thus putting pressure on already stretched cash flows. To address such issues, we have designed and implemented a new multi-agent based Cloud Resource Bartering System (CRBS) that fosters the management and bartering of pooled resources without requiring costly financial transactions between providers. Agents in CRBS not only strengthen the trading relationship among providers but also enable them to handle surges in demand with their primary setup. Unlike existing systems, CRBS assigns resources by considering resource urgency which comparatively improves customers' satisfaction and the resource utilization rate by more than 50%.The evaluation results provide evidence that our system assists providers to timely acquire the additional resources and to maintain sustainable service delivery. We conclude that the existence of such a system is economically beneficial for cloud providers and enables them to adapt to fluctuating workloads.

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Reducing Resource Over-Provisioning Using Workload Shaping for Energy Efficient Cloud Computing

Cited by 4 publications

References 19 publications

Monitoring and optimizing the cost of HPC applications on the cloud

Monitoring and optimizing the cost of HPC applications on the cloud

Analyzing the Merits of Cloud CRM by MEC and ISM

Cloud provider capacity augmentation through automated resource bartering

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