Performance assessment of cloud applications

• Název práce v češtině: Vyhodnocování výkonnosti cloudových aplikací
• Název v anglickém jazyce: Performance assessment of cloud applications
• Klíčová slova: edge-cloud; časové požadavky; sdílení zdrojů; optimalizace výkonnosti
• Klíčová slova anglicky: edge-cloud; real-time requirements; resource sharing; performance optimization
• Akademický rok vypsání: 2017/2018
• Typ práce: diplomová práce
• Jazyk práce: angličtina
• Ústav: Katedra distribuovaných a spolehlivých systémů (32-KDSS)
• Vedoucí / školitel: prof. RNDr. Tomáš Bureš, Ph.D.
• Řešitel: skrytý - zadáno a potvrzeno stud. odd.
• Datum přihlášení: 31.03.2018
• Datum zadání: 04.04.2018
• Datum potvrzení stud. oddělením: 09.04.2018
• Datum a čas obhajoby: 01.07.2020 09:00
• Datum odevzdání elektronické podoby: 29.05.2020
• Datum odevzdání tištěné podoby: 28.05.2020
• Datum proběhlé obhajoby: 01.07.2020
• Oponenti: RNDr. David Bednárek, Ph.D.

Zásady pro vypracování

Modern CPS and mobile applications like augmented reality or coordinated driving, etc. are envisioned to combine edge-cloud processing with real-time requirements. The real-time requirements however create a brand new challenge for cloud processing which has traditionally been best-effort. A key to guaranteeing real-time requirements is the understanding of how services sharing resources in the cloud interact on the performance level.
The objective of the thesis is to design a mechanism which helps to categorize cloud applications based on the type of their workload. This should result in specification of a model defining a set of applications which can be deployed on a single node, while guaranteeing a certain quality of the service. It should be also able to find the optimal node where the application could be deployed.

Seznam odborné literatury

[1] Choy, Sharon, Bernard Wong, Gwendal Simon, and Catherine Rosenberg. “A Hybrid Edge-Cloud Architecture for Reducing on-Demand Gaming Latency.” Multimedia Systems 20, no. 5 (October 1, 2014): 503–19. https://doi.org/10.1007/s00530-014-0367-z.
[2] Xu, Minxian, Wenhong Tian, and Rajkumar Buyya. “A Survey on Load Balancing Algorithms for VM Placement in Cloud Computing.” Concurrency and Computation: Practice and Experience 29, no. 12 (June 25, 2017): e4123. https://doi.org/10.1002/cpe.4123.
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[4] Orsini, Gabriel, Dirk Bade, and Winfried Lamersdorf. “Cloudaware: A Context-Adaptive Middleware for Mobile Edge and Cloud Computing Applications.” In Foundations and Applications of Self* Systems, IEEE International Workshops On, 216–221. IEEE, 2016.
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[6] Östberg, P. O., J. Byrne, P. Casari, P. Eardley, A. F. Anta, J. Forsman, J. Kennedy, et al. “Reliable Capacity Provisioning for Distributed Cloud/Edge/Fog Computing Applications.” In 2017 European Conference on Networks and Communications (EuCNC), 1–6, 2017. https://doi.org/10.1109/EuCNC.2017.7980667.
[7] Wang, S., M. Zafer, and K. K. Leung. “Online Placement of Multi-Component Applications in Edge Computing Environments.” IEEE Access 5 (2017): 2514–33. https://doi.org/10.1109/ACCESS.2017.2665971.
[8] Oueis, J., E. C. Strinati, and S. Barbarossa. “The Fog Balancing: Load Distribution for Small Cell Cloud Computing.” In 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), 1–6, 2015. https://doi.org/10.1109/VTCSpring.2015.7146129.
[9] Jia, Mike, Weifa Liang, and Zichuan Xu. “QoS-Aware Task Offloading in Distributed Cloudlets with Virtual Network Function Services.” In Proceedings of the 20th ACM International Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems, 109–116. MSWiM ’17. New York, NY, USA: ACM, 2017. https://doi.org/10.1145/3127540.3127561.