Details

Autor(en) / Beteiligte

• Sankaran, Lakshmi
• Subramanian, Saleema Janardhanan
• Sikora, Axel
• Geetha, S
• Thampi, Sabu M
• Boppana, Rajendra
• Fernando, Xavier
• Lloret Mauri, Jaime
• Geetha, S.
• Thampi, Sabu M.

Titel

CloudSim Exploration: A Knowledge Framework for Cloud Computing Researchers

Ist Teil von

• Applied Soft Computing and Communication Networks, 2021, Vol.187, p.107-122

Ort / Verlag

Singapore: Springer Singapore Pte. Limited

Erscheinungsjahr

2021

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• This paper aims to help find solutions for questions an early researcher may have to set up experiments in their development environment. Simultaneously, while identifying the steps required for experimenting, the authors narrowed on an experimenting toolkit for Cloud Computing as an area of their study. Because of such simulators, the cloud computing environment itself is available easily at the comfort of one’s desktop resources instead of visiting an actual physical data center to collect trace and log files as data sets for real workloads. This paper acts as an experience sharing to naive researchers who are interested in how to go about to start cloud computing setups. A new framework called Cloud Computing Simulation Environment (CCSE) is presented with inspiration from Procure Apply Consider and Transform (PACT) model to ease the learning process. The literature survey in this paper shares the path taken by researchers for understanding the architecture, technology, and tools required to set up a resilient test environment. This path also depicts the introduced framework CCSE. The parameters found out of the experiments were Virtual Machines (VMs), Cloudlets, Host, and Cores. The appropriate combination of the values of the parameters would be horizontal scaling of VMs. Increasing VMs does not influence the average execution time after a specific limit on the number of VMs allocated. Nevertheless, in vertical scaling, appropriate combinations of the cores and hosts yield better execution times. Thereby maintaining the optimal number of hosts is an ultimate saving of resources in case of VM allocations.