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Network and application-aware cloud service selection in peer-assisted environments

Askarnejad, S ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1109/TCC.2018.2865560
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2021
  4. Abstract:
  5. There are a vast number of cloud service providers, which offer virtual machines (VMs) with different configurations. From the companies perspective, an appropriate selection of VMs is an important issue, as the proper service selection leads to improved productivity, higher efficiency, and lower cost. An effective service selection cannot be done without a systematic approach due to the modularity of requests, the conflicts between requirements, and the impact of network parameters. In this paper, we introduce an innovative framework, called PCA, to solve service selection problem in the hybrid environment of peer-assisted, public, and private clouds. PCA detects the conflicts between the requests and enterprises policies, finds proper services based on the requirements, and reduces VMs rent and end-to-end network costs. PCA selects the services from multiple clouds to utilize resources and reduce the total cost. Our proposed framework utilizes set theory, B+ tree, and greedy algorithms to meet its goals. The simulation results show that PCA can reduce up to 30 percent of cloud-related costs and can achieve answers at least seven times faster in comparison to recent studies. © 2013 IEEE
  6. Keywords:
  7. Cloud computing ; Computation theory ; Cost engineering ; Cost reduction ; Genetic algorithms ; Heuristic algorithms ; Maintainability ; Principal component analysis ; Quality of service ; Conflict detection ; Cost optimization ; Greedy algorithms ; Network costs ; Peer-assisted ; Service selection ; Simulation ; Cost benefit analysis
  8. Source: IEEE Transactions on Cloud Computing ; Volume 9, Issue 1 , 2021 , Pages 258-271 ; 21687161 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/8437131