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Algorithmic Approach to Virtual Machine Migration in Cloud Computing with Updated SESA Algorithm.
Kaur, Amandeep; Kumar, Saurabh; Gupta, Deepali; Hamid, Yasir; Hamdi, Monia; Ksibi, Amel; Elmannai, Hela; Saini, Shilpa.
Afiliação
  • Kaur A; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India.
  • Kumar S; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India.
  • Gupta D; Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab 140401, India.
  • Hamid Y; Information Security and Engineering Technology, Abu Dhabi Polytechnic, Abu Dhabi 111499, United Arab Emirates.
  • Hamdi M; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
  • Ksibi A; Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
  • Elmannai H; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.
  • Saini S; Department of CSE, Chandigarh University, Mohali 140413, India.
Sensors (Basel) ; 23(13)2023 Jul 03.
Article em En | MEDLINE | ID: mdl-37447966
ABSTRACT
Cloud computing plays an important role in every IT sector. Many tech giants such as Google, Microsoft, and Facebook as deploying their data centres around the world to provide computation and storage services. The customers either submit their job directly or they take the help of the brokers for the submission of the jobs to the cloud centres. The preliminary aim is to reduce the overall power consumption which was ignored in the early days of cloud development. This was due to the performance expectations from cloud servers as they were supposed to provide all the services through their services layers IaaS, PaaS, and SaaS. As time passed and researchers came up with new terminologies and algorithmic architecture for the reduction of power consumption and sustainability, other algorithmic anarchies were also introduced, such as statistical oriented learning and bioinspired algorithms. In this paper, an indepth focus has been done on multiple approaches for migration among virtual machines and find out various issues among existing approaches. The proposed work utilizes elastic scheduling inspired by the smart elastic scheduling algorithm (SESA) to develop a more energy-efficient VM allocation and migration algorithm. The proposed work uses cosine similarity and bandwidth utilization as additional utilities to improve the current performance in terms of QoS. The proposed work is evaluated for overall power consumption and service level agreement violation (SLA-V) and is compared with related state of art techniques. A proposed algorithm is also presented in order to solve problems found during the survey.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Computação em Nuvem Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Índia País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Computação em Nuvem Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Índia País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND