Resource Reallocation of Virtual Machine in Cloud Computing with MCDM Algorithm
Byungjun Lee, Kyung Hwan Oh, Hee‐Jung Park, Ung Mo Kim, Hee Yong Youn · 2014
Resource allocation for virtual machines is a crucial issue in cloud computing. Many researchers have developed various solutions for effective resource allocation of data centers. The fuzzy decision making scheme has been recognized as an effective candidate for this problem. The solution, however, has a limitation that linguistic parameters are used as input in the selection of suitable VM and PM, causing subjectivity and vagueness. In this paper, a new approach for resource allocation of virtual machines is proposed which employs the TOPSIS, analytic hierarchy process (AHP), grey theory, and the concept of entropy. The simulation results show that the proposed scheme achieves better load balancing and availability of the system with less VM migration compared to the existing schemes.