A Fuzzy Grouping Genetic Algorithm for Solving a Real-World Virtual Machine Placement Problem in a Healthcare-Cloud

Due to the large-scale development of cloud computing, data center electricity energy costs have increased rapidly. Energy saving has become a major research direction virtual machine placement problems. At same time, multi-dimensional resources on should be used in balanced manner order avoid waste. In this context, paper addresses real-world problem arising Healthcare-Cloud (H-Cloud) hospitals chain Saudi Arabia, considering server power consumption and resource utilization. As part optimizing both objectives, user service quality taken into account. fact, (QoS) is also considered by measuring Service-Level Agreement (SLA) violation rate. This modeled as multi-objective with objective minimizing consumption, utilization, SLA To solve challenging problem, fuzzy grouping genetic algorithm (FGGA) proposed. Considering that multiple optimization objectives may different degrees influence fitness function proposed calculated logic-based function. The experimental results show effectiveness algorithm.