Cloud computing provides a kind of dynamic and scalable service on demand. However, clouds consume huge amountsof electrical energy. Meanwhile, delivering the negotiated QoS defined as Service Level Agreement (SLA) to users is necessary. A virtual machine placement strategy based on the equilibrium between energy and SLA is proposed. Aiming at dynamical changes of application workloads, an adaptive placement strategy RLWR based on robust local weight regression is presented, which decides the overload time of hosts dynamically according to the historical resource occupation of application work...
