Virtualization has become commonplace in modern data centers, often referred
as "computing clouds". The capability of virtual machine live migration brings
benefits such as improved performance, manageability and fault tolerance, while
allowing workload movement with a short service downtime. However, service
levels of applications are likely to be negatively affected during a live
migration. For this reason, a better understanding of its effects on system
performance is desirable.
Cloud computing is rapidly emerging as a new paradigm for delivering IT
services as utlity-oriented services on subscription-basis. The rapid
development of applications and their deployment in Cloud computing
environments in efficient manner is a complex task.
Cloud computing providers have setup several data centers at different
geographical locations over the Internet in order to optimally serve needs of
their customers around the world. However, existing systems do not support
mechanisms and policies for dynamically coordinating load distribution among
different Cloud-based data centers in order to determine optimal location for
hosting application services to achieve reasonable QoS levels.
The use of High Performance Computing (HPC) in commercial and consumer IT
applications is becoming popular. They need the ability to gain rapid and
scalable access to high-end computing capabilities. Cloud computing promises to
deliver such a computing infrastructure using data centers so that HPC users
can access applications and data from a Cloud anywhere in the world on demand
and pay based on what they use. However, the growing demand drastically
increases the energy consumption of data centers, which has become a critical
issue.