Virtual Machine Placement for Hybrid Cloud Using Constraint Programming

Cloud computing is the widely spread paradigm of utility-computing that offers an "on-demand" internet-based access to configurable resources available within data centers. On one hand, public Cloud providers are well suited for highly available access to IT resources (infrastructure, platform and software), for sporadic use, or for elastic demands. On the other hand, private clouds could sometimes be preferred for security or privacy reasons, or for cost reasons due to a high frequency usage of services. However, in many cases a choice between public or private clouds does not fulfill all requirements of companies, and hybrid cloud infrastructures should be preferred. A hybrid cloud solution could, for example, answer sudden workload increase in private clouds, security or fault tolerance requirements, or even latency issues thanks to data-locality. Solutions have already been proposed to address hybrid cloud infrastructures, however most of the time the placement of a distributed software on such infrastructure has to be indicated manually. For this reason, the automation of software deployment on hybrid clouds is still under research. In this paper we propose new specific placement constraints and objectives adapted to hybrid clouds infrastructures within our placement solution, namely OptiPlace, and we address this problem through constraint programming. Furthermore, we evaluate the expressivity and performance of the proposed solution on a real case study.