  This work introduces optimization strategies to continuous variable
measurement based quantum computation (MBQC) at different levels. We provide a
recipe for mitigating the effects of finite squeezing, which affect the
production of cluster states and the result of a traditional MBQC. These
strategies are readily implementable by several experimental groups.
Furthermore, a more general scheme for MBQC is introduced that does not
necessarily rely on the use of ancillary cluster states to achieve its aim, but
rather on the detection of a resource state in a suitable mode basis followed
by digital post-processing. A recipe is provided to optimize the adjustable
parameters that are employed within this framework.
