Evaluation and Optimization on Virtualization Performance Cost under Semantic Gap

Virtualization is a key enabling technology in modern data centers. While it provides numerous benefits, it also creates new problems. Virtualization requires the hypervisor to treat the virtual machine as a black box, limiting the ability of information exchange between the hypervisor and the virtual machine, bringing a problem known as the semantic gap. Currently, much research on the semantic gap mainly focuses on bridging the semantic gap. The evaluation of the semantic gap, on the other hand, is a neglected but crucial problem, and relevant research is currently lacking. Therefore, this paper proposes a corresponding virtualization performance cost model to better evaluate the semantic gap. Based on this cost model, we summarize solutions that can be used to alleviate the semantic gap. Furthermore, we propose a novel evaluation method for the CPU double scheduling semantic gap. Finally, we propose an effective virtio-balloon based dynamic memory tuning strategy to alleviate the memory semantic gap. The experiments show that for 400.perlbench, our strategy saves 551MB of memory on average during running and reclaims 990MB of memory after running, with a performance cost of only 1.1%. For 429.mcf, our strategy saves 815MB of memory on average during running and reclaims 2130MB of memory after running, although with the performance cost of 27.6%, it prevents performance cliff-like drop caused by memory shortage.