An online greedy allocation of VMs with non-increasing reservations in clouds

Dynamic VMs allocation plays an important role in resource allocation of cloud computing. In general, a cloud provider needs both to maximize the efficiency of resource and to improve the satisfaction of in-house users simultaneously. However, industrial experience has often shown only maximizing the efficiency of resources and providing poor or little service guarantee for users. In this paper, we propose a novel model-free virtual machine allocation, which is characterized by an online greedy algorithm with reservation of virtual machines, and is named OGAWR. We couple the greedy allocation algorithm with non-increasing reserving algorithms to deal with flexible jobs and inflexible jobs. With the OGAWR, users are incentivized to be truthful not only about their valuations, but also about their arrival, departure and the characters of jobs (flexible or inflexible). We simulated the proposed OGAWR using data from RICC. The results show that OGAWR can lead to high social welfare and high percentage of served users, compared with another mechanism that adopts the same method of allocation and reservation for all jobs. The results also prove that the OGAWR is an appropriate market-based model for VMs allocation because it works better for allocation efficiency and served users.