Balance Optimization Scheduling Algorithm for Standard Digital Management Cloud Platform Infrastructure

Services in cloud computing systems are typically categorized into three types — software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS). Since the cloud service provider has to deal with various set of clients, a wise scheduling of these requests should not only take into account the efficient use of resources for the provider to maximize its profit, but also respect the satisfaction of the clients, more precisely, make the clients feel fair in the scheduling processing. In this paper, we propose a new fair scheduling algorithm that can efficiently implement in IaaS in a cloud environment. We propose two new objective loss models that analyze the provider profit loss and the client satisfaction loss for our algorithm. Our algorithm is "fair" as it takes into account the provider profit loss and the client satisfaction loss. We then introduce two versions of our algorithm, namely, random greedy and balanced greedy, that aim to minimize the developed loss models and satisfy maximum usage of provider resources to make maximum profit. Finally, Extensive experimental results show that our algorithm is efficient and feasible.