Multi-Objective Optimization Task Scheduling Method Based on Dynamic Programming for Multi-Cloud Environment

Cloud computing is one of the most successfull technologies for providing services on request via the Internet, bringing extreme convenience to customers and businesses with its advantages of hyperscale, modernisation, reliability, universality, high scaleability and payment on request. However, with the growth of services for managing content distribution and interactive computing, such as social networking and scientific processes online, the capacity of cloud data centers is limited and cannot meet the business needs during peak hours. To handle this huge data volume, multiple cloud systems that has been introduced to pool multiple clouds together to provide a single set of services in a collaborative manner. Aiming at the resource allocation problem in cloudy environments, this paper proposes a method of multi-objective task optimization scheduling based on dynamic programming, constructs a scheduling model of time and cost, and designs an efficient multiobjective optimisation approach is used to address the module. The method first describes the resource allocation process in a multi-cloud environment, then establishes a progress model for multi-user tasks in a cloud environment, then formalises the multi-user task optimisation problem and designs a solution algorithm based on a dynamic programming approach, and finally conducts simulation experiments to evaluate the effectiveness of the method. The experimental results show that the method can achieve time and cost optimisation in the scheduling of multi-user tasks.