Balanced Scheduling Method of Network Information Resources for Cloud Storage

Introduction

With the rapid development of network communication technology, the requirements of various industries for the quality of network communication service system are becoming higher and higher. Laptops using wireless System or wireless WAN technologies, cell phones, smartwatches, and Personal Digital Companions (PDAs) with Wireless headphones or IRDA ports all fall under this category. There are several different forms of cloud computing available to people currently. The resource sharing environment with single mode has been unable to meet the needs of various industries (Rao et al., 2020). As an important part of network communication technology, resource balanced scheduling has become the research focus in various fields. Users can connect effectively with a community of individuals utilizing a system by using text messenger, teleconferences, media platforms, discussion forums, and other methods. Sharing files, documents, and knowledge is simple. Encryption keys can be used to safeguard data and folders on a computer. The symmetry of load levels is measured through a balancing algorithm, and loads are assigned correspondingly. However, there are many problems in the current shared resource balanced scheduling method, such as long scheduling time and high-cost consumption. In view of this situation, how to effectively and reasonably schedule has become an urgent problem to be solved in today’s society. At present, cloud storage resource scheduling method based on quantum particle swarm optimization algorithm (Maghsoudloo, & Khoshavi, 2020). This method analyzes the resource scheduling of cloud storage, builds a mathematical model of resource scheduling, gives the objective function, and uses quantum particle swarm optimization algorithm to solve it. The method through which organizations arrange and manage its personnel so that the activities they must perform are planned depending on accessibility and capacity is known as resource scheduling. Project managers may use this method to distribute and delegate tasks to team members instead of over (or below) assigning their calendars. The important features of cloud storage resource scheduling are rapid flexibility, accurate communication, self-service on request, resource pooling and accessibility. As a consequence of the fast fall in variety, the QPSO algorithm is prone to becoming caught in local optimization. Because QPSO simply includes a coordinate and no speed, it is easier to understand than a normal ant colony optimization technique. This method can effectively improve the utilization of resource scheduling, but the completion time in the scheduling process is too long. Resource scheduling method based on resource weight and maximum resource utilization. This method analyzes the resource, obtains the resource weight ratio, and schedules the resource according to the maximum resource utilization (Zhang et al., 2019). This method can effectively improve the resource utilization of the whole system, and quickly solve the load balancing problem, but the cost consumption is high in the process of scheduling. Aiming at the above problems, this paper proposes a network information resource balancing scheduling method for cloud storage. The experimental results show that the proposed scheduling method needs less time and cost.