# Providing Predictable Quality of Service in a Cloud-Based Web System
###### Abstract  
Cloud-computing web systems and services revolutionized the web. Nowadays, they are the most important part of the Internet. Cloud-computing systems provide the opportunity for businesses to undergo digital transformation in order to improve efficiency and reduce costs. The sudden shutdown of schools and offices during the pandemic of Covid 19 significantly increased the demand for cloud solutions. Load balancing and sharing mechanisms are implemented in order to reduce the costs and increase the quality of web service. The usage of those methods with adaptive intelligent algorithms can deliver the highest and a predictable quality of service. In this article, a new HTTP request-distribution method in a two-layer architecture of a cluster-based web system is presented. This method allows for the provision of efficient processing and predictable quality by servicing requests in adopted time constraints. The proposed decision algorithms utilize fuzzy-neural models allowing service times to be estimated. This article provides a description of this new solution. It also contains the results of experiments in which the proposed method is compared with other intelligent approaches such as Fuzzy-Neural Request Distribution, and distribution methods often used in production systems. web cloud system; cloud computing; web systems simulation; fuzzy-neural network; fuzzy-neural modeling intelligent system; HTTP request distribution 2021289622 March 202124 March  
(QoS), or especially the quality of web service (QoWS), load balancing and load sharing mechanisms are implemented. The proper and effective distribution of the load is still an open problem in cloud computing. Little comprehensive research in the field of cloud computing has been done. New architecture structures and algorithms meeting clients' demands need to be developed. The nodes in the cloud-based web system are distributed. There are two types of load sharing techniques related to the centralization of decision units [7]--centralized and distributed. In centralized systems, the distribution decisions are made by a single node. This node stores knowledge of the whole cloud system and uses load sharing algorithms. Distributed and hierarchical load sharing involves different layers of the cloud. There is no single node fully responsible for making distribution decisions. The complexity of cloud infrastructures has created the need for innovative monitoring approaches [8]. The complex nature, at many different levels, of this kind of system is the underlying cause of many problems. This has an effect on all aspects of cloud operation and needs to be handled properly in order to provide high performance, dependability, and quality of service etc. [9]. Most cloud systems are physically divided into regions (server rooms) placed in different geographical locations. Regions are built of availability zones--parts of the regions with independent network infrastructure [10]. Web switches distribute the load in the cloud systems. Taking into account the architecture of a typical web cloud using only one region, a centralized cloud contains one web switch distributing the load all over the region. The switch is placed in one of the zones. It is called one-layer architecture (Figure 1a). A distributed hierarchical web cloud contains many web switches making decisions on different layers. Figure 1b presents a two-layer architecture with one web switch in the region and separate web switches in zones. Figure 1: Cloud-base web systems: (**a**) centralized one-layer architecture and (**b**) distributed two-layer architecture. The quality of the web services can be assessed by the end-users in many different ways. An interesting content of the website ensures an increase in the number of users. However, it is crucial to deliver the content immediately after receiving a request. The users will consider the service to be of low quality when the time required to get the page is too long.