Anna Zatwarnicka

Global Distribution of HTTP Requests Using the Fuzzy-Neural Decision-Making Mechanism

This paper presents the HTTP request global distribution using the fuzzy-neural decision making mechanism. Two efficient algorithms GARDiB and GARDiB2 are proposed to support HTTP request routing to the Websites. The algorithms use the fuzzy-neural decision-making method to assign each incoming request to the Website with the least expected response time. The response time includes the transmission time over the network; as well as the time elapsed on the responding Website server. Simulation experiments showed that GARDiB performed slightly better than GARDiB2 and both proposed algorithms outperformed other competitive distribution algorithms in all simulated workload scenarios.

Global Adaptive Request Distribution with Broker

This paper presents the application of fuzzy logic and neural networks to HTTP request dispatching performed within a geographically distributed Web system. Web sites serve as a global content delivery system where each Web server can respond to the client request. We propose broker-based system architecture with a global request dispatching algorithm called GARDiB. The algorithm uses the fuzzy-neural decision-making mechanism to assign each incoming request to the server with the least expected response time. The response time include the transmission time over the network, both for the request and for the response, as well as the time elapsed on the server responding to the request. We demonstrate through the simulations that our algorithm is more effective than popular global dispatching policies Round-Robin and Weighted Round-Robin.

Estimation of Web Page Download Time

This paper presents a study of a model of Web page download time. According to the proposed model the download time can be modeled on a base of knowledge of round trip time, bandwidth and a concurrency factor specifying the number of HTTP object downloaded concurrently. Through conducted experiments we designate a mean value of the concurrency factor for modern Web browsers: Mozilla Firefox, Internet Explorer and Google Chrome. Analysis of the results of the experiments confirms the serviceability and quality of the proposed model.

The Cluster-Based Time-Aware Web System

The problem of providing fixed Quality of Web Services (QoWS) is now crucial for further development and application in new areas of internet services. In this paper, we present the MLF (Most Loaded First) adaptive and intelligent cluster-based Web system which provides quality of service on a fixed level. The proposed system keeps the page response time within established boundaries in such a way that with a heavy workload, the page response times, for both small and complex pages, would not exceed the imposed time limit. We show, in experiments conducted with the use of a cluster of real Web servers, that the system is efficient and more effective than other examined systems.

Adaptive HTTP request distribution in time-varying environment of globally distributed cluster-based web system

A great development of Web technologies requires the application of complex systems and algorithms for maintaining high quality of Web services. The paper presents application of a broker-based architecture to the globally distributed Web system and the deployment of adaptive request distribution algorithm using neuro-fuzzy models in the decision-making process. The presented results of the simulation experiments show how the Web system operates under control of the proposed algorithm and the way of adaptation of the system to time-varying environment.

Fuzzy-Neural Controller in Service Requests Distribution Broker for SOA-Based Systems

The evolution of software architectures led to the rising importance of the Service Oriented Architecture (SOA) concept. This architecture paradigm support building flexible distributed service systems. In the paper the architecture of service request distribution broker designed for use in SOA-based systems is proposed. The broker is built with idea of fuzzy control. The functional and non-functional request requirements in conjunction with monitoring of execution and communication links are used to distribute requests. Decisions are made with use of fuzzy-neural network.

A Cluster-Based Quality Aware Web System

Providing high quality of Web services is now very important for most of the services. In this article, we present the MLF (Most Loaded First) system, adaptive and intelligent cluster-based Web system. The MLF system provides Quality of Web Service (QoWS) on a fixed level, guaranteeing the page response time within established boundaries, even if Web servers are heavy loaded. We present experiments conducted on real cluster of Web servers and show that MLF system is more reliable than other examined systems.

Modeling Operation of Web Service

This paper presents studies of modeling operation of Web service containing Web and database servers. The first part of the paper describes the method to obtain parameters of real servers. Additionally, detailed description of experiments and the results are presented. In the second part of the paper the Web and database servers models are introduced. In both of the presented models it is taken into account that the server processors are multi-core. Presented models can be used to evaluate proposed Web systems via simulation experiments.

Two-Layer Cloud-Based Web System

Providing high quality of Web services is now very important for most of the services. The application of cloud computing in Web systems enables lower costs and increases efficiency and reliability. In the paper we present a design of two-layer decision-making method in a cloud-based Web system TLCWS (Two-Layer Cloud-based Web System). It uses the neuro-fuzzy approach to enable the distribution of HTTP requests. The proposed method is design to minimize the response time of each request. The simulation experiments show that the proposed approach is more than just adequate and that it is possible to shorten the response time required for requests significantly.