Research on Request Handling Mechanism of Web Server Clusters

2014 ◽  
Vol 1022 ◽  
pp. 261-264
Author(s):  
Li Han ◽  
Xin Cao ◽  
Ya Na Zhang

This paper analyzes the factors that affect the performance of Web architecture cluster system characteristics studied two typical Web server cluster architecture, proposed a new distributed Web server cluster architecture, and in-depth analysis of its structural features, this architecture is verified in terms of scalability and reliability has advantages.

Author(s):  
Kadiyala Ramana ◽  
M. Ponnavaikko

With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster.


2010 ◽  
Vol 7 (1) ◽  
pp. 153-162 ◽  
Author(s):  
Lin Zhang ◽  
Li Xiao-Ping ◽  
Su Yuan

According to the different requests of Web and the heterogeneity of Web server, the paper presents a content-based loadbalancing algorithm. The mechanism of this algorithm is that a corresponding request is allocated to the server with the lowest load according to the degree of effects on the server and a combination of load state of server. Besides, apply a method of random distributing base-probability to assign each request to an appropriate server in terms of their weight. All the parameters that will be used in the algorithm can be acquired by simulated test. Experimental results suggest that this algorithm can balance the load of web server clusters effectively, make full use of the existing source of software and hardware, highly improve the server's performance, and even make the best use of the web server.


2011 ◽  
Vol 282-283 ◽  
pp. 765-769
Author(s):  
Li Feng Wei ◽  
Jian Wei Ji ◽  
Li Qiang Zhao

At present, the extendible Web server clusters are the important framers for the high performance network servers. The architecture based on load balancer is often used on web server clusters. The load balancer is the main bottleneck in improving performance of cluster. For it is hard to complete the task of assigning the requests from the client while collecting the real load information of the web servers efficiently. In this paper, we propose a model of two levels load balancer for web cluster to resolve the contradiction. When web requests are arrive, the first-level balancer continuously assigned them by to the second-level which consist of some load balancers connect to real web servers and receive real-time load information of them. Round robin algorithm is used at the first-level load balancer to schedule the client’s requests in order to shorten the response time. The proposed algorithm in our model is run at the second-level load balancers to schedule the requests to real web servers according to the real load information. At last, a simple test is carried out to make sure the performance of the model. The result of the test shows that the model has made better load balancing.


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