AWSQ: an approximated web server queuing algorithm for heterogeneous web server cluster

Abstract

With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are clusterbased 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.

Path based load balancing for data center networks using SDN

“…Distributed System is important to distributing the work load on the servers [17]. Load Balancer places a vital role in fulfilling the request of the clients through servers and for this work load balancer routes requests to those servers, which has the capability of doing its job in an effective way that is maximization of speed, maximum utilization of capacity and can fulfill the client's requests [18]. Our solution follows the layer architecture of SDN, in which there are two planes, control plane and data Figure 1 is showing the architecture of SDN.…”

Traffic-aware adaptive server load balancing for software defined networks

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Performance Analysis of CloudLinux-based Web Server at the Embassy of the Kingdom of Morocco in Jakarta

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