Please use this identifier to cite or link to this item:
|Title:||Autonomic Fault Tolerance Using HAProxy in Cloud Enviorment|
|Abstract:||Cloud computing, with its great potentials in low cost and on-demand services, is a promising computing platform for both commercial and non-commercial computation clients. In this thesis various fault tolerance techniques have been discussed to improve performance and availability of server applications. Cloud computing is a relatively new way of referring to the use of shared computing resources, and it is an alternative to having local servers handle applications. The cloud computing end users usually have no idea where the servers are physically located. Cloud computing environments comprise of high level of communication and server failures in contrast to conventional data centers. Therefore new tools and techniques are required to build fast, reliable and autonomic fault tolerant system. When several instances of an application running on several virtual machines, a problem that arises is implementation of an autonomic fault tolerance technique to handle a server failure to reassure system reliability and availability. If any of the servers break down, system should automatically redirect user requests to the backup server. The solution provided in this thesis make use of a software tool known as HAProxy that offers high availability and can handle server failures in the framework of virtual machines. This thesis has proposed the cloud virtualized system architecture by using HAProxy. The prototype system is implemented in Linux by using three web server applications that may comprise of faults. The approach provides autonomic and transparent fault tolerance capability to cloud applications. The experimental results show that HAProxy can make server applications to recover from these faults in a few milliseconds by increasing system availability and reliability.|
|Appears in Collections:||Masters Theses@CSED|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.