A fault tolerable load balancing technique in cloud computing
As the IT industry is growing day by day, the need of computing and data storage is increasing rapidly. The process of this increasing mass of data requires more computer equipment to meet the various needs of the organizations. To better capitalize their investment, the over-equipped organizations open their infrastructures to others by exploiting the Internet and other important technologies such as virtualization by creating a new computing model: the cloud computing. Cloud computing is one of the significant milestones in recent times in the history of computers. However, there are number of technical challenges that need to be tackled which include reliability, resource provisioning, fault tolerance, load balancing and efficient mechanism to increase the service level agreement (SLA) and better use of the resources. The main purpose of this dissertation report is to provide a preface of the topic and to work on the various issues involved in the field of load balancing and fault tolerance i.e. load computation and the distribution of load. Load balancing and fault tolerance in cloud computing have a great impact on the performance of the system. Good load balancing makes cloud computing more efficient by provisioning of resources to cloud users on demand basis in pay-as-you-say manner. Load balancers are used for assigning load to different virtual machines in such a way that none of the nodes gets loaded heavily or lightly. When many clients request the server simultaneously, server is overloaded which causes fault. There are many load balancing algorithms and fault tolerance techniques in order to settle down these issues, but these techniques further had some drawbacks. Das and Khilar (2013) discussed a load balancing technique for virtualization and fault tolerance in cloud computing (LBVFT) to assign the task to the virtual nodes depending upon the success rates (SR) and the previous load history. This v technique tolerates not only the faults but also reduce the chance of future faults by not assigning tasks to virtual nodes of physical servers whose success rates are very low and loads are very high. But there is still a need to provide an efficient load balancing, load migration, load calculation and fault handling technique to make the VFT model more effective.