Resource scaling improves the capability of a datacenter or group of datacenters collaborated together to provide resources at low cost in order to meet the demands and objectives of application services, but, it is substantial to determine the requirements of the user, especially in the large projects like XIFI. It is important to estimate the number of users, their arrival rate and types of applications that are often requested for resource allocation, to expand the resource dimensions to proportionate degree. In this study we frame a structure that provides deep insights to comprehend XIFI infrastructure. Furthermore, we model behavior of users that approach the node for resource allocation to run their applications. We aim to provide an understanding on how the user behavior influences the resource scaling in XIFI node. The main objective of this thesis is to investigate different types of applications chosen by users who request for resource allocations and impact of their choice on the resource availability. In the systematic review, a number of deliverables of XIFI to understand the specifications of XIFI architecture are reviewed and analyzed. A model that meets basic requirements, which can be denoted as a XIFI node is developed and the developed design is implemented in a simulator. We simulated the designed structure for 30 iterations and analyzed 10,000 user requests for two cases where total RAM of the node is increased in the second case when compared to the first case. We analyze the reason for the failure of the number of requests and different types of virtual machines for different types of applications, due to unavailable resources. From the obtained results, we conclude that, by increasing total RAM in a XIFI node the failure of average number of requests can be reduced. Also the failure percentage of virtual machines that are to be instantiated, as requested by users decreases when the RAM is scaled to twice the present value. We also conclude that the user behavior that imposes load on the system, decides the degree of scalability of resources in the XIFI node.

Having a good understanding of the load requirements in the datacenter improves the capability to effectively provision the resources available to the meet the demands and objectives of application services. Especially in a large project like XIFI this aspect becomes even more critical because of the limited availability of the resources and the complexity of the various entities present.In this study we frame a structure that provides deep insights to comprehend XIFI infrastructure. Further, we model the user requests that approach the node for resource allocation to run their applications. We aim to provide an understanding on different aspects involved in modelling. The objective of this present study is to investigate the effect of load on the XIFI node. To achieve this objective, we model the XIFI node by examining the various entities involved in it. Furthermore, we provide an overview about what constitutes as load in the XIFI node.We conduct a detailed specifications study after which we identify the imperative entities required for the modelling of both the XIFI node and the requests. We examine the model by simulating it in CloudSim for two different scenarios varying the specifications.We simulated the designed structure for 30 iterations and analyzed 10,000 user requests for two cases where total RAM of the node is increased in the second case when compared to the first case. We analyze the CPU usage, RAM usage, Bandwidth usage and Storage usage in both the cases and examine the effects of the user requests on each one of them.The results provided evidence that the load indices on the host are dependent on each other. Also, it showed that the request modelling had an impact on the load of the host. It can also be concluded that the resource provisioning can be effective if the user behavior is known.