An adaptive real time mechanism for IaaS cloud provider selection based on QoE aspects

Traditionally, companies host their own services, platforms and infrastructures on their own servers. This policy results in high costs in terms of material and human resources. It may also be inadequate to the real needs of the company. In this context, one solution is to use cloud computing to outsource their services. The latter is defined by making available to the customer high-performance servers and high bandwidth. The cloud is also defined by renting software and hardware infrastructure to customers according to their needs. Cloud computing is made possible by the improvement of computer networks infrastructures. Indeed, broadband connections have reduced latency and thus enabled the use of remote resources. The success of cloud computing has led to a significant increase in the providers number offering many and varied cloud services. While the access to these services is made possible through a simple subscription, no technique is currently available to select the cloud provider that best fits their needs. Selecting a provider is an optimization problem that has been studied in several areas. Given the large number of parameters and actors in the cloud, this problem is known as NP-complete one. In this work, we propose a new developed platform which plays the role of a broker between clients and cloud providers. Based on a set of benchmark tasks on provider services, it performs an adaptive cloud provider selection in accordance with the client needs. The experimental results show that the proposed approach gives benefits to subscribers in terms of QoE.