The popularity of ubiquitous Web access requires runtime adaptations of the Web contents. A significant trend in these content adaptation services is the growing amount of personalization required by users. Personalized services are and will be a key feature for the success of the ubiquitous Web, but they open two critical issues: performance and profile management. Issues related to the performance of adaptation services are typically addressed by highly distributed architectures with a large number of nodes located closer to user. On the other hand, the management of user profile must take into account the nature of these data that may contain sensitive information, such as geographic position, navigation history and personal preferences that should be kept private.

In this paper, we investigate the impact that a correct profile management has on distributed infrastructures that provide content adaptation services for ubiquitous Web access. In particular, we propose and compare two scalable solutions of adaptation services deployed on the nodes of a two-level topology. We study, through real prototypes, the performance and the constraints that characterize the proposed architectures.