Profile aggregation and policy evaluation for adaptive internet services

Mobile and ubiquitous computing emphasize the need for highly adaptive delivery of Internet services. While several systems and even products exist that guarantee shallow or deep adaptation, they are usually based on profile information and customer relationship management modules stored and operating at the service provider. On the contrary, in this paper we assume that profile information, including user personal data and preferences, device capabilities, network bandwidth, location and other contextual information, as well as policy rules that can dynamically change this data, are provided by different sources. We describe a formal framework for aggregating this information and for solving conflicts between policy rules. We provide both a theoretical study of the properties of our techniques and a practical evaluation study obtained through a prototype implementation.