Towards connectivity management adaptability: Context awareness in policy representation and end-to-end evaluation algorithm

An infrastructure based on multiple heterogeneous access networks is one of the leading enablers for the emerging pervasive and ubiquitous computing paradigm, in which the optimal management of diverse networking resources is a challenging problem. This paper presents a context-aware policy mechanism and related end-to-end evaluation algorithm for adaptive connectivity management of multi-access wireless networks. A policy is used to express the criteria for adaptive selection of the best local and remote network interfaces. The best connection can then be used for the establishment of a channel as well as the maintenance of on-going data transmission. Rich context information is considered in the policy representation with respect to user profile and preference, application characteristics, device capability, and network QoS condition. The decision of the best access networks to be used is made on the basis of an end-to-end evaluation process. The decision can be made in both Master-Slave and Peer-to-Peer modes. The paper focuses on the methods for policy representation and connection evaluation algorithm. A case study is presented to show the usability of the proposed policy mechanism and decision-making algorithm in the adaptive management of heterogeneous networking resources.