Policy mechanism and evaluation algorithm for connectivity management adaptability

An infrastructure based on multiple heterogeneous access networks is one of the leading enablers for the emerging paradigm of pervasive computing. The optimal management of diverse networking resources is a challenging problem. This paper aims to present a context‐aware policy mechanism with related end‐to‐end (E2E) evaluation algorithm for adaptive connectivity management in 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 for 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 quality of service conditions. The decision of the best access networks to be used is made on the basis of an E2E evaluation process. The decision can be made in both master–slave and peer‐to‐peer modes, according to the decision matrixes generated in both ends. The paper focuses on the 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 adaptiv management of heterogeneous networking resources.

The proposed policy mechanism is for the adaptive decision of connection selection in channel establishment and vertical handoff between heterogeneous access networks. A policy is represented as a four‐tuple, including the direction and the class of traffic, requirement expression, and concrete evaluation items. Three steps are involved in the evaluation process, namely policy traverse, decision matrix calculation, and decision‐making.

The policy mechanism can be easily extended to include adaptive selection of multiple user devices in addition to multiple connections.