| An all-IP pervasive networking system provides a comprehensive IP solution where voice, data and streamed multimedia can be delivered to users at anytime and anywhere. Network selection is a key issue in this converged heterogeneous networking environment. A traditional way to select a target network is only based on the received signal strength (RSS); however, it is not comprehensive enough to meet the various demands of different multimedia applications and different users. Though some existing schemes have considered multiple criteria (e.g. QoS, security, connection cost, etc.) for access network selection, there are still several problems unsettled or not being solved perfectly. In this thesis, we propose a novel model to handle this network selection issue. Firstly, we take advantage of IEEE 802.21 to obtain the information of neighboring networks and then classify the information into two categories: (1) compensatory information; and (2) non-compensatory information; secondly, we use the non-compensatory information to sort out the capable networks as candidates. If a neighboring network satisfies all the requirements of non-compensatory criteria, the checking of the compensatory information will then be triggered; thirdly, taking the values of compensatory information as input, we propose a hybrid ANP and RTOPSIS model to rank the candidate networks. ANP elicit weights to compensatory criteria and eliminates the interdependence impact on them, and RTOPSIS resolves the rank reversal problem which happens in some multiple criteria decision making (MCDM) algorithms such as AHP, TOPSIS, and ELECTRE. The evaluation study verifies the usability and validity of our proposed network selection method. Furthermore, a comparison study with a TOPSIS based algorithm shows the advantage and superiority of the proposed RTOPSIS based model. |
