A battery level aware MADM combination for the vertical handover decision making

Abstract

The internet services became so various, that the number of its users is exponentially increased these last two decades, and wireless technologies are developed as well. Nowadays, people are willing to use mobile devices to connect wirelessly anywhere, anytime and to any available technology under the ABC (Always Best Connected) concept. To access the bet service wirelessly, mobile nodes “MNs” try to connect to the best wireless network technology available anytime, even when quitting the base station or access point area to one another, or changing the wireless access type, which is called vertical handover (VH). This supposes that the MN must connect to the wireless network available, that offers the best quality of service (QoS), without session breaks. To reach this objective, VH decision-making need to be quick and efficient to determine which wireless technology is the best, among those available anytime. Thus, we are seeking to optimize the network selection phase in the process of VH. Several network selection algorithms have been used, based on different theories, such as basic algorithms (based on simple metrics), Neural Networks models, Gaming theory algorithms and Multi Attributes Decision Making (MADM) methods. This paper presents a comparison of different MADM methods, taking into account an important criterion which is the battery level, so as to determine which method makes the best VH decisions, while extending the MN's battery life.