Performance evaluation of MADM-based methods for network selection in a multimedia wireless environment

As mobile devices have become more affordable, easy to use and powerful, the number of mobile users and their bandwidth demands have experienced a significant growth. Considering the rising popularity of power hungry applications (e.g. multimedia), battery power capacity is an important concern as upgrades are not keeping up with the advances in other technologies (e.g., Central Processing Unit (CPU) and memory). Mobile users now demand better power and battery management techniques to prolong their mobile battery performance. This, together with the need for green Information Communications Technology (ICT), provides motivation for researchers to develop energy efficient techniques to reduce the power consumption in next-generation wireless networks while meeting user’s quality expectations. This paper conducts a realistic performance evaluation of a number of widely used Multi Attribute Decision Making (MADM)-based methods for network selection that aim at keeping the mobile users Always Best Connected anywhere and anytime. The main trade-off parameters considered include energy efficiency and user perceived quality levels for multimedia streaming. The energy consumption is modeled using real experimental results for an Android Mobile device. Similarly, the multimedia quality function was modeled using real user data, combined with a qualitative study to determine the resulting mean opinion scores. The performance analysis shows that the Weighted Multiplicative Method (MEW) finds a better energy-quality trade-off for users in a heterogeneous wireless environment in comparison with three other MADM solutions.