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Energy efficient network selection and seamless handovers in Mixed Networks

Network selection is the decision process for a mobile terminal to handover between homogeneous or heterogeneous networks. This handover decision can be either mobile or network initiated. Today's decision is mainly based on the received signal strength (RSS). In the future as the number of ava...

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Bibliographic Details
Main Authors: Huaiyu Liu, Maciocco, C., Kesavan, V., Low, A.L.Y.
Format: Conference Proceeding
Language:English
Subjects:
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Summary:Network selection is the decision process for a mobile terminal to handover between homogeneous or heterogeneous networks. This handover decision can be either mobile or network initiated. Today's decision is mainly based on the received signal strength (RSS). In the future as the number of available networks increase the selection process must evaluate additional factors such as monetary cost, offered services, network conditions, required energy to operate in a network, system conditions, user and operator's preferences. Upcoming IEEE or 3GPP standards provide facilities such as network maps, handover negotiation messages, network and client event reports and message exchange like handover triggers and handover negotiation. In this paper we investigate the use of a cost function to perform an optimal network selection using information provided by these standards, such as network coverage map or network properties. The cost function provides flexibility to balance different factors in the decision making, and our research is focused on improving both seamlessness and energy efficiency of the device and handovers. We evaluated our approach based on usage scenarios over WiFi, WiMax, and 3G networks using captured signal strength traces. The results of our simulations and early implementation show that our schemes select the optimal networks and handovers were triggered at appropriate times to increase overall network connectivity as compared to traditional triggering schemes, while at the same time optimizing energy consumption of multi-radio devices.
DOI:10.1109/WOWMOM.2009.5282451