@misc{KoenigGaeblerKlaucketal., author = {K{\"o}nig, Hartmut and G{\"a}bler, Jan and Klauck, Ronny and Pink, Mario and Sprejz, Michael}, title = {uBeeMe - A Platform for Mobile Collaborative Applications}, series = {PIK - Praxis der Informationsverarbeitung und Kommunikation}, volume = {36}, journal = {PIK - Praxis der Informationsverarbeitung und Kommunikation}, number = {1}, issn = {0930-5157}, doi = {10.1515/pik-2012-0058}, pages = {S. 43}, language = {en} } @inproceedings{PinkSprejzKoenig, author = {Pink, Mario and Sprejz, Michael and K{\"o}nig, Hartmut}, title = {A Coordinated Group Decision for Vertical Handovers in Heterogeneous Wireless Networks}, series = {2013 International Conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications, Bologna, Italy, November 11-13, 2013}, booktitle = {2013 International Conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications, Bologna, Italy, November 11-13, 2013}, publisher = {IEEE}, address = {Piscataway, NJ}, doi = {10.1109/Mobilware.2013.20}, pages = {130 -- 137}, abstract = {Cooperation and interactions of mobile users is a characteristic feature of mobile collaborative applications. The users are located in different mobile communication networks or move in or among them, respectively. This requires horizontal and vertical handovers. The latter is required when the networks use different network technologies. Usually each mobile device independently chooses the most appropriate network for its purposes to switch to. In group-oriented applications this may lead to an uncoordinated network selection and as consequence to increased energy consumption. In this paper, we present a distributed vertical handover decision algorithm that coordinates the selection of the network among the mobile devices in order to ensure an optimal quality of service for the collaborative application and a low energy consumption of the involved mobile devices. The network selection is based on the calculation of a group benefit for each alternative network using the Simple Additive Weighting (SAW) algorithm. The feasibility of the algorithm is evaluated regarding varying group sizes and resource requirements.}, language = {en} }