@inproceedings{FraunholzSchoerghoferVrinssenKoenigetal.2021, author = {Fraunholz, Daniel and Sch{\"o}rghofer-Vrinssen, Richard and K{\"o}nig, Hartmut and M{\"u}hlbauer, Wolfgang and Zahoransky, Richard}, title = {Mobility-Enabling Edge Cloud Infrastructure: Testbed and Experimental Evaluation}, series = {2021 IEEE Cloud Summit}, booktitle = {2021 IEEE Cloud Summit}, pages = {19 -- 24}, year = {2021}, abstract = {Mobility management is a key feature of mobile edge computing. We present an edge cloud infrastructure testbed to explore various mobility scenarios. The design objection of this testbed has been a flexible open platform based on commodity hardware that can easily be scaled with more edge devices and compute resources to perform various edge cloud experiments. As first experiments on our testbed, we have investigated the feasibility of task migration among edge devices caused by edge device overload and unpredictable user movements. We describe the migration process and present some measurements to demonstrate the feasibility.}, language = {en} } @inproceedings{ZahoranskyMuehlbauerKoenig2020, author = {Zahoransky, Richard and M{\"u}hlbauer, Wolfgang and K{\"o}nig, Hartmut}, title = {Towards Mobility Support in Edge Clouds}, series = {2020 IEEE Cloud Summit}, booktitle = {2020 IEEE Cloud Summit}, editor = {IEEE,}, publisher = {IEEE Xplore}, pages = {1 -- 6}, year = {2020}, abstract = {Mobile-access edge clouds provide distributed com-pute capacities for low-latency applications. 5G technology willpave the way for such mobile deployment scenarios. In thispaper, we propose an edge cloud infrastructure that supportslow-latency video analysis connected with bandwidth reductionfor a moving group of persons. As example, we consider a mobilebody camera scenario that monitors the situation in a certain areaand transmits it to an operations center. Our discussion focuseson three aspects: mobility support, low-latency video processing,and bandwidth reduction. For this, we propose a mobile edgecloud infrastructure with a central cloud. In order to optimizevideo processing we optimize the edge cloud device assignmentof the cameras depending on their movement by reassigning itto another cloud device. This requires live migration of ongoingvideo analysis between edge devices. Finally we discuss the useof a mobile central cloud.}, language = {en} }