%0 Conference Paper %1 info3-inproceedings-2016-16 %A Dinh-Xuan, Lam %A Seufert, Michael %A Wamser, Florian %A Tran-Gia, Phuoc %B IEEE 6th International Conference on Communications and Electronics (ICCE) %C Ha Long, Vietnam %D 2016 %K %T QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service %X The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.

@inproceedings{info3-inproceedings-2016-16, abstract = {The paradigm of Software as a Service has gained great achievements in the last decade. By transferring computation and storage to the cloud and migrating services to the edge network, users benefit from using demanding services on lightweight devices. However, the user perceived quality of experience (QoE) for these services is facing the challenges of network impairments and the accessibility of users. Unlike a typical PC-based software, the cloud provides users a location-aware, flexible placement of resource for a cost effective service. The geographical placement of content is therefore one of the key factors that affects the user's satisfaction. The closer the content to the user geographically is, the faster it will be delivered to the user that will also increase the user perceived QoE. In this work, we estimate more precisely the QoE for photo loading time in a particular usage of a photo album cloud service with regard to the influence of various parameters. Firstly, we validate a TCP throughput model and use it to calculate the photo loading time from a given photo size and network QoS. Thereafter, we formulate a mapping function to calculate the MOS value from a QoE model adding the output of the TCP model. From this mapping function, we can estimate QoE for photo loading time from a given photo size, its placement and network QoS. Our main contribution is to determine the trade-off between the size of photo and its placement to acquire a high QoE for photo loading time, which is important for the development of a photo album cloud service.}, added-at = {2023-12-13T01:39:50.000+0100}, address = {Ha Long, Vietnam}, author = {Dinh-Xuan, Lam and Seufert, Michael and Wamser, Florian and Tran-Gia, Phuoc}, biburl = {https://www.bibsonomy.org/bibtex/27a8d435964174bb5553e66d883f3ecbe/admin}, booktitle = {IEEE 6th International Conference on Communications and Electronics (ICCE)}, interhash = {74a527953909242d09c6b6fa9349a1de}, intrahash = {7a8d435964174bb5553e66d883f3ecbe}, keywords = {}, month = {7}, timestamp = {2023-12-13T01:39:50.000+0100}, title = {QoE Aware Placement of Content in Edge Networks on the Example of a Photo Album Cloud Service}, year = 2016 }