TY - GEN
T1 - A QoS-aware streaming service over fog computing infrastructures
AU - Lai, Chin Feng
AU - Song, Dong Yu
AU - Hwang, Ren Hung
AU - Lai, Ying Xun
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/9/22
Y1 - 2016/9/22
N2 - The cloud computing technology gradually brings every service online that makes all data and information of services is stored in cloud storage. However, there are real-time services such as multimedia streaming and emergency notification that require sensitive response and low latency. Regarding of the cloud computing, the data transmission between the end-users and the cloud significantly increases the response latency and limits the user coverage, thus preventing cloud streaming services to achieve high user quality of service. To this end, a QoS-aware streaming service over fog computing infrastructures is proposed to relieve the traditional content delivery issues by adapting the video to the current network conditions and possibly exploiting local computing resources. Fog computing is designed to extend the edge of the cloud network in order to decrease the latency and network congestion. Experimental results show the proposed mechanism enables service providers to improve resource utilization and quality of service by incorporating information from different layers in order to deliver and adapt a video in its best possible quality over fog computing infrastructures.
AB - The cloud computing technology gradually brings every service online that makes all data and information of services is stored in cloud storage. However, there are real-time services such as multimedia streaming and emergency notification that require sensitive response and low latency. Regarding of the cloud computing, the data transmission between the end-users and the cloud significantly increases the response latency and limits the user coverage, thus preventing cloud streaming services to achieve high user quality of service. To this end, a QoS-aware streaming service over fog computing infrastructures is proposed to relieve the traditional content delivery issues by adapting the video to the current network conditions and possibly exploiting local computing resources. Fog computing is designed to extend the edge of the cloud network in order to decrease the latency and network congestion. Experimental results show the proposed mechanism enables service providers to improve resource utilization and quality of service by incorporating information from different layers in order to deliver and adapt a video in its best possible quality over fog computing infrastructures.
UR - http://www.scopus.com/inward/record.url?scp=84991787655&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84991787655&partnerID=8YFLogxK
U2 - 10.1109/DMIAF.2016.7574909
DO - 10.1109/DMIAF.2016.7574909
M3 - Conference contribution
AN - SCOPUS:84991787655
T3 - 2016 Digital Media Industry and Academic Forum, DMIAF 2016 - Proceedings
SP - 94
EP - 98
BT - 2016 Digital Media Industry and Academic Forum, DMIAF 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 Digital Media Industry and Academic Forum, DMIAF 2016
Y2 - 4 July 2016 through 6 July 2016
ER -