TY - GEN
T1 - Improving Quality of Experience of Service-Chain Deployment for Multiple Users
AU - Wang, I. Chih
AU - Wen, Charles H.P.
AU - Chao, H. Jonathan
N1 - Funding Information:
with Latency Prediction” (QoEDD) for deploying service chains in practice. According to our experiments, QoEDD reduces more than 99% rejections and more than 99% of waiting time, comparing to RDD and LDD. These results illustrate that optimizing latency or computational resource does not necessarily improve the quality of experience. Moreover, QoEDD reduces 99.89% rejections and 99.99% waiting time, comparing to SOVWin. In conclusion, QoEDD is an efficient algorithm for service-chain deployment which notably elevate the quality of experience. ACKNOWLEDGMENT This paper is particularly supported by ”Aiming for the SPROUT Project-Center for Open Intelligent Connectivity” of National Chiao Tung University and Ministry of Education, Taiwan, R.O.C.
Publisher Copyright:
© 2018 IEEE.
PY - 2019/1/22
Y1 - 2019/1/22
N2 - The fifth generation (5G) mobile communication network aims at providing high-rate, low-latency services. When a user subscribes a chain of service functions (a.k.a. service chain) from the telecom providers, a Service Level Agreement (SLA) is specified according to his requirement. Deploying service chains optimally has always been a big issue. Several previous works have presented various strategies of service-chain deployment for optimizing either latency or computational resources; however, over-optimization of latency or computational resource is not necessarily equivalent to improvement on quality of experience. Therefore, in this paper, we formally formulate this problem of optimizing quality of experience with the queuing theory and mixed-integer linear programming. In addition, we propose an efficient algorithm named 'QoE-driven Service-Chain Deployment with Latency Prediction' for deploying a service chain for a user in practice. According to the experiments, our algorithm reduces > 99% rejections and > 99% waiting time, notably elevating the quality of experience for users.
AB - The fifth generation (5G) mobile communication network aims at providing high-rate, low-latency services. When a user subscribes a chain of service functions (a.k.a. service chain) from the telecom providers, a Service Level Agreement (SLA) is specified according to his requirement. Deploying service chains optimally has always been a big issue. Several previous works have presented various strategies of service-chain deployment for optimizing either latency or computational resources; however, over-optimization of latency or computational resource is not necessarily equivalent to improvement on quality of experience. Therefore, in this paper, we formally formulate this problem of optimizing quality of experience with the queuing theory and mixed-integer linear programming. In addition, we propose an efficient algorithm named 'QoE-driven Service-Chain Deployment with Latency Prediction' for deploying a service chain for a user in practice. According to the experiments, our algorithm reduces > 99% rejections and > 99% waiting time, notably elevating the quality of experience for users.
UR - http://www.scopus.com/inward/record.url?scp=85062621044&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062621044&partnerID=8YFLogxK
U2 - 10.1109/IWQoS.2018.8624167
DO - 10.1109/IWQoS.2018.8624167
M3 - Conference contribution
AN - SCOPUS:85062621044
T3 - 2018 IEEE/ACM 26th International Symposium on Quality of Service, IWQoS 2018
BT - 2018 IEEE/ACM 26th International Symposium on Quality of Service, IWQoS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th IEEE/ACM International Symposium on Quality of Service, IWQoS 2018
Y2 - 4 June 2018 through 6 June 2018
ER -