Multimedia QoE optimized management using prediction and statistical learning
Open accessAbstract
We present a scheme for flow management with heterogeneous access technologies available indoors and in a campus network such as GPRS, 3G and Wi-Fi. Statistical learning is used as a key for optimizing a target variable namely video quality of experience (QoE). First we analyze the data using passive measurements to determine relationships between parameters and their impact on the main performance indicator, video Quality of Experience (QoE). The derived weights are used for performing prediction in every discrete time interval of our designed autonomic control loop to know approximately the QoE in the next time interval and perform a switch to another access technology if it yields a better QoE level. This user-perspective performance optimization is in line with operator and service provider goals. QoE performance models for slow vehicular and pedestrian speeds for Wi-Fi and 3G are derived and compared.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the literature, simple-regression models with a single feature are most dominant, although the collective impact of different QoS parameters was also considered.
“In the literature, simple-regression models with a single feature are most dominant [145, 240, 383, 408], although the collective impact of different QoS parameters was also considered [23,132].”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [132]
Cites
Video Quality Estimation for Mobile H.264/AVC Video Streaming
Ries, M., Némethová, O., & Rupp, M. (2008) · Journal of Communications · doi:10.4304/jcm.3.1.41-50 · Cited by 85 · see citing works
Wireless LANs: From WarChalking to Open Access Networks
Battiti, R., Cigno, R. L., Sabel, M., et al. (2005) · Mobile Networks and Applications · doi:10.1007/s11036-005-6422-4 · Cited by 39 · see citing works
Autonomic resource management in IEEE 802.11 open access networks
Elkotob, M. (2008) · Epubl LTU · Cited by 10 · see citing works
Self-citationFeasibility of QoS control based on QoS mapping over IP networks
Ito, Y., & Tasaka, S. (2008) · Computer Communications · doi:10.1016/j.comcom.2008.03.025 · Cited by 7 · see citing works
Estimating user-perceived Web QoS by means of passive measurement
Cheng, W., Gong, J., & Ding, W. (2005) · The ... IEEE International Conference on Networks/The IEEE International Conference on Networks · doi:10.1109/icon.2004.1409185 · Cited by 3 · see citing works
A Parameter Injection Algorithm for Real-Time Traffic in 802.11 Open Access Networks
Elkotob, M., & Albayrak, Ş. (2007) · doi:10.1109/glocom.2007.486 · Cited by 3 · see citing works
Self-citationIto, Y., & Tasaka, S. (2006) · International Conference on Communications · doi:10.1109/icc.2006.255475 · Cited by 3 · see citing works
Multimedia Quality Prediction Methodologies for Advanced Mobile and IP-Based Telephony
Kitawaki, N. (2006) · IEICE Transactions on Communications · doi:10.1093/ietcom/e89-b.2.262 · Cited by 2 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Boutaba, R., Salahuddin, M. A., Limam, N., Ayoubi, S., Shahriar, N., Estrada-Solano, F., & Caicedo, O. M. (2018) · Journal of Internet Services and Applications · doi:10.1186/s13174-018-0087-2 · Cited by 1,036 · see citing works
Han, B., Zhang, X., Qi, Y., Gao, Y., & Yang, D. (2012) · Wireless Personal Communications · doi:10.1007/s11277-012-0739-7 · Cited by 24 · see citing works
- Authors
- Elkotob, M., Grandlund, D., Andersson, K., & Ahlund, C.
- Affiliations
- Luleå University of Technology (SE)
- ORCID
- Andersson, Karl
- Venue
- IEEE Local Computer Network Conference
- Publisher
- IEEE
- Published
- 2010-10
- Pages
- 324-327
- ISSN
- 0742-1303 (ISSN-L)
- OpenAlex
- W2125316131
- Cited by
- 23
- References
- 8
- Citations by year
- 2022: 1 · 2020: 3 · 2019: 3 · 2018: 3 · 2016: 3 · 2014: 4 · 2013: 2 · 2012: 3
- FWCI
- 1.73
- Type
- conference paper
- Language
- en
- Open access
- green
- urn.kb.se
- Licence
- other-oa
- Locations
- Conference on Local Computer Networks (publishedVersion)
- Epubl LTU (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Network Optimization
- Keywords
- video quality of experience, statistical learning, QoE prediction, autonomic regulation, passive measurement, GPRS, 3G, Wi-Fi, campus network
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
