ADVANCED TENSOR APPROACH TO FAST REROUTE WITH QUALITY OF SERVICE PROTECTION UNDER MULTIPLE PARAMETERS
DOI:
https://doi.org/10.20535/2411-2976.12020.41-52Keywords:
infocommunication network, fast rerouting, bandwidth, average end-to-end packet delay, probability of packet loss, tensor, space, coordinate system.Abstract
Background. The paper proposes a solution to such an urgent problem today, as to ensure the fault tolerance of infocommunication networks with the support of the required level of quality of service. The proposed solution is based on the
implementation of an advanced tensor approach to fast reroute with the protection of the level of quality of service under multiple parameters.
Objective. The aim of the article is to improve the flow-based fast rerouting model in the infocommunication network, which is based on updated conditions for ensuring quality of service in terms of bandwidth, average end-to-end delay, and probability of packet loss. It was possible to obtain updated conditions for ensuring the quality of service through the use of a tensor approach to modeling infocommunication networks.
Methods. As research methods, graph theory, tensor theory, queuing systems were used. For mathematical modeling and experimental studies, the MatLab simulation package was used.
Results. As a result of the study, under the conditions of implementing fast rerouting, it was possible to provide the required level of quality of service in the infocommunication network. At the same time, with an increase in QoS requirements, thanks to an improved tensor approach, the updated conditions for ensuring the quality of service while implementing fast rerouting were adequate, which, as a result, contributed to a more efficient use of the available network resource.
Conclusions. Implementation of an improved tensor approach to solving the problem of fast rerouting will ensure the fault tolerance of the infocommunication network with the protection of the level of quality of service in terms of bandwidth, average end-to-end delay, and the probability of packet loss.
References
R. White, E. Banks. Computer Networking Problems
and Solutions: An innovative approach to building resilient,
modern networks // Addison-Wesley Professional. – 2017. –
p.
A. S. Monge, K. G. Szarkowicz. MPLS in the SDN Era:
Interoperable Scenarios to Make Networks Scale to New
Services // O’Reilly Media, Inc. – 2016. – 920 p.
J. Rak. Resilient routing in communication networks //
Switzerland: Springer. – 2015. – 181 p.
https://doi.org/10.1007/978-3-319-22333-9
J. Rak, D. Papadimitriou, H. Niedermayer, P. Romer.
Information-driven network resilience: Research challenges
and perspectives // Optical Switching and Networking. –
– Vol.23, №2. – P.156-178.
https://doi.org/10.1016/j.osn.2016.06.002
O. Lemeshko, O. Yeremenko, N. Tariki. Solution for
the Default Gateway Protection within Fault-Tolerant
Routing in an IP Network // International journal of electrical
and computer engineering systems. – 2017. – Vol. 8(1). –
P.19-26. https://doi.org/10.32985/ijeces.8.1.3
H. Hasan, J. Cosmas, Z. Zaharis, P. Lazaridis, S.
Khwandah. Development of FRR mechanism by adopting
SDN notion // 2016 24th International Conference on
Software, Telecommunications and Computer Networks
(SoftCOM) Proceedings. – 2016. – P.1-72.
M. Pióro, A. Tomaszewski, C. Żukowski, D. Hock, M.
Hartmann, M. Menth. Optimized IP-based vs. explicit paths
for one-to-one backup in MPLS fast reroute // 14th
International Telecommunications Network Strategy and
Planning Symposium (NETWORKS) Proceedings. – 2010. –
P.1-6. https://doi.org/10.1109/NETWKS.2010.5624923
A. Alashaikh, D. Tipper, T. Gomes. Supporting
differentiated resilience classes in multilayer networks // 12th
International Conference on the Design of Reliable Communication Networks (DRCN) Proceedings. – 2016. –
P.31-38. https://doi.org/10.1109/DRCN.2016.7470832
A.V. Lemeshko, O.S. Yeremenko, N. Tariki.
Improvement of flow-oriented fast reroute model based on
scalable protection solutions for telecommunication network
elements // Telecommunications and Radio Engineering. –
– Vol.76(6). – P.477-490.
https://doi.org/10.1615/TelecomRadEng.v76.i6.30
D. Wang and G. Li. Efficient Distributed Bandwidth
Management for MPLS Fast Reroute // IEEE/ACM
Transactions on Networking. –2008. – Vol. 16, no. 2. – P.
-495.
O. Lemeshko, M. Yevdokymenko, O. Yeremenko, A.M.
Hailan, P. Segeč, J. Papán. Design of the Fast ReRoute QoS
Protection Scheme for Bandwidth and Probability of Packet
Loss in Software-Defined WAN // 15th International
Conference the Experience of Designing and Application of
CAD Systems in Microelectronics (CADSM) Proceedings. –
– P.3/72-3/76.
C. D. Nocito, M. S. Scordilis. Monitoring jitter and
packet loss in VoIP networks using speech quality features //
IEEE Consumer Communications and Networking
Conference (CCNC). – Las Vegas, NV. – 2011. – P.685-686.
https://doi.org/10.1109/CCNC.2011.5766571.
O. Lemeshko, O. Yeremenko, M. Yevdokymenko,
A.M. Hailan. Tensor Based Load Balancing under Self-
Similar Traffic Properties with Guaranteed QoS // Advanced
Trends in Radioelectronics, Telecommunications and
Computer Engineering (TCSET): Proceedings of the 15th
International Conference. – 25–29 February, 2020. – Lviv-
Slavske, Ukraine. – P.293-297,
https://doi.org/10.1109/TCSET49122.2020.235442.
O. Lemeshko, M. Yevdokymenko, A. Alsaleem.
Development of the tensor model of multipath QoE-routing
in an infocommunication network with providing the
required Quality Rating // Eastern-European Journal of
Enterprise Technologies. – 2018. – №2(95). – P.40-46.
https://doi.org/10.15587/1729-4061.2018.141989
O. Lemeshko, O. Yeremenko, M. Yevdokymenko.
Tensor Model of Fault-Tolerant QoS Routing with Support of
Bandwidth and Delay Protection // XIIIth International
Scientific and Technical Conference Computer Sciences and
Information Technologies (CSIT) Proceedings. – 2018. – P.
-138. https://doi.org/10.1109/stc-csit.2018.8526707
O. Lemeshko, M. Yevdokymenko, O. Yeremenko,
O. Nevzorova, A. Snihurov, T. Kovalenko. Fast ReRoute
Model with VoIP Quality of Experience Protection // 3rd
IEEE International Conference Advanced Information and
Communication Technologies (AICT). – July 2–6, 2019. –
Lviv, Ukraine. – P. 1-6.
G. Kron. Tensor analysis of networks // J. Wiley and
Sons. – 1949. – 635 p.
O. Yeremenko. Development of the dynamic tensor
model for traffic management in a telecommunication
network with the support of different classes of service //
Eastern-European Journal of Enterprise Technologies. –
– Vol. 6, Issue 9 (84). – P.12–19. DOI: 10.15587/1729-
2016.85602
O.V. Lemeshko, O.S. Yeremenko, A.M. Hailan.
QoS solution of traffic management based on the dynamic
tensor model in the coordinate system of interpolar paths and
internal node pairs // Radio Electronics & Info
Communications (UkrMiCo): Proceedings of the
International Conference. – 2016. – Kiev, Ukraine. – P.1–6.
DOI: 10.1109/UkrMiCo.2016.7739625
O. Lemeshko, O. Yeremenko. Routing Tensor
Model Presented in the Basis of Interpolar Paths and Internal
Node Pairs // Problems of Infocommunications Science and
Technology (PIC S&T): Proceedings of the Third
International Scientific-Practical Conference. – 2016. –
Kharkiv, Ukraine. – P.201–204. DOI:
1109/INFOCOMMST.2016.7905381
O. Lemeshko, M. Yevdokymenko, Z. Hu, O.
Yeremenko. Inter-domain routing method under normalized
Quality of Service based on hierarchical coordination //
CEUR Workshop Proceedings of The Third International
Workshop on Computer Modeling and Intelligent Systems
(CMIS). – 2020. – Vol. 2608. – P. 394-408.
