Maximization of Service Flows Rates as a Solution of Network Capacity Allocation Problem
DOI: 10.23977/iotea.2017.31001 | Downloads: 43 | Views: 2585
Bohdan Buhyl 1, Pavlo Huskov 1, Orest Lavriv 1, Roman Bak 1, Andriy Luntovskyy 2
1 Department of Telecommunications, Lviv Polytechnic National University, Lviv, Ukraine
2 BA Dresden Univ. of Coop. Education, Dresden, Germany
Corresponding AuthorOrest Lavriv
The problem of network capacity allocation is a well-known problem in information and telecommunication area. Emerging set of new services such as cloud-based services, internet of things services, health care services, delivery support services are the key motivators of network capacity growth. In general, network capacity allocation is the static solution for general resources balancing dynamic problem. As far as user demands to change rapidly the network should be capable to support all traffic in accordance with service quality indicators. The solution of the formulated problem is the set of maximum rates of the corresponding service flows that compete with other service flows. This information is essential for the implementation of the service-oriented resource planning, as it enables to calculate the customers’ audience if the values of services popularity and subscriber’s distribution in the access network are predefined.
KEYWORDSNetwork resources allocation, Service flow, Information services, Service-oriented resource planning, Network routing.
CITE THIS PAPER
Bohdan, B., Pavlo, H., Orest, L., Roman, B. and Andriy, L.. Maximization of Service Flows Rates as a Solution of Network Capacity Allocation Problem. Internet of Things (IoT) and Engineering Applications (2018) 3: 1-10.
 J. He, J. Rexford, and M. Chiang, "Design principles of manageable networks", Princeton University Computer Science, Technical Report TR-770-06, Oct. 2006.
 L. Beril Toktay and R. Uzsoy, "A Capacity Allocation Problem with Integer Side Constraints", European Journal of Operational Research, Volume 109, Issue 1, pp. 170-182, 1998.
 L.F. Ochoa, C.J. Dent and G. P. Harrison, "Distribution Network Capacity Assessment: Variable DG and Active Networks", IEEE Transactions on Power Systems, vol. 25, pp. 87-95, 2010.
 Sayan Sen Sarma, Goutam Chakraborty, “Queuing model-based optimal traffic flow in a grid network”, IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 2015, pp. 1-3.
 A.V. Lemeshko, H.D.K. Al-Janabi and O.M. Khodzhaev, "A Mathematical Model of the Centralized Distribution of the Downlink WiMAX Resources on the Channel and Network Layers of the OSI Model", Telecommunications Problems, No. 1 (18), p. 52-71, 2016. [Online]. Available: http://pt.journal.kh.ua/2016/1/1/161_lemeshko_wimax.pdf.
 Qin Ba, Ketan Savla and Giacomo Como, “Distributed optimal equilibrium selection for traffic flow over networks”, 54-th IEEE Conference on Decision and Control (CDC), pp. 6942-6947, 2015.
 Bonnans, J. Frédéric, Gilbert, J. Charles, Lemaréchal, Claude, Sagastizábal, Claudia A., “Numerical optimization: Theoretical and practical aspects”, Universitext (Second revised ed. of translation of 1997 French ed.), Berlin, Springer-Verlag, ISBN 3-540-35445-X. MR 2265882.
 M. Klymash , O. Lavriv , B. Buhyl , Y. Danik, “Service quality oriented method of multiservice telecommunication networks design,” in Modern Problems of Radio Engineering Telecommunications and Computer Science (TCSET), 2012 International Conference on, 2012.
 P. Huskov, O. Lavriv, and M. Klymash, “The concept of services assurance in heterogeneous service-oriented systems,” in 2016 Third International Scientific-Practical Conference Problems of Infocommunications Science and Technology (PIC S&T), 2016, pp. 24–26.
 O. Lavriv, B. Buhyl, P. Huskov, and R. Bak, “Heterogeneous network capacity distribution among service flows,” in 2017 14th International Conference The Experience of Designing and Application of CAD Systems in Microelectronics (CADSM), 2017, pp. 173–175.
 Bioinformatics Toolbox. Documentation. [Online]. Available: https://www.mathworks.com/ help/ bioinfo/index.html
 Optimization Toolbox. Documentation. [Online]. Available: https://www.mathworks.com/help/optim/.