Comparative Analysis of Smart Grid Routing Using Mixed-Integer SOCP and Network Calculus
Smart grids improve how power systems are managed and integrate advanced technologies to improve efficiency and reliability. However, smart grid networks need robust, flexible communication systems to fully realize their potential services. Software-Defined Networking (SDN) offers a promising soluti...
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| Published in: | Procedia computer science Vol. 265; pp. 528 - 535 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
2025
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| ISSN: | 1877-0509, 1877-0509 |
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| Abstract | Smart grids improve how power systems are managed and integrate advanced technologies to improve efficiency and reliability. However, smart grid networks need robust, flexible communication systems to fully realize their potential services. Software-Defined Networking (SDN) offers a promising solution by providing dynamic control and optimization capabilities. Accordingly, this paper presents an optimization framework for network flow scheduling and resource allocation in smart grid communication networks, leveraging SDN to improve flexibility and performance. A two-phase process integrates Mixed-Integer Second-Order Cone Programming (MI-SOCP) and Network Calculus to guarantee efficient data transmission while satisfying strict Quality of Service (QoS) requirements. The combined use of MI-SOCP and Network Calculus ensures robust, cost-effective, and QoS-compliant communication in smart grid networks. Our approach optimizes resource utilization while maintaining predictable performance under varying network conditions, making it well-suited for the demanding operational requirements of smart grid applications. |
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| AbstractList | Smart grids improve how power systems are managed and integrate advanced technologies to improve efficiency and reliability. However, smart grid networks need robust, flexible communication systems to fully realize their potential services. Software-Defined Networking (SDN) offers a promising solution by providing dynamic control and optimization capabilities. Accordingly, this paper presents an optimization framework for network flow scheduling and resource allocation in smart grid communication networks, leveraging SDN to improve flexibility and performance. A two-phase process integrates Mixed-Integer Second-Order Cone Programming (MI-SOCP) and Network Calculus to guarantee efficient data transmission while satisfying strict Quality of Service (QoS) requirements. The combined use of MI-SOCP and Network Calculus ensures robust, cost-effective, and QoS-compliant communication in smart grid networks. Our approach optimizes resource utilization while maintaining predictable performance under varying network conditions, making it well-suited for the demanding operational requirements of smart grid applications. |
| Author | Fellerer, Jonathan German, Reinhard Alshra’a, Abdullah S. Hielscher, Kai-Steffen |
| Author_xml | – sequence: 1 givenname: Abdullah S. surname: Alshra’a fullname: Alshra’a, Abdullah S. email: abdullah.alshraa@fau.de organization: Department of Computer Science 7, Computer Networks and Communication Systems Lab, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany – sequence: 2 givenname: Jonathan surname: Fellerer fullname: Fellerer, Jonathan organization: Department of Computer Science 7, Computer Networks and Communication Systems Lab, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany – sequence: 3 givenname: Kai-Steffen surname: Hielscher fullname: Hielscher, Kai-Steffen organization: Department of Computer Science 7, Computer Networks and Communication Systems Lab, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany – sequence: 4 givenname: Reinhard surname: German fullname: German, Reinhard organization: Department of Computer Science 7, Computer Networks and Communication Systems Lab, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany |
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| Cites_doi | 10.1109/PES.2006.1709546 10.1016/j.sysarc.2019.01.008 10.3390/app5040706 10.3390/app11020627 10.1109/TCOMM.2012.12.100620 10.1109/CCDC.2018.8408012 10.1109/IGESSC59090.2023.10321752 10.1016/j.renene.2019.08.092 10.1109/JIOT.2017.2701205 10.4018/979-8-3693-3451-5.ch013 10.1109/PESGM.2018.8585816 10.1109/TWC.2014.2314121 10.1109/TSG.2018.2835487 10.1007/978-981-15-9927-9_33 10.1109/TPWRS.2020.3036235 10.3390/en10070858 10.1109/COMST.2017.2749760 10.1109/ICCCNT.2014.6963087 10.1007/s11227-024-06203-9 10.1016/j.comcom.2016.09.006 10.1109/TSG.2013.2279184 10.3389/fenrg.2023.1259445 10.1007/s00158-016-1406-5 10.1002/9781119440284 10.1109/JSYST.2014.2304291 10.1109/SmartGridComm57358.2023.10333945 10.1109/ACCESS.2020.3043600 10.1109/TWC.2023.3347667 10.1088/1742-6596/2803/1/012012 10.1109/JSAC.2012.120708 |
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| Keywords | Quality of Service (QoS) Network Calculus Smart Grid Networks Mixed-Integer Second-Order Cone Programming (MI-SOCP) |
| Language | English |
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