Software Defined Networking (SDN) has been identified as a potential approach to achieve a more flexible control and management of the traditional satellite systems and enhance the opportunities for future services including the possibility of a hybrid satellite/terrestrial network. Given the renewed interest towards Low-Earth-Orbit (LEO) constellations, an interesting research topic is the design of a suitable network management model taking into account user specific metrics. In this paper, we address this issue while investigating the use-case scenario of an SDN-enabled satellite space segment. A Dynamic Controller Placement Problem (DCPP) is considered for a LEO constellation where the traffic demands change dynamically based on users' geographical position and time zone. To this end, we develop a mathematical model and formulate it as an Integer Linear Programming (ILP) guaranteeing an optimal controller placement and satellite-to-controller assignment minimizing the average flow setup time with respect to the traffic dynamics. We show results for the DCPP regarding the average flow setup time. Furthermore, a comparison with respect to the static approach is investigated and the proposed SDN-enabled LEO constellation architecture is compared with alternative architectures proposed in the state of the art.
Abstract-With Network Function Virtualization (NFV), network functions are deployed as modular software components on the commodity hardware, and can be further chained to provide services. Network operators offer different classes of services to their users and their requirements are specified in Service Level Agreements (SLA) which include several QoS performance parameters such as the maximum tolerated delay or the minimum availability. So far, state of the art solutions for NFV deployment focus on delay related requirements. However, service availability, which is an important requirement for any SLA is mostly neglected. This paper focuses on the placement of virtualized network functions, with the target to support service differentiation in terms of delay and availability while minimizing the associated costs. We present two solutions: an ILP formulation and an efficient heuristic to obtain near optimal solution. Considering a national core network case study, we show that the proposed function placement solutions are able to guarantee both delay and availability requirements, and imply only a limited increase of used network resources, compared to solutions that only address a single requirement. Finally, we show that the execution time of the proposed heuristic scales well with the size of the problem.
In the context of the 5G ecosystem, the integration between the terrestrial and satellite networks is envisioned as a potential approach to further enhance the network capabilities. In light of this integration, the satellite community is revisiting its role in the next generation 5G networks. Emerging technologies such as Software-Defined Networking (SDN) which rely on programmable and reconfigurable concepts, are foreseen to play a major role in this regard. Therefore, an interesting research topic is the introduction of management architecture solutions for future satellite networks driven by means of SDN. This anticipates the separation of the data layer from the control layer of the traditional satellite networks, where the control logic is placed on programmable SDN controllers within traditional satellite devices. While a centralized control layer promises delay reductions, it introduces additional overheads due to reconfiguration and migration costs. In this paper, we propose a method to quantify the overhead imposed on the network by the aforementioned parameters while investigating the usecase scenario of an SDN-enabled satellite space segment. We make use of an optimal controller placement and satellite-tocontroller assignment which minimizes the average flow setup time with respect to varying traffic demands. Furthermore, we provide insights on the network performance with respect to the migration and reconfiguration cost for our proposed SDNenabled architecture. Finally, we compare our proposed space segment SDN-enabled architecture with alternative solutions in the state-of-the-art given the aforementioned performance metrics.
People desire to be connected, no matter where they are. Recently, providing Internet access to on-board passengers has received a lot of attention from both industry and academia. However, in order to guarantee an acceptable Quality of Service (QoS) for the passenger services with low incurred cost, the path to route the services, as well as the datacenter (DC) to deploy the services should be carefully determined. This problem is challenging, due to different types of Air-to-Ground (A2G) connections, i.e., satellites and Direct Air-To-Ground (DA2G) links. These A2G connection types differ in terms of cost, bandwidth, and latency. Furthermore, due to the flights' movements, it is important to consider adapting the service location accordingly. In this work, we formulate two Mixed Integer Linear Programs (MILPs) for the problem of Joint Service Placement and Routing (JSPR): i) Static (S-JSPR), and ii) Mobility-Aware (MA-JSPR) in Space-Air-Ground Integrated Networks (SAGIN), with the objective of minimizing the total cost. We compare S-JSPR and MA-JSPR using comprehensive evaluations in a realistic European-based SAGIN. The obtained results show that the MA-JSPR model, by considering the future flight positions and using a service migration control, reduces the long-term total cost notably. Also, we show S-JSPR benefits from a low time-complexity and it achieves lower end-to-end delays comparing to MA-JSPR model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.