2026· IEEE Open Journal of the Communications Society· Vol 7, pp. 7744-7769· 0 citations· 38 references
Computer Science
TL;DR
Simulation results reveal that both setup penalties and controller activation thresholds are critical determinants of system behavior across both optimization-based and heuristic schemes, highlighting the necessity of jointly optimizing reassignment policies and controller activation strategies to support robust, low-latency, and resource-aware SDN architectures for large-scale LEO satellite constellations.
Abstract
The growing demand for adaptive, resilient communication in software-defined networking (SDN)-enabled low Earth orbit (LEO) satellite networks underscores the importance of optimized SDN controller management. In particular, the overhead introduced by setup penalties and constraints on controller capacity significantly impacts key performance metrics, including satellite-to-controller delay, reassignment frequency, and the number of concurrently active controllers. These factors collectively influence the network’s ability to provide low-latency services while maintaining resource utilization in dynamic orbital environments. To investigate these dynamics, we develop a simulation framework based on OMNeT++ and INET, extending the open-source satellite simulator OS3 with enhanced satellite mobility and dynamic routing. The framework integrates SDN functionality into LEO satellite networks using the OpenFlow protocol, enabling centralized, programmable control with real-time adaptability. A central challenge in such networks is not only assigning satellites to appropriate controllers, but also dynamically activating and deactivating SDN controllers to match evolving topologies and traffic demands. To address this, we consider the baseline Dynamic Satellite-to-Controller Assignment (DSCA), the proposed Optimal Dynamic Satellite-to-Controller Assignment (Opt-DSCA), and their scalable heuristic variants (H-DSCA and H-Opt-DSCA). Opt-DSCA jointly minimizes satellite-to-controller delay and the number of active controllers, while incorporating setup penalties and activation costs to discourage unnecessary satellite migrations and redundant controller utilization. Simulation results reveal that both setup penalties and controller activation thresholds are critical determinants of system behavior across both optimization-based and heuristic schemes. Lower penalties enhance adaptability but result in more frequent reassignments and higher variability in controller state transitions. Conversely, higher penalties improve robustness by limiting controller switching, though at the cost of reduced flexibility and increased latency. These findings highlight the necessity of jointly optimizing reassignment policies and controller activation strategies to support robust, low-latency, and resource-aware SDN architectures for large-scale LEO satellite constellations.
An Adaptive SDN-Edge 5G Architecture (ASE-5G) is proposed that integrates SDN programmability with edge-assisted control-plane coordination while preserving compatibility with the 3rd Generation Partnership Project (3GPP) service-based architecture.
Vivi Monita, Naufal Hanan, Lutfianto et al.· 0 citations
Findings affirm that the suggested scalable control plane is practical in supporting large scale SDN implementation and is therefore applicable in future carrier grade, data center and wide area network deployments at realistic workloads with varying topological setups in the modern programmable networks in the world.
A. Nagadeepan, Vishakha Abhay Gaidhani, Bhambare Rajesh et al.· Journal of Intelligent Decis...· 0 citations
Software-defined satellite networks (SDSNs) enhance resource utilization and flexibility in space-based networks by leveraging a global view and programmability. A highly reliable control plane is essential to sustain network operations. However, the highly dynamic topology and physical failures in Low Earth Orbit (LEO) environments can cause satellite node outages or inter-satellite link disruptions, leading to control plane interruptions and local load imbalances. To address this, we propose a switch migration mechanism for failure recovery and establish a multi-objective migration model that jointly optimizes control link delay, controller load variance, and normalized migration ratio. To accommodate distinct dynamic characteristics such as frequent topology changes, failure-intensive periods, and stable periods, we design two algorithms: a robust migration algorithm, DNSGA-II, which features population diversity maintenance and environmental awareness, and an efficient migration algorithm, IHAOAVOA, which integrates strong global exploration with powerful local exploitation. Simulation results show that IHAOAVOA rapidly converges under large-scale failures, achieving millisecond-level delay recovery and low normalized migration ratio overhead during failure-intensive periods, while DNSGA-II focuses on long-term load balancing and system stability during stable periods, effectively suppressing localized controller overload. By adopting IHAOAVOA during topology fluctuations or high-failure phases to reduce delay, and switching to DNSGA-II during stable phases to optimize load distribution, the overall network robustness can be improved under the evaluated failure scenarios. This work provides effective support for achieving highly reliable control in SDSNs under failure scenarios.
Shuang Xu, Zhen-Yu Yin, Min Huang et al.· Italian National Conference...· 0 citations
Satellite-airborne-terrestrial edge computing networks (SATECNs) emerge as a global solution for Internet of Things (IoT) since they can provide global coverage even in remote areas and under natural disasters. However, their dynamic and non-stationary nature makes control and resource allocation more challenging. Preserving data freshness is crucial in many IoT applications and requires timely decisions. To address these challenges, we present a knowledge-base software-defined networking architecture for satellite–airborne–terrestrial networks (KB-SAT-SDN) that enables collaboration between SDN controllers to optimize SAT configurations. A shared knowledge base (KB) is built through lifelong learning (LL) to continuously adapt and efficiently manage computing and networking resources to minimize the age of information (AoI) and energy consumption. To further accelerate learning, we exploit the heterogeneity of nodes and offloading decisions by defining different learning domains and designing a cross-domain lifelong learning (CDLL-SATECN) algorithm. With domain-specific projections, knowledge is shared between domains. Numerical results show that CDLL reduces average AoI and energy by up to 70% and converges $8\times $ faster than existing baselines. It achieves the lowest or near-lowest penalty across all RL domains, nearly halving Natural Actor-Critic (NAC)’s penalty in the most complex domains. LEO assistance lowers penalty/AoI from 61.9/49.4 to 48.5/45.1 relative to a domain without LEO, while reducing UAV energy and queues. The sensitivity analysis confirms that CDLL maintains a stable AoI–energy tradeoff over a broad range of weighting parameters.
Yinxuan Wu, Ning Wang, B. Lorenzo et al.· IEEE Transactions on Wireles...· 0 citations