SDN-Based Integrated Satellite Terrestrial Cyber–Physical Networks with 5G Resilience Infrastructure: Future Trends and Challenges
Abstract
:1. Introduction
- Proposes a novel SDN-based framework for integrated satellite–terrestrial networks to enable resilient and ubiquitous real-time communications.
- Proposes both traffic steering and switching within the user-plane connectivity model to intelligently select optimal AN based on dynamic network conditions and application QoS requirements.
- Incorporates QoS aware multi-attribute decision-making for AN selection, accounting for metrics such as latency, jitter, and available bandwidth.
- Demonstrates how distributed SDN control can enable seamless satellite network operation during terrestrial network disruptions.
- Proposes a cooperative SDN control framework spanning terrestrial and space domains for intelligent traffic routing and AN switching decision.
- Synthesises insights from an extensive set of prior works on SDN-based traffic engineering, QoS provisioning, and integrated satellite–terrestrial networking.
- Lays out an agenda for future research by identifying key performance factors, algorithms, and mechanisms needed to realise the proposed SDN-based integration framework.
2. Traffic Transmission Architecture
3. Overview of 5G Technology
3.1. Evolution of 5G Terrestrial Network
3.2. Satellites in 5G and Beyond Networks
- A.
- Satellites and Their Roles in 5G and Beyond Networks
- B.
- Benefits of Integrated Satellite Terrestrial Networks
- C.
- Satellite Communication Use Cases
- i.
- Vision of Future 6G Network: Sixth-generation networks are poised to revolutionise connectivity, offering unparalleled speed, reliability, and scalability. These networks will serve as the backbone for a myriad of applications, ranging from smart cities to autonomous vehicles, ushering in an era of ubiquitous connectivity and unprecedented innovation.
- ii.
- Smart and Connected Vehicular Life in 6G: In the 6G era, vehicles will be seamlessly integrated into a connected ecosystem, communicating not only with each other but also with the surrounding infrastructure and pedestrians. This interconnectedness will pave the way for safer roads, optimised traffic flow, and enhanced passenger experiences.
- iii.
- Vehicle–Road–Human Integrated Network: The integration of vehicles, road infrastructure, and human interaction will form a cohesive network aimed at enhancing transportation efficiency, safety, and sustainability. Through advanced sensors, communication technologies, and AI algorithms, this network will enable real-time data exchange and decision-making, creating a more responsive and adaptive transportation system.
- iv.
- Vehicular Communications in 6G: Sixth-generation vehicular communications will transcend traditional boundaries, leveraging satellite communication networks alongside terrestrial infrastructure to deliver seamless connectivity in even the most remote or challenging environments. From backhaul to direct access, broadcast, and mobility, satellites will play a pivotal role in extending coverage and ensuring uninterrupted communication for vehicles on the move.
- v.
- Cloud, Fog, and Edge Computing: The convergence of cloud, fog, and edge computing will empower 6G networks with unprecedented computational capabilities, enabling real-time data processing, analytics, and decision-making at the network’s edge. This distributed computing paradigm will reduce latency, enhance privacy, and unlock new opportunities for edge-based applications and services.
- vi.
- Centralised and Distributed AI: AI will be at the heart of 6G networks, driving intelligent automation, optimisation, and decision-making across various domains. From centralised AI platforms orchestrating network resources to distributed AI algorithms running on edge devices, AI will enhance network efficiency, reliability, and adaptability, ushering in an era of autonomous networking and intelligent services.
- vii.
- Data Security and Privacy Protection: As connectivity proliferates and data volumes soar, robust security and privacy measures will be paramount in safeguarding sensitive information and preserving user trust. Sixth-generation networks will employ advanced encryption techniques, decentralised authentication mechanisms, and privacy-preserving technologies to ensure the confidentiality, integrity, and availability of data across the network.
- D.
- Challenges in Integration of Satellite with Terrestrial Networks
3.3. SDN and NFV Concepts for Programmable Infrastructure
4. Proposed Framework for Reliable SDN-Based ISTN for Real-Time Communication
- The assessment of the Reference Signal Received Power (RSRP) for both ANs interfaced with User Equipment 1 (UE-1) through its Nis is essential. If only one NI of UE-1 meets the RSRP threshold for the available radio access technology (RAT), UE-1 will automatically utilise that NI for data transmission. The RSRP can be measured based on the expression in (7) [75,76].
- 2.
- If both NIs of UE-1 meet the RSRP threshold of their respective RATs, UE-1 will transmit a control signal to the network requesting assistance with AN selection based on specific network criteria. Criteria such as latency, available bandwidth, jitter, and PLR may be considered.
- 3.
- The network will need to perform multi-attribute/criteria decision-making (MADM/MCDM) to select a suitable AN for UE-1 using a multi-objective function as depicted in (8) [77].
- 4.
- The network, aided by SDN controllers situated in both space and terrestrial domains, will cooperatively select the AN by evaluating network conditions along the path between UE-1 and UE-2.
5. Related Works on Foundational Concepts and Evidence Gaps
5.1. QoS Considerations in Satellite and Terrestrial Networks
5.2. Software-Defined Networking (SDN) Approaches for QoS-Based Traffic Steering and Routing
5.3. Protocol Consideration for Traffic Steering in SDN-Based ISTN
5.4. QoS-Based Traffic Steering and Data Offload Consideration for ISTN
5.5. Real-Time QoS and Link Assessment Mechanisms
5.6. Strategies and Algorithms Considerations for Access Network Selection
5.7. Distributed SDN Controller Architecture for Converged ISTN
6. Global Research Gaps
- Quality of Service (QoS) Frameworks for ISTN Environments: The importance of QoS considerations in integrated ISTN has been emphasised but there is currently no standardised QoS framework tailored specifically for ISTN environments. Therefore, there is a need for a unified QoS architecture that considers ISTN-specific factors like latency, jitter, reliability, and diverse link capacities across both satellite and terrestrial networks.
- Adaptive Traffic Engineering and Management: Mechanisms for dynamic traffic engineering that adapt in response to fluctuating network conditions owing to dynamic LEO satellite topologies are lacking. Thus, there is a need to explore joint optimal traffic distribution, routing, and load balancing across a heterogeneous ISTN link.
- Privacy-Preserving Traffic Analysis: While techniques like Deep Packet Inspection (DPI) enable traffic identification, they pose privacy risks. Hence, an alternative AI approach needs to be explored to balance between reliable traffic classifications and user privacy protections.
- Service Resilience and Continuity: Although studies demonstrated certain capabilities in disaster/failure scenarios, limitations persist in meeting 5G expectations for service availability. Therefore, advanced methods or policies are needed to guarantee resilient service continuity for all applications without compromising network availability for critical and emergency use cases.
- Efficient Resource Estimation and Management: Gaps exist in developing adaptive admission control, capacity estimation, and bandwidth management techniques specifically tailored for ISTN environments. Existing link measurement and modelling techniques in both wireless and wired environments need to be studied and adapted toward satellite channels.
- Energy Efficiency and Management: One of the many critical areas considered by standard organisations in the energy saving (ES) capability of a network. While the use of SDN/NFV technologies has helped in conserving energy for network infrastructure, there is need for more techniques to be investigated for an ISTN system.
7. Future Trends and Applications
8. Lessons Learned
- Resilience and Continuity: The investigation underscored the significance of guaranteeing service resilience and continuity within integrated networks, especially during disaster or failure scenarios. Advanced methodologies and policies are imperative to ensure resilient service continuity for all applications without compromising network availability for critical and emergency use cases. Techniques such as network redundancy, fast failover mechanisms, and dynamic rerouting can enhance resilience by ensuring that services remain available even in the event of network failures or disruptions. Continuity measures may include seamless handover mechanisms, session persistence, and backup communication paths to maintain connectivity and service availability during transitions or outages.
- Efficient Resource Management: The document identified gaps in the development of adaptive admission control, capacity estimation, and bandwidth management techniques tailored for integrated satellite–terrestrial networks. Efficient resource estimation and management are crucial for optimising network performance and ensuring seamless connectivity. Techniques such as dynamic spectrum allocation, load balancing, and traffic prioritisation can optimise resource usage and improve network efficiency. Adaptive algorithms that monitor network conditions in real-time and adjust resource allocation dynamically can address fluctuations in demand and maximise resource utilisation.
- Integration Challenges: Addressing technical challenges in designing and optimising network architectures that seamlessly integrate satellite and terrestrial components is essential. The joint exploitation of multiple paths and the utilisation of network coding techniques can enhance the performance of integrated systems. Challenges may include synchronisation issues, protocol interoperability, and coordination between satellite and terrestrial networks. Hybrid routing protocols, cross-layer optimisation techniques, and protocol translation mechanisms can help overcome integration challenges and improve system performance.
- Mobility and Edge Computing: Seamless mobility support and leveraging edge computing capabilities are critical for enabling low-latency and high-bandwidth applications in integrated networks. Offloading computing tasks to the edge can reduce latency and enhance the overall user experience. Mobility management protocols, such as Mobile IP and Proxy Mobile IPv6, facilitate seamless handovers between different access technologies and network domains. Edge computing platforms, such as cloudlet and fog computing, bring computing resources closer to the users, enabling faster processing and response times for latency-sensitive applications.
- Quality of Service Considerations: Real-time link assessment based on Quality of Service (QoS) metrics is essential for ensuring efficient and reliable communication in integrated networks. Traffic steering and switching within the user-plane connectivity model play a crucial role in selecting optimal Access Nodes (ANs) based on dynamic network conditions and application QoS requirements. QoS-aware routing protocols, admission control mechanisms, and traffic shaping algorithms ensure that network resources are allocated efficiently to meet application-specific QoS requirements. Techniques such as traffic prioritisation, packet scheduling, and Quality of Experience (QoE) monitoring enhance user satisfaction and improve overall network performance.
9. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Medium | Application | Degree of Symmetry | Data Rate (kbps) | Key Performance Parameters and Target Values | ||
---|---|---|---|---|---|---|
E2E One-Way Delay (ms) | Delay Variation Within a Cell (ms) | Information Loss (%) | ||||
Audio | Interactive voice | Two-way | 4–25 | <150 preferred [16] <400 limit | <1 ms | <3 FER |
Video | Video phone | Two-way | 32–384 | <150 preferred <400 limit Lip-synch: 100 | NA | <1 FER |
Data | Telemetry-two-way control | Two-way | <28.8 | <250 | NA | Zero |
Data | Interactive games | Two-way | <250 | NA | Zero | |
Data | Telnet | Two-way | <250 | NA | Zero |
S/N | Features | LEO | MEO | GEO |
---|---|---|---|---|
1. | Altitude | 500–2000 km [36] | 2000–35,780 km [43] | >35,780 km [43] |
2. | One-Way Latency | <30 ms [36,38] | 112 ms [44] | ≥250 ms [45] |
4. | Coverage/visibility period | ~20 min [46] | ~2 h | 24 h |
5. | Coverage area | 0.45% of earth’s surface at 30 deg inclination [36] | Several thousand kilometres in diameter per satellite | 1/3 of the earth’s surface |
6. | Speed | 7.6 km/s at 500 km altitude [36] | 3.07 km/s at 20,000 km altitude | Synchronous with earth’s rotational speed |
7. | Capacity | |||
8. | Design | Walker, Delta | Walker | Fixed |
9. | Application | Communications, scientific, weather monitoring | Navigation (GPS), observation, weather monitoring | Weather monitoring, communication, tracking |
10. | Examples | Starlink, Oneweb, Kepler, Telesat | O3b, mPOWER, Telstar | Inmarsat, ViaSat, SES |
S/N | Technique | Application | Advantage | Drawbacks |
---|---|---|---|---|
1. | Analytical Hierarchical Process (AHP) Habbal et al. [78] | Weighting and ranking. | Offers a way to check for judgement error by evaluating consistency index. Works with both objective and subjective criteria. | Requires pre-defined criteria weights provided by user/operator. Difficult to ensure consistency with increased number of elements. Pairwise comparisons result in lengthy subjective opinions for weight assignment if there are many criteria and alternatives. |
2. | Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) [78,79] | Ranking. | Scales well with objective measurable criteria. Exhibits a simple and rational way of choosing alternative closest to ideal solution. | Requires pre-defined criteria weights provided by user/operator. Exhibits ranking abnormalities. |
3. | Analytical Network Process (ANP) [80,81] | Weighting and ranking. | Offers a network of relationships among criteria, which leads to more reliable results. | Requires pre-defined criteria weights provided by user/operator. |
4. | Simple Additive Weighting (SAW) [82] | Ranking. | Simple and transparent. | Sensitive to attributes scaling and normalisation can adversely affect scores. |
5. | Fuzzy-AHP [83,84] | Weighting and ranking. | Considers the vagueness of judgement made in weight assignment. Can handle imprecise and uncertain information. | Computationally complex and time intensive. |
S/N | Technique | Measured Metric | Pros | Cons | SDN-Implemented |
---|---|---|---|---|---|
1. | Self-Loading Periodic Streams [87,88] | Available bandwidth | Non-intrusive, i.e., no increase in network utilisation or delay is induced. | Accuracy is dependent on variables like stream length. | No |
2. | Variable Packet Size (VPS) probing [89] | Available bandwidth, delay | Requires no prior knowledge of network path and requires control of only the source node. | Being an active method, it requires tests packet to be injected into the network while actual traffic is being transmitted. | Yes |
3. | Packet pair/train probing [90] | Link capacity | Simple and low overhead. Compensates for errors induced by revers cross traffic using SDN flow statistics. | Overhead [91] and accuracy is a trade-off based on chosen train length. Cross traffic interleaving probe packets can lead to inaccurate link capacity measurement. | Yes |
4. | LLDP-looping [92] | Latency | Minimises overhead by leveraging SDN controller as monitoring point. | Incurs failures caused by timestamping of probe packets. | Yes |
5. | PacketBurst [91] | Bandwidth | No | ||
6. | OpenNetMon [93] | Packet loss and delay | Exploits the OpenFlow features to measure per flow metrics without requiring additional hardware resources. | Incurred overhead due to injection of probe packets. | Yes |
7. | E2E SDN-based ABW measurement [94] | Available bandwidth | Obtains available bandwidth for any paths in real-time. Exploits OpenFlow messages for monitoring thereby reducing overhead. | Accuracy is limited to OpenFlow counter timestamps. | Yes |
S/N | Reference | SDN/NFV Implementation | Link QoS/Metric Measure | Satellite–Terrestrial Integration |
---|---|---|---|---|
1. | Lee and Park [95] | Yes | Yes | Yes |
2. | Zeydan and Turk [96] | No | Yes | Yes |
3. | Niephaus et al. [10] | Yes | Yes | Yes |
4. | Ravishankar et al. [38] | Yes | Yes | Yes |
5. | Li et al. [99] | Yes | Yes | Yes |
6. | Xu et al. [100] | Yes | No | Yes |
7. | Cola et al. [103] | Yes | Yes | No |
8. | Al-Najjar et al. [107] | Yes | Yes | No |
9. | Sato et al. [108] | Yes | Yes | Yes |
10. | Shu et al. [106] | Yes | Yes | No |
11. | Wang and Yu [101] | Yes | No | Yes |
12. | Ahuja et al. [77] | No | Yes | No |
13. | Bao et al. [102] | Yes | No | Yes |
14. | Curtis et al. [109] | Yes | Yes | No |
15. | Bi et al. [105] | Yes | No | Yes |
16. | Li et al. [112] | Yes | No | Yes |
17. | Wang et al. [48] | Yes | No | Yes |
18. | Boero et al. [5] | Yes | No | Yes |
19. | Guo et al. [97] | Yes | No | Yes |
20. | Niephaus et al. [98] | Yes | Yes | Yes |
21. | Di et al. [104] | No | No | Yes |
22. | Al-Najjar et al. [89] | Yes | Yes | No |
23. | Hossen and Jamalipour [111] | Yes | Yes | No |
24. | Giambene et al. [11] | Yes | Yes | Yes |
25. | Priscoli et al. [18] | No | Yes | No |
26. | Davy et al. [110] | No | Yes | No |
27. | Jain and Dovrolis [87] | No | Yes | No |
28. | Almadani et al. [114] | Yes | No | No |
29. | Yu et al. [113] | Yes | No | No |
30. | Bhardwaj and Panda [115] | Yes | No | No |
31. | Koulouras et al. [116] | Yes | Yes | No |
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Ayofe, O.A.; Okafor, K.C.; Longe, O.M.; Alabi, C.A.; Tekanyi, A.M.S.; Usman, A.D.; Musa, M.J.; Abdullahi, Z.M.; Agbon, E.E.; Adikpe, A.O.; et al. SDN-Based Integrated Satellite Terrestrial Cyber–Physical Networks with 5G Resilience Infrastructure: Future Trends and Challenges. Technologies 2024, 12, 263. https://doi.org/10.3390/technologies12120263
Ayofe OA, Okafor KC, Longe OM, Alabi CA, Tekanyi AMS, Usman AD, Musa MJ, Abdullahi ZM, Agbon EE, Adikpe AO, et al. SDN-Based Integrated Satellite Terrestrial Cyber–Physical Networks with 5G Resilience Infrastructure: Future Trends and Challenges. Technologies. 2024; 12(12):263. https://doi.org/10.3390/technologies12120263
Chicago/Turabian StyleAyofe, Oluwatobiloba Alade, Kennedy Chinedu Okafor, Omowunmi Mary Longe, Christopher Akinyemi Alabi, Abdoulie Momodu Sunkary Tekanyi, Aliyu Danjuma Usman, Mu’azu Jibrin Musa, Zanna Mohammed Abdullahi, Ezekiel Ehime Agbon, Agburu Ogah Adikpe, and et al. 2024. "SDN-Based Integrated Satellite Terrestrial Cyber–Physical Networks with 5G Resilience Infrastructure: Future Trends and Challenges" Technologies 12, no. 12: 263. https://doi.org/10.3390/technologies12120263
APA StyleAyofe, O. A., Okafor, K. C., Longe, O. M., Alabi, C. A., Tekanyi, A. M. S., Usman, A. D., Musa, M. J., Abdullahi, Z. M., Agbon, E. E., Adikpe, A. O., Anoh, K., Adebisi, B., Imoize, A. L., & Idris, H. (2024). SDN-Based Integrated Satellite Terrestrial Cyber–Physical Networks with 5G Resilience Infrastructure: Future Trends and Challenges. Technologies, 12(12), 263. https://doi.org/10.3390/technologies12120263