Toward a Flexible and Reconfigurable Broadband Satellite Network: Resource Management Architecture and Strategies
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1 Toward a Flexible and Reconfigurable Broadband Satellite Network: Resource Management Architecture and Strategies Yu Wang Xidian University October 21, 2016
2 Outline Introduction Background Knowledge Existing Satellite Network Architecture Software Defined Networking and Network Virtualization FRBSN Architecture Resource Management Architecture Functional Architecture Multi dimensional Resource Representation Resource Allocation Strategy and Performance Evaluation Conclusion 2
3 Introduction Applications of Broadband Satellite Networks (BSNs) Navigation, communication/relaying, Earth observation, emergency rescue, Drawbacks of traditional BSNs Lacks interactions and cooperation: Ocean and Resource satellite series are utilized separately Hard to reconfigure: Coupled control and data plane, customized legacy function Cannot adapt to traffic increase and new space mission Evolutions Single satellite Satellite constellations Integrating multiple heterogeneous satellite networks SDN, NFV and NV (use cases) Unified framework for efficient resource sharing and management for BSN?? 3
4 Background Knowledge Existing Satellite Network Architecture A Network Operations Control Center (NOCC) mission planning, network control and resource management. Multiple Ground Stations (GS) (1) different types of GS, communicate with satellites and perform tracking and upload operations; (2) a strong set of local control functions Satellites in the space segment: bent pipe or Fig.1: An example BSN architecture. onboard processing. 4
5 Background Knowledge Main Design Principles Mission dependent protocol The standard protocol running on each satellite system is greatly coupled with a certain space mission, and may not be compatible with other protocols. Dedicated resource usage The current satellite system is strictly customized. Certain GSs, despite being idle, cannot be shared with others Pre planned mission The missions, as well as the resource allocation strategies, executed by a system, e.g., data relay satellite system, are generally planned by several days in advance. 5
6 Background Knowledge Software Define Networking (SDN) Decoupling the control plane and data plane Network Virtualization (NV) Decoupling the roles of ISPs into infrastructure providers (InP) and service providers (SP) Combined together, SDN and NV can enhance the network openness, programmability and interoperability. 6
7 Background Knowledge FRBSN architecture Infrastructure Layer (InL) Virtual Network Layer (VNL) Application Layer (AL) Network Configuration Controller (NRC) Open Issues regarding FRBSN Security Fine grained and reliable network control Software defined payloads onboard Resource management Fig.2: Logical view of FRBSN reference architecture. 7
8 Resource Management Architecture Functional Architectures : resource status collection Fig.3: (a) An example FRBSN architecture; (b) functions of each network device. 8
9 Resource Management Architecture Challenges in Multidimensional Resource Representation Dynamic network topology Due to orbit related network dynamics, resource availability varies continuously and periodically Multi dimensional resource space Various resources, such as transmission resources, storage resources, observation resources, how to precisely represent them and dictate the relationship among them? 9
10 Resource Management Architecture Basic principles using TVRG A unified two dimensional time space basis, wherein vertices correspond to replicas of satellites, GSs, NOCC and observing targets in each time slot. Edges: corresponding resource availability, unify in terms of bits that can be transmitted, stored or observed. Path: reveal resource correlations: The number of bits that can be delivered by a possible resource combination. 10
11 Resource Management Architecture An example TVRG Observing targets, LEO satellites, data relay satellites, NOCC Fig.4: An example Time varying resource graph (TVRG). 11
12 Resource Management Strategy based on TVRG Objective e.g., Network utility maximization Multi dimensional resource Flow conservation Observation resource Transmission resource Storage resource Solution MILP optimization problems on graph Approximate online solutions Fig.5: Modeling based on TVRG. 12
13 Performance Evaluation Optimal resource allocation Three different schemes: ORA, NCT CO, NCT NCO Fig.5: (a) Throughput performance of different schemes with varying buffer size; (b) Resource utilization ratio. 13
14 Conclusion Addressed the issue of flexible and reconfigurable networking techniques for BSN. The resource management framework inside FRBSN was studied. We proposed a novel time evolving resource graph to characterize the multi dimensional resources in BSN. Furthermore, the optimal resource allocation mechanism was put forward to achieve an efficient utilization of network resources. In summary, we expect that this study could open up a new research direction for the design of next generation BSN. 14
15 Reference [1]T.Pecorella,L.S.Ronga,F.Chiti,S.Jayousi,andL.Franck, Emergency Satellite Communications: Research and Standardization Activities, IEEE Commun. Mag., vol. 53, no. 5, pp , May [2] Schrogl Kai Uwe et al., Handbook of Space Security, Springer New York, [3] B. Astuto, A. Nunes et al., A Survey of Software Defined Networking: Past, Present, and Future of Programmable Networks, IEEE Commun. Surveys & Tutorials, [4] T. Rossi et al., Future Space based Communications Infrastructures based on High Throughput Satellites and Software Defined Networking, in Pro. IEEE ISSE, pp , [5] L. Bertaux et al., Software Defined Networking and Virtualization for Broadband Satellite Networks, IEEE Commun. Mag., vol. 53, no. 3, pp , Mar [6] Z. Tang, B. Zhao, W. Yu, Z. Feng, and C. Wu, Software Defined Satellite Networks: Benefits and Challenges, in Pro. IEEE ComComAp, pp , Oct [7] B. Cao et al., Software Defined Virtual Wireless Network: Framework and Challenges, IEEE Network, vol. 29, no. 4, pp. 6 12, Feb [8] C. Jiang et al., Security in Space Information Networks, IEEE Commun. Mag., vol. 53, no. 8, 15 pp , Aug
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17 Thanks!!! Q&A 17
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