Software defined Vehicular Network Challenges & Opportunities. Weisen Shi October 3, 2016

Transcription

1 Software defined Vehicular Network Challenges & Opportunities Weisen Shi October 3, 2016

2 Outline Backgrounds Issues in VANET Software defined networking (SDN) Software defined Vehicular Network(SDVN) Frameworks of SDVN Challenges & Opportunities Challenges in SDVN Research topics in SDVN Summary 2

3 Issues in VANET Interworking Heterogeneous V2X networks (DSRC, LTE V, 60GHz WiFi, WhiteFi, etc.) Different scenarios require different technologies ( DSRC for sparse scenario, delay sensitive Apps; LTE for high density, delay insensitive Apps[1] ) Adaptive network reconfiguration Rapidly switching network parameters according to topology changes Resource Allocation Allocating network resources for Apps with different priorities/requirements 3

4 Software Defined Networking New Network Paradigm Separation of control and data planes Logical centralized control Network programmability OpenFlow as southbound API Advantages Abstracting infrastructures functions for Apps Centralized control enables rapid reconfiguration of network Allocating network resources in dynamical ways 4

5 Software Defined Vehicular Network Advantages of SDN match Issues in VANET SDN has been introduced to Carrier networks and WiFi networks [2][3] Software Defined Vehicular Network (SDVN) is proposed in recent years [4 9] 5

6 Frameworks & Progresses Name Year Summary Software defined VANET [4] 2014 Pioneer work introducing SDN structure into VANET Software defined Networking for RSU Cloud [5] Soft Defined Heterogeneous Vehicular Network (SERVICE) [6] 2015 Implementing SDN for communication among RSUs 2015 Implementing SDN into Heterogeneous VANET by the help of Cloud Radio Access Networks (Cloud RAN) SDVN [7] 2016 Proposed an overall SDVN framework Delay Optimal Virtualized Radio Resource Scheduling in SERVICE [8] Control Plane Optimization in Software defined VANET [9] 2016 Radio Resource Scheduling based on SERVICE 2016 A control plane optimization algorithm based on the Softwaredefined VANET in [4] 6

7 Case 1: SDN for Wired Part Software defined Networking for RSU Cloud [5] Implementing SDN in RSU Cloud Keeping traditional DSRC for V2V & V2I 7

8 Case 2: Software Defined VANET Software defined VANET [4] DSRC for data plane communication LTE for control plane communication SDN node for each vehicle & RSU 8

9 Case 2: Software Defined VANET Control Modes of Software defined VANET 9

10 Case 3: SDVN Software defined Vehicular Network [7] Mobile & stationary data plane Topology manager & status manager in control plane Various Apps 10

11 Case 4: SERVICE SERVICE (Soft defined heterogeneous VehICular network) [6] Cloud RAN & RRH enabled data plane (infrastructure layer) Hierarchical control plane Virtualizing network function to Apps 11

12 Case 4: SERVICE 12

13 Challenges Inefficient control for high mobility High mobility of vehicles causes dynamic topology & unstable wireless channels for SDVN Hard for controllers to collect vehicles & network information in real time Delay the distribution of commands from controllers. Current Solutions: SERVICE implements RRH & hierarchical control layer [6] [7] utilizes predictions results of vehicles behaviors 13

14 Challenges Interworking gaps among heterogeneous networks Coexisting of heterogeneous V2X networks requires efficient interworking mechanisms. Lacking standardized Eastbound/Westbound APIs Lacking Northbound APIs for Vehicular Apps. Current Solutions: Customizing OpenFlow? Introducing ideas of NFV to abstract infrastructure layer [7] 14

15 Challenges To what extend the VANET will be software defined Transforming whole network into SDN structure is questionable and inefficient Only using SDN in wired part nearly change nothing Should figure out which control intelligences could be decoupled from data plane, which could be remained. Current Solutions:? 15

16 Opportunities Network slicing in SDVN Different Apps require different topology & network resources [7] SDN enables efficient network slicing in a dynamic way 16

17 Opportunities NFV in SDVN Controllers virtualize network function to Apps through Northbound API Adjusting OpenFlow to facilitate heterogeneous networks interworking Introducing a Hypervisor between data plane and OpenFlow API. Hypervisor handles interworking of heterogeneous networks and abstracts a seamless network topology for OpenFlow to Software define SDVN Hypervisor 17

18 Opportunities Improving network resource utilization Adaptive network reconfiguration according to scenarios SDVN frameworks design for vehicular environment Control algorithms design for specific Apps Security issues in SDVN 18

19 Summary Advantage of SDN match issues in VANET Initial SDVN frameworks have emerged High mobility & interworking issues are vital challenges Interesting environment for future SDN research Long way before real world implementation 19

20 Reference [1] Abboud, Khadige, Hassan Omar, and Weihua Zhuang. "Interworking of DSRC and Cellular Network Technologies for V2X Communications: A Survey." [2] Asensio, A., et al. "Carrier SDN for flexgrid based inter datacenter connectivity." th International Conference on Transparent Optical Networks (ICTON). IEEE, [3] Schulz Zander, Julius, et al. "Programmatic orchestration of wifi networks."2014 USENIX Annual Technical Conference (USENIX ATC 14) [4] Ku, Ian, et al. "Towards software defined VANET: Architecture and services."ad Hoc Networking Workshop (MED HOC NET), th Annual Mediterranean. IEEE, [5] Salahuddin, Mohammad Ali, Ala Al Fuqaha, and Mohsen Guizani. "Software defined networking for rsu clouds in support of the internet of vehicles." IEEE Internet of Things Journal 2.2 (2015): [6] Zheng, Kan, et al. "Soft defined heterogeneous vehicular network: architecture and challenges." arxiv preprint arxiv: (2015). 20

21 Reference [7] He, Zongjian, Jiannong Cao, and Xuefeng Liu. "Sdvn: Enabling rapid network innovation for heterogeneous vehicular communication." IEEE Network(2016): 3. [8] Q. Zheng; K. Zheng; H. Zhang; V. C. M. Leung, "Delay Optimal Virtualized Radio Resource Scheduling in Software Defined Vehicular Networks via Stochastic Learning," in IEEE Transactions on Vehicular Technology, vol.pp, no.99, pp.1 1. [9] H. Li; M. Dong; K. Ota, "Control Plane Optimization in Software Defined Vehicular Ad Hoc Networks," in IEEE Transactions on Vehicular Technology, vol.pp, no.99, pp

22 Thanks 22

23 Q & A 23