Virtualization in Wireless Networks

Transcription

1 ORCA-PROJECT.EU Virtualization in Wireless Networks Jonathan van de Belt, Yi Zhang CONNECT, TCD CROWNCOM 2018 TUTORIAL Gent ORCHESTRATION AND RECONFIGURATION CONTROL ARCHITECTURE

2 Why use virtualization? Virtualization is crucial for future networks New services Increased flexibility and dynamicity Higher resource efficiency Faster technology development and deployment Who is developing (wireless) network virtualization? Academia 6000 papers on IEEE, many testbeds Industry AT&T, Deutsche Telekom, BT, Cisco, +++ Standards bodies 3GPP, IEEE 802.1Q ORCA-PROJECT.EU 2

3 Challenges for wireless virtualization What does virtualization mean in a wireless context? Are there different types of virtualization? How do we implement virtualization in wireless networks? How do we assign virtual resources? Can we develop metrics? What are the costs? What applications benefit? What are the regulatory impacts? and many more ORCA-PROJECT.EU 3

4 Need for a definition/theory Existing definitions of wireless virtualization are not clear Defined in terms of purpose, rather than a process E.g. business models, efficiency ORCA-PROJECT.EU 4

5 Need for a definition/theory But how does this explain virtualization? How do we implement virtualization? How does this map to existing technologies? What are the research challenges? A precise theory allows: Specificity and a common understanding Identification of research gaps Modelling and implementation ORCA-PROJECT.EU 5

6 Outline 1. Explain Virtualization theory using Abstraction/Representation theory 2. Describe virtualization in wireless networks using the theory 3. Network Function Virtualization (Yi Zhang) 4. Wireless-optical integration (Yi Zhang) 5. Wireless link virtualization implementation & experiments potential research directions ORCA-PROJECT.EU 6

7 Housekeeping for hands-on part 1. Install GNU Radio sudo apt-get install gnuradio gnuradio-dev (on linux) or build from source (long process!) 2. Download MySVL out-of-tree module git clone 3. Build MySVL mkdir build && cd build cmake../ make sudo make install ORCA-PROJECT.EU 7

8 Abstraction/Representation theory

9 Two domains... The physical domain - physical objects in the real world - you live there The abstract domain - realm of concepts, mathematics, ideas logic language pictures ORCA-PROJECT.EU 9

10 Connecting the two domains Representation - relationship R between objects in the physical domain and the abstract domain e.g. a switch represents binary number Generalized as p and m p Not a mathematical function! Arbitrary modelling convention D. C. Horsman, Abstraction/Representation theory for heterotic physical computing, Philosophical Transactions of the Royal Society of London, vol. 373, no. 2046, 2015 ORCA-PROJECT.EU 10

11 Physical and abstract evolution Evolution or moving from one state to another in physical domain: H(p): p p' in abstract domain: C(m p ): m p m' p examples? If m p m p then R is a faithful abstract representation D. C. Horsman, Abstraction/Representation theory for heterotic physical computing, Philosophical Transactions of the Royal Society of London, vol. 373, no. 2046, 2015 ORCA-PROJECT.EU 11

12 Instantiation Instantiation R: abstract domain to physical domain e.g. binary number as voltages Inverse of representation Very hard to find ~ requires faithful abstract representation Writing example D. C. Horsman, Abstraction/Representation theory for heterotic physical computing, Philosophical Transactions of the Royal Society of London, vol. 373, no. 2046, 2015 ORCA-PROJECT.EU 12

13 The compute cycle? D. C. Horsman, Abstraction/Representation theory for heterotic physical computing, Philosophical Transactions of the Royal Society of London, vol. 373, no. 2046, 2015 ORCA-PROJECT.EU 13

14 Levels of representation Abstract objects can represent (and instantiate) other abstract objects Multiple levels of representation in abstract domain Abstract Domain Physical Domain ORCA-PROJECT.EU 14

15 Levels of representation ORCA-PROJECT.EU 15

16 Levels of representation Multiple levels of representation in abstract domain Reuse existing instantiation in physical domain ORCA-PROJECT.EU 16

17 Hardware and software Representation levels lead to new definition of HW/SW HW: compute cycle between abstract and physical SW: compute cycle in abstract domain ORCA-PROJECT.EU 17

18 Virtualization theory

19 Virtualization theory Virtualization is a mapping in the abstract domain And within one level of representation ORCA-PROJECT.EU 19

20 Virtualization theory Use virtual resources in different manner to real resources E.g. second level of representation ORCA-PROJECT.EU 20

21 Virtualization theory: mapping One-to-one Many-to-one One-to-many Many-to-many Representation Level n Virtual Resources Real Resources ORCA-PROJECT.EU 21

22 Virtualization theory: recursion Users perceive virtual resources as real can virtualize again Recursion Multiple instances Virtual and real depend on context Recursion is always possible in theory requirement for virtualization Virtual Resources Representation Level n Instance two Instance three Real Virtual or Virtual Resources? Instance one Real Resources ORCA-PROJECT.EU 22

23 Virtualization theory: sub-problems Two sub-problems: isolation and embedding Isolation maintaining independence between virtual resources Isolate along one or more dimensions (e.g. time) Embedding mapping virtual to real resources Depends on the isolation problem ORCA-PROJECT.EU 23

24 Virtualization theory: the definition Virtualization is a resource mapping in abstract domain within any representation level abstract resources are limited by underlying physical resources (real resources) after virtualization, abstract resources can be larger or smaller (virtual resources) virtual resources are independent and allocated to multiple users virtualization can always be recursive. ORCA-PROJECT.EU 24

25 Virtualization theory: an example Each concept in the theory applies to virtual memory See handout Concept Physical resources Abstract resources Mapping Isolation Embedding Recursion Use in virtual memory Disk, RAM Memory Space One-to-many Address space Paging, segmentation Possible, but not very useful Provides some validation of theory ORCA-PROJECT.EU 25

26 Virtualization in Networks

27 Computer functions in HW and SW Hardware Software Need all functions in SW to be able to virtualize ORCA-PROJECT.EU 27

28 Node virtualization Wireless networks consist of nodes and links some of the links can be wireless Virtualize nodes and links independently Node virtualization: each function must be virtualized first Processing Storage I/O ORCA-PROJECT.EU 28

29 Link virtualization Wired link virtualization Consists of I/O virtualization (e.g. NIC) and link virtualization Wireless link virtualization Similarly, I/O (RF front-end) and link virtualization ORCA-PROJECT.EU 29

30 Network virtualization Virtualize both nodes and links to create virtual networks requires each component to be virtualized For simplicity, assume I/O virtualization (NIC) ORCA-PROJECT.EU 30

31 Software defined networking Prerequisite to virtualization of switches Physical Domain Physical Domain ORCA-PROJECT.EU 31

32 Network function virtualization Form of server virtualization, specific to network functions ORCA-PROJECT.EU 32

33 Wireless network virtualization Virtualize both nodes and links to create virtual networks requires each component to be virtualized Assume I/O virtualization ORCA-PROJECT.EU 33

34 Wireless link virtualization From here, we focus on wireless link virtualization (WLV) Remember link virtualization required for network virtualization Main obstacle to wireless network virtualization is WLV Can reuse existing techniques from network virtualization after solving WLV But first... Yi talks about NFV and wireless-optical integration ORCA-PROJECT.EU 34

35 Wireless Link Virtualization

36 WLV: overview 1. Identify state of the art and research gaps Benefiting from the theory Identify what is virtualized and if it is virtualization Consistent comparison of techniques 2. One research gap: lack of implemention (Isolation problem) Design and test a WLV implementation Enables the analysis of other research gaps. 3. Examine the Embedding problem 4. Remaining research challenges ORCA-PROJECT.EU 36

37 WLV: survey Test to determine if techniques are virtualization Use the recursive property of virtualization Techniques are always a mapping of input resources to output resources Input resources are the resources that techniques can allocate (i.e. real) Output resources are the resources the users receive (i.e. virtual) Output Resources Input Resources ORCA-PROJECT.EU 37

38 WLV: recursive test Recursive test to determine if a technique is virtualization Check the units of the input and output resources If they are the same, the technique is recursive Example: a technique for which the input is spectrum resources (in Hertz) and the output given to users is also spectrum resources (also in Hz) is considered recursive Input Resources Recursive Test Result Output Resources ORCA-PROJECT.EU 38

39 WLV: applying the test... Techniques that passed the test Also learn representation level isolation mapping embedding (separate table) ORCA-PROJECT.EU 39

40 WLV: classification of techniques In addition to determining virtualization, recursive test provides classification Units determine representation level Spectrum level (Hz) Information level (Mbit/s) Also determines isolation E.g. Frequency, time, space, etc. Identify mapping and embedding separately ORCA-PROJECT.EU 40

41 WLV: survey insights 1 Mix up levels 3 Lack of isolation 4 Only 2 Lack of isolation and embedding combined ORCA-PROJECT.EU 41

42 Implementing WLV

43 Acting on the insights One of the gaps: lack of spectrum level implementation Implement on SDR Testbed ORCA-PROJECT.EU 43

44 Software defined radio Flexible, reconfigurable radio processing on GPP IQ samples to radio front-end Transmitter SDR Tx USRP Common paradigm Receiver SDR Rx USRP and Universal Software Radio Peripheral (USRP) ORCA-PROJECT.EU 44

45 Design principles 1. Reuse existing implementations as much as possible (open-source) 2. Many-to-many 3. Recursive 4. Separation of isolation and embedding Use any isolation with any suitable embedding 5. Flexible 6. Simple 7. Cheap ORCA-PROJECT.EU 45

46 Design process The Spectrum Virtualization Layer (SVL) The Many-to-many Spectrum Virtualization Layer (MySVL) ORCA-PROJECT.EU 46

47 Resulting design ORCA-PROJECT.EU 47

48 Resulting design ORCA-PROJECT.EU 48 48

49 Frequency reassignment ORCA-PROJECT.EU 49

50 Hands-on experiments

51 Example 1: proof of concept ++ Example 1a: contiguous spectrum mapping Example 1b: non-contiguous spectrum mapping Example 1c and 1d ORCA-PROJECT.EU 51

52 Example 2: recursion ORCA-PROJECT.EU 52

53 Example 3: many-to-many ORCA-PROJECT.EU 53

54 Example 4: real channel conditions Effects of noise, frequency offset, time offset, etc. Need to add guard bands! ORCA-PROJECT.EU 54

55 Example 4: real channel conditions Effects of noise, frequency offset, time offset, etc. Need to add guard bands! Non-contigous spectrum easily broken! Due to fft window misalignment ORCA-PROJECT.EU 55

56 Example 5: add synchronization Complex Hermitian sequence with good autocorrelation properties for synchronization. Preamble detection at the receiver. Incoming samples are crosscorrelated with above sequence. Spike above a threshold is the start of a frame. ORCA-PROJECT.EU 56

57 Example 6: synchronization with MySVL Now non-contiguous spectrum can be received correctly Disclaimer: can't replicate channel conditions properly in the hands-on example Not simulating time offset accurately compared to real world conditions ORCA-PROJECT.EU 57

58 Virtual resource embedding

59 2D knapsack embedding Static embedding virtual resources allocated once Dynamic embedding re-embed existing virtual resources 2D problem for us Frequency and Time isolation Knapsack problem ORCA-PROJECT.EU 59

60 2D dynamic knapsack embedding Optimal 2D knapsack problem with priorities Static and dynamic Heuristic Static Karnaugh Dynamic Karnaugh Dynamic Greedy ORCA-PROJECT.EU 60

61 Results Dynamic embedding increases flexibility and resource efficiency reduces virtual resource request rejections ORCA-PROJECT.EU 61

62 Embedding use-case: Safety operator Virtual Public Safety operator and virtual commercial operator requesting resources Normal and emergency (timeslots ) operation Different types of traffic: voice, video, message ORCA-PROJECT.EU 62

63 Embedding use-case: Safety operator Virtual Public Safety operator and virtual commercial operator requesting resources Normal and emergency operation Different types of traffic: voice, video, message ORCA-PROJECT.EU 63

64 Research Challenges

65 Research Challenges Comparison of embedding techniques New embedding techniques Dynamic and reconfigurable virtualization Predict, discover, request, use, release resources How isolation affects embedding (1D, 2D, 3D + contiguous vs. noncontiguous, etc.) Isolation + embedding for different scenarios Comparison of spectrum vs information level for different scenarios and use-cases Integrate with node virtualization (E2E network virtualization) Harder ORCA-PROJECT.EU 65

66 Comparing embedding techniques Metrics Rejection rate of virtual resource requests Resource efficiency Complexity Latency Reliability/Isolation New algorithms Heuristic, optimization, auction, etc. ORCA-PROJECT.EU 66

67 Dynamic embedding Dynamic vs Static Reconfigure existing mapping Add/remove virtual resources Asynchronous use of virtual resources Partially solved (Colleague Joao working on it) ORCA-PROJECT.EU 67

68 Virtual resource use cycle Full virtualization cycle: prediction discovery request allocate release ORCA-PROJECT.EU 68

69 How isolation affects embedding Fully isolated, or can overlap? Dimensions used Overhead of isolation Granularity of isolation Illusion of real resource Paging vs segmentation Combination? ORCA-PROJECT.EU 69

70 Virtualization for different scenarios Traffic services with different requirements Suitable methods of virtualization Narrowband Bandwidth Broadband Isolation dimension(s) Bursty Data Transmission Continuous Granularity Embedding techniques Short Low Propagation Latency Long High Static/Dynamic Low Reliability High ORCA-PROJECT.EU 70

71 Spectrum vs information level Spectrum level More flexibility/customization Latency, reliability? Higher spectrum efficiency Adapt to channel conditions Information level Less complex Easier to implement Easier integration with wired ORCA-PROJECT.EU 71

72 End-to-end network virtualization End-to-end Slicing All network resources virtualized first Combine NFV, SDN, and SDR through orchestrator Potential for UE virtualization? ORCA-PROJECT.EU 72

73 End-to-end network virtualization Orchestrator of Orchestrators ORCA-PROJECT.EU 73

74 Conclusions

75 Why did we need a theory? Enables us to tackle research challenges With specificity: clear analysis and results Theory Vague Systematic & Specific ORCA-PROJECT.EU 75

76 THANK YOU FOR YOUR ATTENTION ORCA-PROJECT.EU This project received funding from the European Union s Horizon2020 research and innovation programme under grant agreement No

77 Security example ORCA-PROJECT.EU 77