Multi-layer resource management in ICN

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1 Multi-layer resource management in ICN M.J. Reed School of Computer Science and Electronic Engineering, University of Essex, UK PURSUIT/COMET Workshop

2 Outline 1 Introduction 2 PURSUIT (PSIRP) architecture 3 ICN: real deployment 4 Examples: resource control; resilience 5 Conclusion

3 Introduction ICN brings new possibilities: Better match between technology/users/providers - exploring and improving the tussle

4 Introduction ICN brings new possibilities: Better match between technology/users/providers - exploring and improving the tussle some traditional network features in new ways

5 Introduction ICN brings new possibilities: Better match between technology/users/providers - exploring and improving the tussle some traditional network features in new ways some new techniques for traditional networks

6 Introduction ICN brings new possibilities: Better match between technology/users/providers - exploring and improving the tussle some traditional network features in new ways some new techniques for traditional networks Why multi-layer? ICN is a grand new scheme - but we will still have bit-pipes Operators will still want good return on their investments New architecture: new traffic engineering/resource management...

7 High level view of PURSUIT architecture Rendezvous Pub. 4 Topology Manager 5 Packet switched using BF Data Sub Data Alternative path with different BF Major functions: Rendezvous, topology management, forwarding

8 Forwarding function A wide variety of strategies possible Assumed implementation: line speed publish-subscribe inter-networking (LIPSIN): source routing constructed from Bloom filter Bloom filter Creation ID ORed with ID ORed with ID Resulting BF Testing for membership ID ANDed with BF Matches ID ID ANDed different BF No match ID 1

9 LIPSIN forwarding Pub. Sub.

10 LIPSIN forwarding Pub Sub

11 LIPSIN forwarding Rendezvous Pub Sub

12 LIPSIN forwarding Rendezvous Topology Manager Pub Sub

13 LIPSIN forwarding 1 Rendezvous Topology Manager Pub Sub

14 LIPSIN forwarding Rendezvous 1 2 Topology Manager Pub Sub

15 LIPSIN forwarding Rendezvous Topology Manager Pub Sub

16 LIPSIN forwarding Rendezvous Topology Manager Pub Sub

17 LIPSIN forwarding Rendezvous Pub Topology Manager 5 Packet switched using BF Data Sub

18 LIPSIN forwarding Rendezvous Pub Topology Manager 5 Packet switched using BF Data Sub Data Alternative path with different BF

19 ICN: real deployment Deployment in real networks mixture of optical layer and electronic layer: both need management grooming of packet switched in circuit switched optimisation of routing and wavelength allocation resilience requirements inter-domain separation vs transparent end-to-end forwarding Still need traffic engineering optimise use of network resources for operator s benefit provide mechanisms to meet customer s needs (SLA, QoS)

20 Multilayer-network RV TM Pub Control Signal Sub EN 1 EN 2 EN 3 Electronic Layer ON 1 ON 3 Op,cal Layer ON 2

EN 1 EN 3 Sub 4 4 4 4 3 3 3 3 2 2 1 1 ON 1 Path

21 Multilayer-network: controlled by ICN RV TM Control Plane Pub OXC Pub OXC Sub 1 OXC Sub 3 EN 1 EN 3 Sub ON 1 Path ON 3 Data Plane Path ON 2

22 Example resource problem Allocate traffic x for demands d D along paths p such that the minimum free capacity on the most congested link Γ is maximised. This has a formal problem representation...

23 Example resource problem Allocate traffic x for demands d D along paths p such that the minimum free capacity on the most congested link Γ is maximised. This has a formal problem representation... Multicommodity flow with minimum congestion (MFMC) max(γ L ) subject to x(p) u(e)(1 Γ L ) e E P e:e p x(p) d j d j D p P j

24 Pictorial representation of TE goal - shortest path solution u x = 10 3 = 7 x 3 = 6 x 1 = 3 u x = = 1 Γ = 1 x 2 = 5 u x = 10 5 = 5 For all links capacity u = 10

25 Pictorial representation of TE goal - optimal MFMC solution u x = 10 1 = 9 x 3 = 6 x 1 = 3 x 1a = 2 x 1b = 1 u x = = 3 Γ = 3 x 2 = 5 u x = = 3 For all links capacity u = 10

26 Pictorial representation of TE goal - optimal integer MFMC solution x 3 = 6 x 1 = 3 u x = 10 6 = 4 x 2 = 5 u x = = 2 Γ = 2 For all links capacity u = 10

27 Flows in ICN?

28 Flows in ICN? An absurdity? Yes: Most ICN/CCN approaches avoid flow based models Information items are individual units (or small parts of items) Caching and publish/subscribe semantics do not a fit flow model

29 Flows in ICN? An absurdity? Yes: Most ICN/CCN approaches avoid flow based models Information items are individual units (or small parts of items) Caching and publish/subscribe semantics do not a fit flow model An absurdity? No: The information items will be transported over some mechanism that does have a flow e.g. optical network. We can choose: ignore the flow based mechanism: dumb overlay approach integrate ICN with the underlying flow based mechanism. Latter approach allows us to rethink traffic engineering.

30 Probabilistically assign forwarding IDs to paths u x = 10 1 = 9 x 3 = 6 A x 1 = 3 x 1a = 2 x 1b = 1 Path 1 u x = = 3 Γ = 3 x 2 = 5 u x = = 3 Path 2 B For all links capacity u = 10 PUB/SUB between A and B: TM assigns P=1/3 for Path 1, P=2/3 for Path 2

31 Shortest Path (Dijkstra) compared with MFMC 1.0 Fraction of free capacity, ΓS, for SPR Optimal fraction of free capacity, Γ F, using MFMC Mean of ten results Error bars: highest=best, lowest=worst Dotted line is the optimal x-scale: 1 means no traffic, 0 means no free capacity in MFMC

32 Integer flow MFMC compared to MFMC (fractional flows) 1.0 Fraction of free capacity, ΓI, for IMFMC Mean of ten results Error bars: highest=best, lowest=worst Dotted line is the optimal x-scale: 1 means no traffic, 0 means no free capacity in MFMC Optimal fraction of free capacity, Γ F, using MFMC

33 State comparison between ICN and IP/MPLS for MFMC Mean of maximum switching state in a forwarder Number of vertices Method MPLS LIPSIN MPLS state: grows N 2 and requires state to be controlled with signalling; per-packet/per-flow path allocation needed at edge router LIPSIN state: equal to the number of outgoing links and is not updated; allocation of packets much simpler than MPLS.

34 Multilayer ICN control Domain RV/TM 5 Publish Pub 4 Packet layer Path info Packet TM 3 OXC lightpath info OXC TM 7 FId Info sent 1 Traffic monitoring Packet Forwarder 6 Subscribe Sub Packet layer OXC layer 2 Configure lightpaths OXC

35 Resilience Traditional circuit switched resilience still needed we use the ICN layer to perform this function But new possibilities come with the anycast nature of ICN

36 Resilience Traditional circuit switched resilience still needed we use the ICN layer to perform this function But new possibilities come with the anycast nature of ICN Anycast vs traditional

37 Resilience Traditional circuit switched resilience still needed we use the ICN layer to perform this function But new possibilities come with the anycast nature of ICN Anycast vs traditional with topology formation they become the same...

38 Resilience Traditional circuit switched resilience still needed we use the ICN layer to perform this function But new possibilities come with the anycast nature of ICN Anycast vs traditional with topology formation they become the same... We can now have information resilience in addition (or instead of) network resilience

39 Resilience Traditional circuit switched resilience still needed we use the ICN layer to perform this function But new possibilities come with the anycast nature of ICN Anycast vs traditional with topology formation they become the same... We can now have information resilience in addition (or instead of) network resilience Information resilience can be applied recursively to solve resilience of the underlying functions such as Rendezvous and Topology Formation.

40 Resilience example Scenario Ultra-high video dissemination e.g. to cinemas Informa:on Graph Publish Movie X Subscribe to Movie X Movie X Sub Publish Movie X Pub 2 TM/RV Pub 1 Packet Layer Circuit Layer ON 1 ON 3

41 Conclusion ICN still needs to inter-operate with lower layers a multi-layer topology. With new architectures traditional functions can be revisited The PURSUIT/PSIRP ICN model allows fractional flows to be implemented with no added cost in network state - new optimisation is possible. New resilience features are possible see demonstration later...

42 Rendevous (RV) function Information items allocated fixed length Rendevous IDs (RIDs) RIDs reside within hierarchical scopes (SIDs) Concatenation of SIDs and RIDs uniquely define items (statistically unique) SID=20 SID=55 RID=23 SID=101 SID=55 Publishers (or subscribers) responsible for creating the IDs IDs may be algorithmically generated using application logic RV matches publishers and subscribers to SIDs/RIDs RV may be host/domain local or distributed

43 Topology management (TM) function General operation Manages delivery, may be distributed, centralised, or hierarchical Rendezvous function sends publish/subscribe start requests to TM TM finds best publisher ( anycast ) and best delivery mechanism Assumed for this paper centralised TM for each service provider domain only intra-domain considered inter-domain handled by peer collaboration between TMs

44 Variability of IMFMC results with topology size 0.0 Fraction of free capacity, ΓI, for IMFMC Median, inter-quartile and 1.5 inter-quartile ranges Number of vertices in graph, V

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