Challenges in the Design and Evaluation of Content -Centric Networks

1. Challenges in the Design and Evaluation of Content-Centric Networks Jim Kurose Department of Computer Science University of Massachusetts Amherst MA USA ‘ Visiting Scientist, Technicolor Paris Lab Professeur Invite, LINCS Sigcomm ICN Workshop, Aug 2013

2. Overview • architecture, system, prototype • networksof caches • challenges • approximation algorithms • network calculus for cache networks • workload: logical mobility among networks

3. Architecture, System, Prototype * high-level design/structuring principles, service/function modularity architecture guides, informs, inspires, constrains system instantiated set of interoperating protocols, mechanisms, platforms conforming to design principles “here’s what it does (function), you tell me how” prototype (realization) Implemented (sub)set of protocols, platforms in particular existing technologies * ack: D. Clark, J. Wroclawksi

4. Architecture, System, Prototype Minimalist – principles, modularities architecture system Maximalist – protocols, mechanisms go here prototype

5. Architecture, System, Prototype telephony Internet ICN architecture end-end circuit, stateless endpoints, stateful core, QoS, single service content, naming, stateful core, caching datagram, stateful endpoints, best-effort stateless core, multiple services, IP Ongoing (routing, congestion control, caching, name resolution, search,…) system SS7, ESS, MSC, VLR, HLD TCP, UDP, DNS, BGP, IS-IS, OSPF prototype many .. over the years Ramping up … many .. over the years

6. Architecture, System, Prototype telephony Internet ICN architecture end-end circuit, stateless endpoints, stateful core, QoS, single service content, stateful core, caching datagram, stateful endpoints, best-effort stateless core, multiple services, IP OK .. but why care? Ongoing (routing, congestion control, caching, name resolution, search,…) system SS7, ESS, MSC, VLR, HLD TCP, UDP, DNS, BGP, IS-IS, OSPF prototype many .. over the years Ramping up … many .. over the years

7. Architecture, System, Prototype Internet ICN architecture content, stateful core, caching datagram, stateful endpoints, best-effort stateless core, multiple services, IP Ongoing (routing, congestion control, caching, name resolution, search,…) system TCP, UDP, DNS, BGP, IS-IS, OSPF Architecture research/evaluation more difficult, more “fundamental” (?), more impactful (?) Research/evaluation mostly here: mechanism, protocols prototype

8. Architecture, System, Prototype telephony Internet ICN architecture end-end circuit, stateless endpoints, stateful core, QoS, single service content, stateful core, caching datagram, stateful endpoints, best-effort stateless core, multiple services Kleinrock 64 ? Cerf, Kahn 74 Clark 1988 McCanne 1998 Ongoing (routing, congestion control, caching, name resolution, search,…) system SS7, ESS, MSC, VLR, HLD TCP, UDP, DNS, BGP, IS-IS, OSPF ? Queueing networks Delay calculus Effective bandwidths TCP, NUM optimization ? Blocking networks Evaluation

9. Challenges • ICN: architecture vs protocol/mechanism • elucidation, value-proposition of design principles, service/function modularities • evaluation tool: networks of caches Interlude ….

10. Overview • architecture, system, prototype • networksof caches • challenges • approximation algorithms • network calculus for cache networks • workload: logical mobility among networks

11. Cache networks content custodian content custodian miss miss miss miss miss miss miss • content requests from different users interact: cache replacement content request • consumer requests content • request routed (e.g., shortest path) to known contentcustodian • en-route to custodian, cachesinspectrequest • hit: return local copy • miss: forward request towards custodian • during content download, store in cachesalong path

12. Challenge: networks of caches • network effect: interaction amongcontent request/reply flows from different users: • content replacement: requested content by one user replaces content previously requested by others x Circuit-switching: blocking networks (Erlang, 1917, Kelly 1986) Packet-switching: queueing networks (Kleinrock, 1963) Content-caching: cache networks

13. Modeling a network of caches j • y • i • m(j,i) • w • m(j,w) S l(i,j) r(i,j) = l(i,j) + m(j,h) • m(j,x) all downstream neighbors, h content • x • node i: exogenous(external) arrivals for content j: l(i,j) • node i: internal arrivals (miss stream) for content jfrom downstream neighbors h:m(j,h) • r(i,j): aggregate rate of arrival requests at i for content j • ZDD: zero download delay assumption

14. Modeling a network of caches Pr(Xt= fj| X1,..,Xt-1) = Pr(Xt=fi) r(i,1) m(i,1) r(i,n) m(i,n) • cache i But we need {(ri,j, mi,j)} for a network of caches • SCA: standalone cache i approximation algorithm: given r(i,j),compute miss rate for all content j • Independence Reference Model (IRM) of incoming requests: • SCA approximation algorithm for LRU: [Dan 1985]

15. Fixed-point iteration Note: tree-network (feed-forward) require single iteration Using SCA algorithm Set r(i,j)=λ(i,j) Using SCA algorithm Compute miss rate m(i,j) Compute arrival rate r(i,j) Repeat until convergence Return r(i,j), m(i,j) Using Routing Matrix 

16. Quality of a-NET a-NET: approximation error 1.14 1.12 1.10 1.08 1.06 1.04 1.02 1.0 0.98 • line topology with 9 nodes • errors decrease in networks with high node degree Sim / Approx Misses 0 1 2 3 4 5 6 7 8 9 Cache ID

17. a-NET: error factor analysis sources of approximation errors in a-NET? • SCA algorithm inaccuracies • cascading errors • approximated output rates of one iteration is input to next iteration • violating IRM assumed by SCA algorithm • miss process for file j negatively correlated

18. Quality of a-NET Cascade Err. removed Non-IRM removed Quality of SCA a-NET: error factor analysis 1.14 1.12 1.10 1.08 1.06 1.04 1.02 1.0 0.98 • Factor analysis reveals that non-IRM inputto SCA is main cause of error Sim / Approx Misses 0 1 2 3 4 5 6 7 8 9 Cache ID “Approximate Models for General Cache Networks,” Elisha J. Rosensweig, Jim Kurose, Don Towsley, 2010 IEEE INFOCOM

19. Overview • architecture, system, prototype • networksof caches • challenges • approximation algorithms • network calculus for cache networks • workload: logical mobility among networks

20. (σi,ρi) analyses of cache networks (σi,ρi)bounds # requests for fiover [t1,t2]: where ri(t) = request rate for fi at time t Goal: a network calculus for cache networks: (σ1out,ρ1out) (σ1in,ρ1in) f1 requests fnrequests t1 t1 t0 t0 (σnin,ρnin) (σnout,ρnout)

21. (σi,ρi) cache networks: observations • not all requests arriving at cache will leave (unlike queue) • stream of input requests for one file only generates no output • “burst” of request for same file generates one output • interactions among files in cache critical • different intuition (from queues) about “performance damage” of bursts f1 requests f2 requests t1 t1 t0 t0

22. Building block: miss set, Mi miss set for fi: set of requests for c unique files, other than i Mi(x1, …., xn,c): max number miss sets for file fi, given {xiin} arrivals, cache of size c. properties: • Mi = min(xiin, M) • xiout < Mi, and this bound is achievable x1requests for f1 . . . . . . xnrequests for fn c: cache size w !!

23. From (σiin,ρiin)to(σiout,ρiout): (σiout,ρiout) (σiin,ρiin) fi requests . . . . . . fj requests (σjin,ρjin) (σjout,ρjout) If {(σiin,ρiin)}ni=1and {(σ’iin,ρ’iin) }ni=1are globally tightand ρiin = ρ’iinfor all i then ρiout= ρ’iout Theorem: riout independent of {σiin}

24. From (σiin,ρiin)to(σiout,ρiout): (σiout,ρiout) (σiin,ρiin) fi requests . . . . . . fj requests (σjin,ρjin) (σjout,ρjout) For a cache of size c: ρiout= min(ρiin, Mi(ρ1in, … ,ρnin,c )) Theorem: Can calculate ρioutfrom {ρiin} siout Can compute as well

25. Numerical example f0,f2 f1,f3 cache size = 2 at each node homogeneous IRM arrivals, exponential interarrival times 4 files, uniform popularity distribution

26. Numerical example: bounding results bound miss rate for f3 simulation Cache ID

27. Challenges • ICN: architecture vs protocol/mechanism • elucidation, value-proposition of design principles, service/function modularities • modeling networks of caches: develop analytic models for cache networks (ICN) • equivalent of blocking networks (circuit-switched), or queueing networks (packet switched)? • exact in asymptotic regimes? • ergodicty?

28. Overview • architecture, system, prototype • networks of caches • challenges • approximation algorithms • network calculus for cache networks • workload: logical mobility among networks

29. Characterizing mobility among networks • Historic shift from PC’s to mobile/embedded devices • ~5B cell phones (`1B smart) vs. ~1B Internet-connected PC’s • Mobile data growing exponentially,surpassing wired user traffic by 2012 [Cisco] • any evaluation/model (ICN or otherwise) must consider mobility • “not your father’s mobility:” characterize mobility among networks • distinctly different from physical mobility, models • physically mobile users may be stationary (from network transition POV); stationary users may move among networks (multi-homing, multiple devices)

30. Characterizing mobility among networks • Measure mobility among networks via IMAP logs • online users periodically “push” (background login, check) email, and/or intentionally read mail • e.g., kurose@cs.umass.edu generated 7,482 IMAP entries 4/14/13 – 6/4/13 • track network location from which IMAP accessed • 70 users, 4/14/13 – 7/5/13, resident in 183 unique AS numbers

31. Where do users (in aggregate) spend time? Work: 5 college Home: Comcast, Verizon, Verizon, Hughes Mobile: Verizon, AT&T, sprint) Misc: 172 other networks in trace Users spend most of their time in small number of networks

32. Where do users (individually) spend time? Users individually spend most of their time in small number of networks

33. Multihoming VERIZON COMCAST

34. Multi-homing • Q: How often are users multi-homed? • 15-min subinterval has IMAP access from two different AS’s

35. Characterizing mobility among networks • other characterizations of mobility among networks • generative mobility-among-network model: parsimonious Markov chain model for individual user transitioning among networks

36. Challenges • ICN: architecture vs protocol/mechanism • elucidation, value-proposition of design principles, service/function modularities • modeling networks of caches: develop analytic models for cache networks (ICN) • equivalent of blocking networks (circuit-switched), or queueing networks (packet switched) • exact in asymptotic regimes? • ergodicty • traffic models (for ICM and otherwise), with mobile users, content • mobility the norm

37. Conclusion • architecture, system, prototype • networksof caches • challenges • approximation algorithms • network calculus for cache networks • workload: logical mobility among networks

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39. Interesting reading • J. Wroclawski, “All hat no answers: Some issues related to the evaluation of architecture,” March 2013 NSF FIA meeting, Salt Lake City UT • D. Clark, “The Design Philosophy of the DARPA Internet Protocols,” ACM Sigcomm 1988,Revised with extensive commentary 2013 • E. Rosensweig, D. Menasche, J. Kurose, “On the Steady-State of Cache Networks,” IEEE Infocom 2013. • E. Rosensweig, J. Kurose, “A Network Calculus for Cache Networks,” IEEE Infocom Mini-conference 2013. • E. Rosensweig, J. Kurose, D. Towsley, “Approximate Models for General Cache Networks,” 2010 IEEE Infocom, pp. 1100-1108 • S. Yang, S. Heimlicher, J/.Kurose, A. Venkataramani, “User Transitioning Among Networks - a Measurement and Modeling Study”, submitted, 2014.

40. Ergodicity of cache networks • does steady state performance depend on initial conditions (ergodicity)? • shown existence of non-ergodic cases (replacement policy, topology, cache size) • derived sufficient conditions for ergodicity • topology (single-custodian trees) • from individual ergodicity to system ergodicity Requests for B Requests for A A B B A A B

41. Ergodicity of cache networks • ergodicty (continued): • showed random replacement: ergodic • defined class of non-protective policies (including LRU): all ergodic content