Programmable Packets in the Emerging Extreme Internet

1. Programmable Packets in the Emerging Extreme Internet David Culler UC Berkeley Intel Research @ Berkeley

2. The emerging internet of 2012 • won’t be dominated by independent, point-to-point transport between ‘desktops’ • 99.9% of the network nodes will be the billions of devices deeply embedded in the physical world • they are the majority today, but not connected to each other or the web.... This will change. • they will generate a phenomenal amount of data • Broad-coverage services spread over a substantial portions of the web serve millions at once • CDNs and P2Ps the tip of the iceberg • These ‘extreme’ network environments may present a much greater need for programmability • may also be more condusive to generality • very different attack models and response Programmable Packets

3. Outline • Motivation • Deeply embedded networks of tiny devices • Planetary-scale Services • Discussion Programmable Packets

4. Deeply Embedded Networks • # nodes >> # people • sensor/actuator data stream • unattended • inaccessible • prolonged deployment • energy constrained • operate in aggregate • in-network processing necessary • what they do changes over time => must be programmed over the network Programmable Packets

5. Berkeley Wireless Sensor ‘Motes’ Programmable Packets

6. TinyOS Application Graph Route map router sensor appln application Active Messages Serial Packet Radio Packet packet Temp photo SW Example: self-organized ad- hoc, multi-hop routing of photo sensor readings HW UART Radio byte ADC byte 3450 B code 226 B data clocks RFM bit Graph of cooperating state machines on shared stack Programmable Packets

7. It is a noisy world after all... • Get to rethink each of the layers in a new context • coding, framing • mac • routing • transport, • rate control • discovery • multicast • aggregation • naming • security • ... • Resource constrained, power aware, highly variable, ... • Every node is also a router • No entrenched ‘dusty packets’ probability of reception from center node vs xmit strength Programmable Packets

8. Example “epidemic” tree formation Programmable Packets

9. Tiny Virtual Machines? • TinyOS components graph supports a class of applns. • Application flexibility / extendability needed • Re-tasking deployed networks • Adjusting parameters • Binary program uploading takes ~2 minutes • significant energy cost, vulnerable transition • Tiny virtual machine adds layer of interpretation for specific coordination • Primitives for sensing and communication • Small capsules (24 bytes) • Propagate themselves through network Programmable Packets

10. Maté Overview • TinyOS component • 7286 bytes code, 603 bytes RAM • Stack-based bytecode interpreter • Three concurrent execution contexts • Code broken into capsules of 24 instructions • Single instruction message send • Self-forwarding code for rapid programming • Message receive and send contexts Programmable Packets

11. Subroutines Events 0 1 2 3 Clock Send Receive gets/sets Code Operand Stack PC Mate Context Return Stack Maté Network VM Architecture • 3 execution contexts • dual stack, 1-byte inst. • Send/Rcv/Clock + sub capsules • Hold up to 24 instructions • Fit in a single TinyOS AM packet • installation is atomic • no buffering • Context-specific inst: send, receive, clock • Shared: subroutines 0-3 • Version information Programmable Packets

12. Code Snippet: cnt_to_leds gets # Push heap variable on stack pushc 1 # Push 1 on stack add # Pop twice, add, push result copy # Copy top of stack sets # Pop, set heap pushc 7 # Push 0x0007 onto stack and # Take bottom 3 bits of value putled # Pop, set LEDs to bit pattern halt # Programmable Packets

13. Sending a Message pushc 1 # Light is sensor 1 sense # Push light reading on stack pushm # Push message buffer on stack clear # Clear message buffer add # Append reading to buffer send # Send message using built-in halt # ad-hoc routing system Programmable Packets

14. Viral Code • Every capsule has version information • Maté installs newer capsules it hears on network • Motes can forward their capsules (local broadcast) • forw • forwo Programmable Packets

15. Forwarding: cnt_to_leds gets # Push heap variable on stack pushc 1 # Push 1 on stack add # Pop twice, add, push result copy # Copy top of stack sets # Pop, set heap pushc 7 # Push 0x0007 onto stack and # Take bottom 3 bits of value putled # Pop, set LEDs to bit pattern forw # Forward capsule halt # Programmable Packets

16. Code Progation • 42 motes: 3x14 grid • 3 hop network • largest cell 30 motes • smallest cell 15 motes Programmable Packets

17. Why Tiny Programmable Packets? • All programming must be remote • rare opportunities to get to GDI, can’t mess with the birds, minimize disturbance • too many devices to program by hand • Network programming of entire code image • essential, but often overkill • takes about 2 minutes of active radio time • window of vulnerability • Packet programs propagate very cheaply • if a change will run for less than 6 days, less energy to interpret it • ~10,000 instructions per second • Task operations are 1/3 of Maté overhead • 33:1 to 1.03:1 overhead on TinyOS operations Programmable Packets

18. www.tinyos.org Thoughts on the “Many Tiny” • Deeply embedded networks of small devices are coming • utilize spatial diversity as well as coding and retransmission • severely constrained resources • self-organization is essential • deal with noise and uncertainty - routinely • “Programming the network?” is not a question. • it is necessary • epidemic algorithms common • distributed algorithms (time synch, leader elec, ...) • reactive by design • ‘learning’ framework is natural (ex. MPR routing) • Nodes interact directly with physical world • what they do will matter • potential to observe the effects of actions • Models of security & privacy TBD! • very different attack models • Deja vu opportunity Programmable Packets

19. The Other Extreme - Planetary Scale Services • www.planet-lab.org Programmable Packets

20. Motivation • A new class of services & applications is emerging that spread over a sizable fraction of the web • CDNs as the first examples • Peer-to-peer, ... • Architectural components are beginning to emerge • Distributed hash tables to provide scalable translation • Distributed storage, caching, instrumentation, mapping, events ... • The next internet will be created as an overlay on the current one • as did the last one • it will be defined by its services, not its transport • translation, storage, caching, event notification, management • There will soon be vehicle to try out the next n great ideas in this area Programmable Packets

21. Confluence of Technologies • Cluster-based scalable distribution, remote execution, management, monitoring tools • UCB Millennium, OSCAR, ..., Utah Emulab, ModelNet... • CDNS and P2Ps • Gnutella, Kazaa, ... ,Pastry, Chord, CAN, Tapestry • Proxies routine • Virtual machines & Sandboxing • VMWare, Janos, Denali,... web-host slices (EnSim) • Overlay networks becoming ubiquitous • XBONE, RON, Detour... Akamai, Digital Island, .... • Service Composition Frameworks • yahoo, ninja, .net, websphere, Eliza • Established internet ‘crossroads’ – colos • Web Services / Utility Computing • Grid authentication infrastructure • Packet processing, • Anets, .... layer 7 switches, NATs, firewalls • Internet instrumentation The Time is NOW Programmable Packets

22. Guidelines (1) • Thousand viewpoints on “the cloud” is what matters • not the thousand servers • not the routers, per se • not the pipes, per se Programmable Packets

23. Guidelines (2) • and you miust have the vantage points of the crossroads • primarily co-location centers Programmable Packets

24. Guidelines (3) • Each service needs an overlay covering many points • logically isolated • Many concurrent services and applications • must be able to slice nodes => VM per service • service has a slice across large subset • Must be able to run each service / app over long period to build meaningful workload • traffic capture/generator must be part of facility • Consensus on “a node” more important than “which node” Programmable Packets

25. Guidelines (4) • Test-lab as a whole must be up a lot • global remote administration and management • mission control • redundancy within • Each service will require its own remote management capability • Testlab nodes cannot “bring down” their site • generally not on main forwarding path • proxy path • must be able to extend overlay out to user nodes? • Relationship to firewalls and proxies is key Management, Management, Management Programmable Packets

26. Guidelines (5) • Storage has to be a part of it • edge nodes have significant capacity • Needs a basic well-managed capability • but growing to the seti@home model should be considered at some stage • may be essential for some services Programmable Packets

27. Initial Researchers (mar 02) • Rice • Peter Druschel • Utah • Jay Lepreau • CMU • Srini Seshan • Hui Zhang • UCSD • Stefan Savage • Columbia • Andrew Campbell • ICIR • Scott Shenker • Mark Handley • Eddie Kohler • Intel Research • David Culler • Timothy Roscoe • Sylvia Ratnasamy • Gaetano Borriello • Satya • Milan Milenkovic • Duke • Amin Vadat • Jeff Chase • Princeton • Larry Peterson • Randy Wang • Vivek Pai Washington Tom Anderson Steven Gribble David Wetherall MIT Frans Kaashoek Hari Balakrishnan Robert Morris David Anderson Berkeley Ion Stoica Joe Helerstein Eric Brewer John Kubi Programmable Packets see http://www.cs.berkeley.edu/~culler/planetlab

28. Initial Planet-Lab Candidate Sites Uppsala UBC Copenhagen UW Cambridge WI Chicago UPenn Amsterdam Harvard Utah Intel Seattle Karlsruhe Tokyo Intel MIT Intel OR Beijing Barcelona Intel Berkeley Cornell CMU ICIR Princeton UCB St. Louis Columbia Duke UCSB Washu KY UCLA GIT Rice UCSD UT ISI Melbourne Programmable Packets

29. Approach:Service-Centric Virtualization • Virtual Machine Technology has re-emerged for hosting complete desktop environments on non-native OS’s and potentially on machine monitors. • ex. VMWare, ... • Sandboxing has emerged to emulate multiple virtual machines per server with limited /bin, (no /dev) • ex. ENSim web hosting • Network Services require fundamentally simpler virtual machines, can be made far more scalable (VMs per PM), focused on service requirements • ex. Jail, Denali, scalable and fast, but no full legacy OS • access to overlays (controlled access to raw sockets) • allocation & isolation • proportional scheduling across resource container - CPU, net, disk • foundation of security model • fast packet/flow processing puts specific design pressures • Instrumentation and management are additional virtualized ‘slices’ • distributed workload generation, data collection Programmable Packets

30. Hard problems/challenges • “Slice-ability” – multiple experimental services deployed over many nodes • Distributed Virtualization • Isolation & Resource Containment • Proportional Scheduling • Scalability • Security & Integrity - remotely accessed and fully exposed • Authentication / Key Infrastructure proven, if only systems were bug free • Build secure scalable platform for distributed services • Narrow API vs. Tiny Machine Monitor • Management • Resource Discovery, Provisioning, Overlay->IP • Create management services (not people) and environment for innovation in management • Deal with many as if one • Building Blocks and Primitives • Ubiquitous overlays • Instrumentation Programmable Packets

31. Programmable Packets w/i a Slice • A service spread over the globe needs to be extensible through methods more lightweight than ‘reload all the code’ • not unlike the ‘new router firmware’ problem • Smart Packets interpreted in the context of the containing service-slice, rather than generic core-router. • Routing is overlay routing, so not limited by CISCO design cycle • ‘Global view’ gives the service many advantages • not just localization / caching • adaptive or multipath routing in the overlay • multi-lateration in the network space • consider a global spam filter • Reactive loops within a service are natural • service-driven load balancing, overlay management, SEDA-style processing Programmable Packets

32. Discussion Wide-Area Broad-Coverage Services Deeply- Embedded Networks Traditional pt-pt Internet Programmable Packets

33. Security: restricted API -> Simple Machine Monitor • Authentication & Crypto works… if underlying SW has no holes • very simple system • push complexity up into place where it can be managed • virtualized services • Classic ‘security sandbox’ limits the API and inspects each request • Ultimately can only make very tiny machine monitor truly secure • SILK effort (Princeton) captures most valuable part of ANets nodeOS in Linux kernel modules • controlled access to raw sockets, forwarding, proportional alloc • Key question is how limited can be the API • ultimately should self-virtualize • deploy the next planetlab within the current one • progressively constrain it, introducing compatibility box • minimal box defines capability of thinix • Host f1 planetSILK within f2 thinix VM Programmable Packets