soft state in publish/subscribe

Overview System Model Soft State Evaluation Summary 1 of 23 slides

Soft State in Publish/SubscribeDEBS 2009

Zbigniew Jerzak and Christof Fetzer

Systems Engineering Group, Dresden University of Technology

Thursday 9th July, 2009

Soft State in Publish/Subscribe Zbigniew Jerzak and Christof Fetzer

What is Soft State?

System state which can be lost without permanent disruption ofsystem features [Cla88]

I Soft state system =⇒ a survivable system:I can cope with transient failuresI state is held at the edge of the systemI node crash =⇒ loss of state owned by it

What is Soft State?

System state which can be lost without permanent disruption ofsystem features [Cla88]

I Soft state system =⇒ a survivable system:I can cope with transient failuresI state is held at the edge of the systemI node crash =⇒ loss of state owned by it

In This Talk

I How to build a soft pub/sub system using a practical systemmodel, i.e., one which:

I makes realistic assumptions about the type and frequency offailures

I can be implemented in a real, distributed environment, i.e.,PlanetLab

Approach Overview

Challenges

rtt [ms]

LAN: inf.tu-dresden.deMAN: tu-dresden.de

WAN: tu-dresden->tu-berlin

Figure 1: Network latencies cannot be predicted, nor bounded!

Challenges

request processing time [µs]

Lab PCPlanetLab node

Figure 1: Request processing time cannot be predicted, nor bounded!

Challenges – contd.

Timed Asynchronous Distributed System Model [CF99]

I All processes are timed (σmax)I . . . however, no guarantee that a request is indeed answered

within σmax

I Processes expose crash-stop failure semanticsI . . . and we know [WF07] how to enforce it

I Messages might be arbitrarily delayed or droppedI . . . specifically, no upper bound on message transmission delay

I Only local hardware clocks, with bounded drift rate (ρmax)I . . . and crash-stop failure semantics

within σmax

Publish/Subscribe Model

I Our approach works with any pub/sub modelI topic-basedI type-basedI content-basedI rule-based

I It does not require bounds on message propagation delays

I It does not require clock synchronization

I Our approach works with any pub/sub model

I propagation delay = transmission delay + processing delay

I Our approach works with any pub/sub model

Approach

Use upper bound on message propagation delayto estimate the link uncertainty

I Link uncertainty:I a measure of the link latency variationI calculated using upper bound on propagation delay [JFF07]

Extend the advertisement/subscription validityusing calculated link uncertainty

Approach

Extending the Lease Time

Estimating (One-Way) Link Latencies

latency(sub) 6= (D − C )

latency(sub) ≥ (D − A)

latency(sub) ≥ (D − A)− (C − B)

latency(sub) ≥ (D − A)− (C − B)− δmin

latency(sub) ≥ (D − A)(1 + ρmax)− (C − B)(1− ρmax)− δmin

Evaluation Environment

I F-A P/SI Zbigniew Jerzak, Robert Fach, and Christof Fetzer. Fail-aware

publish/subscribe. In NCA 07: Sixth IEEE InternationalSymposium on Network Computing and Applications, pages113125, Cambridge, MA, USA, July 2007.

I XSiena

I Apache Mina

I PlanetLab

I F-A P/SI XSiena

I http://wwwse.inf.tu-dresden.de/xsiena/

I Apache Mina

I PlanetLab

I F-A P/S

I XSienaI Apache Mina

I http://mina.apache.org/

I PlanetLab

I F-A P/S

I XSiena

I Apache MinaI PlanetLab

I http://www.planet-lab.eu/

Local Setup

Local Setup – Upper Bound on Processing Delay

0 10 20 30 40 50

event number

u-b pd (p1->s3)r-t pd (p1->s3)

u-b pd (p1->b2)r-t pd (p1->b2)

European PlanetLab Setup

PlanetLab Europe – First Broker

300 320 340 360 380 400

refresh message number

last 200 msgs (di.unito.it)last 20s (di.unito.it)u-b pd (di.unito.it)

PlanetLab Europe – Last Broker

300 320 340 360 380 400

refresh message number

last 200 msgs (cs.uit.no)last 20s (cs.uit.no)u-b pd (cs.uit.no)

Intercontinental PlanetLab Setup

PlanetLab World – Advertisement Presence

26 28 30 32 34

time [s]

uoit.ca - extuoit.ca - noext

hiit.fi - exthiit.fi - noext

PlanetLab World – Total Time without Advertisement

1 10 100

time [s]

uoit.ca - extuoit.ca - noext

hiit.fi - exthiit.fi - noext

Summary

I Keep the state with the state owner

I Limit the impact of failures

I Use upper bound on propagation delay to ensure eventuallconsistency

I For more information:I Jerzak, Z.; Fach, R. & Fetzer, C. Fail-Aware Publish/Subscribe

NCA ’07: Proceedings of the Sixth IEEE InternationalSymposium on Network Computing and Applications, IEEEComputer Society, 2007, 113-125

I Jerzak, Z.; Fach, R. & Fetzer, C. Adaptive Internal ClockSynchronization SRDS ’08: 27th International Symposium onReliable Distributed Systems, IEEE Computer Society, 2008,217-226

Thank You!http://wwwse.inf.tu-dresden.de/xsiena/softstate

References

Flaviu Cristian and Christof Fetzer.The timed asynchronous distributed system model.IEEE Transactions on Parallel and Distributed Systems, 10(6):642–657, June1999.

D. Clark.The design philosophy of the DARPA internet protocols.In SIGCOMM ’88: Symposium proceedings on Communications architecturesand protocols, pages 106–114, New York, NY, USA, 1988. ACM.

Zbigniew Jerzak, Robert Fach, and Christof Fetzer.Fail-aware publish/subscribe.In NCA ’07: Proceedings of the Sixth IEEE International Symposium on NetworkComputing and Applications, pages 113–125, Cambridge, MA, USA, July 2007.IEEE Computer Society.

Ute Wappler and Christof Fetzer.Software encoded processing: Building dependable systems with commodityhardware.In Francesca Saglietti and Norbert Oster, editors, SAFECOMP ’07: 26thInternational Conference on Computer Safety, Reliability, and Security, volume4680 of Lecture Notes in Computer Science, pages 356–369, Nuremberg,Germany, September 2007. Springer.

soft state in publish/subscribe

Education

system state

slides soft state

talk soft state

planetlab soft state

soft pubsub system

loss of state

transient failures state

practical system model