total order in content-based publish/subscribe systems

MIDDLEWARE SYSTEMSRESEARCH GROUP

MSRG.ORG

Total Order in Content-based Publish/Subscribe Systems

Joint work with:

Vinod Muthusamy,

Hans-Arno Jacobsen

University of Toronto http://www.padres.msrg.utoronto.ca

ICDCS 2012, June 19th 2012Kaiwen Zhang


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2Kaiwen Zhang, Vinod Muthusamy, Hans-Arno Jacobsen

Outline

Background: publish/subscribe Total order semantics Related work: sequencers Natural pairwise total order Our two-phase solution Performance evaluation Comparison with

Group communication systems


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Advertisement-Based Pub/Sub3

brokermatch &

forward

Advertisement pathSubscription path

Publication path

publisher

name = ÌBM’

price = $40

subscriber

name = ÌBM’ price > $20

subscriber

name = ÌBM’ price > $30

name = ‘IBM’


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Pairwise Total Order (PTO)for Pub/Sub


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Application Scenarios Little work on total order in pub/sub so far

Subscriber decoupling Minimize overhead

External communication between peers Comparing event streams

Consistency Online games (non-commutative operations) Monitoring (stream ordering)

Fairness Stock quote (detecting event patterns)


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Drawbacks of Sequencers

Sequencer networks [Lumezanu 2006] Topic-based Global knowledge Sequencing overhead applied

to all pubs and subs


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Per-Publisher Ordering using FIFO Links Per-Publisher TO

Maintaining order per publisher (i.e. FIFO order) Per-Publisher TO is maintained using

FIFO links between overlay neighbours Requires unique paths to each sub!


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Natural Pairwise TO (N-PTO) Using FIFO links, a common broker for all

publisher/subscriber pairs provides N-PTO. Consider that broker as a “super-publisher”

Per-publisher TO is then enforced from that broker on

Consider P1 and P2 as internal tothe publisher B0


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Our Solution

Uses FIFO links N-PTO provided by a common broker

Two phases: Conflict detection

Identify pairs of disjoint publisher/subscriber paths

Resolution Defer delivery only to affected subscribers

Lightweight solution for content-based P/S Uses local ads/subs broker knowledge

(next-hops)


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No ConflictP2 doesn't match S4No conflict

S1-S3 share same next-hop as P2No conflicts detected at B1

S1-S3 have differentnext hop from P2:

B3 is a common broker


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Conflict ResolutionS4 forwardedimmediately

S1 has a different next-hop fromS2-3 and P2:

Their paths are disjoint!

Defer delivery to S1, wait for ackConflict for S3, defer until ack

Detects that P2 and S2 have different next-hops:

Send ack back


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Properties of the Solution System model:

Acyclic topology FIFO links Advertisement-based

Solution is safe under crash failures Theorem: “Pairwise total order is impossible in

publish/subscribe systems under the presence of failures.”

Optimizations: Progressive delivery Faster detection


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Evaluation

Implementation using PADRES in Java Modular; requires only few changes to the core

Workload Overlapping subscriptions; stress test High conflict rates: 25-100%

Topology 24 to 96 brokers 800 subscribers, 240 publishers


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Low Detection OverheadOverall, still small

impact to non-conflictsubs

Overhead increaseswith less conflict


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Scalability over Baseline

Central sequencer

Our solution

No total order

Throughput saturatedfor central sequencer


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Performance over Spread (Group Communication Systems)

Our solution

Spread w/o ord.

Outperformed aftera certain size

Spread w/ TO(token algorithm)

Overhead due toTO


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Conclusions & Future Work Lightweight solution for content-based p/s

Local broker knowledge Contained resolution overhead

Extension for cyclic topologies Adjust routing paths

Pub/sub clustering and client mobility Maximize natural ordering


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Thank you!

total order in content-based publish/subscribe systems

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