1 Cycle Detection in Publish/Subscribe Overlay Networks Reza Sherafat Alex Cheung Prof. Cristiana Amza ECE1747 – Course Project University of Toronto

2 Overview of Publish/Subscribe Systems Network consists of - Clients: Publisher, subscriber - Routing brokers Overlay may be cyclic, non-cyclic Publisher Subscriber 1. Advertise 2. Subscribe 3. Publish

3 Cyclic Overlay Networks Supporting cycles is good: Load balancing Hard to avoid Failure recovery Routing through cycles is challenging: Duplicates waste bandwidth Infinite loops Advertisement Tree 1 Advertisement Tree Duplicate Messages S S S S S

4 Outline Routing in cyclic overlay Cycle detection algorithm Implementation Future work

5 Routing Through Cycles Preparation: Detect cycles Let brokers know that they are on cycles Keep cycle information updated Routing: Route advertisements in a cycle-free manner Route subscriptions in a cycle-free manner Keep track of brokers downstream Route publications in a cycle-free manner Use cycle information and source routing to exploit cycles

6 Cycles Large cycles are bad candidates for re-routing Alternative paths may be too long We focus on cycles smaller than a configurable size s. Better choices for our purposes Easier to detect Cycles detection algorithm, detects such small cycles.

7 Cycle Detection Algorithm We want to detect all cycles smaller than s+1 Based on Asynchronous Breath-First Search Starting from a Heart broker propagate special messages Append broker’s id to the message and send it to neighbors When a duplicate is received, there is a cycle Compare broker id lists to find members Inform all members of the cycle Delays in message delivery are problem some

8 Cycle Detection Algorithm Ad1: b1 Ad1:b1,b2 Ad1:b1,b2,b3 Ad1:b1,b2,b3,b4 Ad1:b1,b5 s=5 L=4 Ad1:b1,b2,b3,b4,b5 Propagate b1b5 b1,b5 b1b5 b1,b2,b3,b4,b5 Compare

9 Cycle Detection Algorithm By limiting the size of cycles we lower the overhead Broker id list will be at most s-1 Problem when the “small” cycle is far away from the Heart Because broker id list is too short Hearts must not be far away Hearts roughly partition the network into local areas …… Heart A small cycle is not discovered We have to limit the depth d that messages are propagated.

10 Cycle Detection Algorithm Roughly speaking we propagate Heart’s messages to double the cycle size (2s) in order to detect whether a broker within distance s (local) is on a cycle. Hence s brokers in each direction away have a local broker’s id s-1 is sufficient for broker id lists Zones: Full discovery zone Partial discovery zone Full Discovery zone (local) Partial discovery zone Distance from Heart

11 Cycle Detection Algorithm Scalability Heart messages are propagated limited # of hops away Broker id lists have at most s-1 ids Each Heart locally detects cycles We need to place hearts side by side (Future work)

12 Implementation Based on pub/sub semantics Message class LOOP_DETECTOR Command attribute: control, path, loop Loop detection module An add-on to brokers Process LOOP_DETECTOR publications using separate queues Extensions to the pub/sub semantics Source routing Distance-aware

13 Implementation Path information is part of publication’s payload Brokers subscribe to LOOP_DETECTOR messages Received messages are put into the loopdetector’s queue Major new classes: LoopDetector LoopDetectorManager

14 Future Work Heart placement We need to place hearts side by side Implement routing algorithm With load balancing Implement fault recovery algorithm By using alternative paths formed in cycles