Towards Cooperative Self- Organized Replica Management Work in Progress David Hales, Andrea Marcozzi (University of Bologna) Giovanni Cortese (University.

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Presentation transcript:

Towards Cooperative Self- Organized Replica Management Work in Progress David Hales, Andrea Marcozzi (University of Bologna) Giovanni Cortese (University of Rome, RadioLabs) SASO 2007, Cambridge. Mass.

SASO 2007www.davidhales.com Cooperative Self-Organized Content Replication Assuming protocols for Replicating content between nodes Redirecting queries (requests for content) between nodes Peer sampling over a population of nodes We want: Simple protocol for cooperatively coordinating these services to maximise system capacity With incentives for nodes to cooperate Dynamically adjusting to varying load and node entry and exit CacheWorld: Cooperative content replication

SASO 2007www.davidhales.com CacheWorld outline

SASO 2007www.davidhales.com CacheWorld outline

SASO 2007www.davidhales.com CacheWorld Outline Algorithm capacity and load for each node specify different scenarios maximum number of neighbours (k) currently fixed nodes “satisfied” if all queries submitted to them are answered (over a given period - the load cycle) nodes associated with single unique content item replicated between linked neighbours nodes are “receptive” if they have spare capacity or are not satisfied

SASO 2007www.davidhales.com Q = queries answered, S = satisfied nodes (very simple scenario, half nodes underloaded, half overloaded, k = 1) Some initial results

SASO 2007www.davidhales.com Q = queries answered, S = satisfied nodes (less simple scenario, half nodes under-loaded, half overloaded, k = 4) Some initial results

SASO 2007www.davidhales.com Very initial results, with simple load / capacity scenarios Nodes replicate and serve a single “content” item Not modelling cost of replication process Fixed loads and capacities Hence more realistic scenarios needed and comparison with existing protocols (Squirrel, Globule) Still not tested with malicious nodes, pure free-riders and churn. But reasonably confident will degrade gracefully Specially factoring in replication cost could help prevent bad guys Varying of satisfaction threshold simple “loyalty” approach (where preference is given to older links) could lead to much better results but this is on-going. Interesting this could link to a lot of work from “evolutionary economics” (Kirman’s Marseille Fish Market studies / models) CacheWorld in progress

SASO 2007www.davidhales.com WP5.3 Summary Related Publications: Hales, D. and Arteconi, S. (2006) SLACER: A Self-Organizing Protocol for Coordination in P2P Networks. IEEE Intelligent Systems 21(2):29-35 Hales, D. (2006) Emergent Group-Level Selection in a Peer-to- Peer Network. Complexus 2006:3. Hales, D. and Babaoglu, O. (2006) Towards Automatic Social Bootstrapping of Peer-to-Peer Protocols. ACM SIGOPS Operating Systems Review 40(3) Arteconi, S., Hales, D., Babaoglu, O. (2007) Greedy Cheating Liars and the Fools Who Believe Them. Proc. Workshop on Engineering Self-Organising Applications (ESOA2006), Springer Get these from

SASO 2007www.davidhales.com