A Modeling Framework for Gossip-based Information Spread

We present an analytical framework for gossip protocols based on the pair wise information exchange between interacting nodes. This framework allows for studying the impact of protocol parameters on the performance of the protocol. Previously, gossip-based information dissemination protocols have been analyzed under the assumption of perfect, lossless communication channels. We extend our framework for the analysis of networks with lossy channels. We show how the presence of message loss, coupled with specific topology configurations, impacts the expected behavior of the protocol. We validate the obtained models against simulations for two protocols.

[1]  Maarten van Steen,et al.  CYCLON: Inexpensive Membership Management for Unstructured P2P Overlays , 2005, Journal of Network and Systems Management.

[2]  Anne-Marie Kermarrec,et al.  Gossip-based peer sampling , 2007, TOCS.

[3]  Andrew S. Tanenbaum,et al.  Distributed systems: Principles and Paradigms , 2001 .

[4]  Idit Keidar,et al.  Correctness of gossip-based membership under message loss , 2009, PODC '09.

[5]  Ansgar Fehnker,et al.  On the Impact of Modelling Choices for Distributed Information Spread , 2009, 2009 Sixth International Conference on the Quantitative Evaluation of Systems.

[6]  M. van Steen,et al.  A Gossip-based Distributed News Service for Wireless Mesh Networks , 2006 .

[7]  Gian Paolo Jesi,et al.  Exploring the interdisciplinary connections of gossip-based systems , 2007, OPSR.

[8]  Peng Gao,et al.  Formal Verification and Simulation for Performance Analysis for Probabilistic Broadcast Protocols , 2006, ADHOC-NOW.

[9]  R. Bakhshi Gossiping Models : Formal Analysis of Epidemic Protocols , 2011 .

[10]  M. V. Steen,et al.  Newscast Computing , 2003 .

[11]  Keith Marzullo,et al.  Directional Gossip: Gossip in a Wide Area Network , 1999, EDCC.

[12]  Boudewijn R. Haverkort,et al.  Mean-field framework for performance evaluation of push-pull gossip protocols , 2011, Perform. Evaluation.

[13]  Roberto Beraldi,et al.  A Formal Characterization of Uniform Peer Sampling Based on View Shuffling , 2009, 2009 International Conference on Parallel and Distributed Computing, Applications and Technologies.

[14]  Wan Fokkink,et al.  A Modeling Framework for Gossip-based Information Spread , 2011, 2011 Eighth International Conference on Quantitative Evaluation of SysTems.

[15]  Stephen P. Boyd,et al.  Randomized gossip algorithms , 2006, IEEE Transactions on Information Theory.

[16]  A. Dimakis,et al.  Geographic gossip: efficient aggregation for sensor networks , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[17]  Dan Rubenstein,et al.  A lightweight, robust P2P system to handle flash crowds , 2002, IEEE Journal on Selected Areas in Communications.

[18]  Arend Rensink,et al.  Applying formal methods to gossiping networks with mCRL and groove , 2008, PERV.

[19]  Wan Fokkink,et al.  An analytical model of information dissemination for a gossip-based protocol , 2008, Comput. Networks.

[20]  Scott Shenker,et al.  Epidemic algorithms for replicated database maintenance , 1988, OPSR.

[21]  John E. Hopcroft,et al.  Correctness of a gossip based membership protocol , 2005, PODC '05.

[22]  Henri E. Bal,et al.  ARRG: real-world gossiping , 2007, HPDC '07.

[23]  Boudewijn R. Haverkort,et al.  Automating the Mean-Field Method for Large Dynamic Gossip Networks , 2010, QEST.