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Biology-Inspired techniques for Self-Organization in dynamic Networks

Progress - Overlay Networks

Overlay Networks

Computer networks in general, and the Internet in particular, are experiencing explosive growth in many dimensions, including size, performance, user base and geographical span. The potential for communication and access to computational resources have improved dramatically both quantitatively and qualitatively in a relatively short time. New design paradigms such as peer-to-peer (P2P) and grid computing have emerged in response to these trends. The Internet, and all similar networks, pose special challenges to the designer of large-scale, reliable distributed applications. The ``best-effort'' design philosophy that characterizes such networks renders the communication channels inherently unreliable and the continuous flow of nodes joining and leaving the network make them highly dynamic. Control and monitoring in such systems are particularly challenging: performing global computations requires orchestrating a huge number of nodes.

We believe that, in order to respond to these challenges, a modular paradigm is required. The idea is to identify a collection of simple and predictable services as building blocks and combine them in arbitrarily complex functions and protocols. Such a modular approach presents several attractive features. Developers will be allowed to plug different components implementing a desired function into existing or new applications, being certain that the function will be performed in a predictable and dependable manner. Research may be focused on the development of simple and well-understood building blocks, with a particular emphasis on important properties like robustness, scalability, self-organization and self-management.

The ``building blocks'' produced so far can be informally subdivided into two broad categories: overlay protocols and functional protocols. An overlay protocol is aimed at maintaining application-layer, connected communication topologies over a set of distributed nodes. These topologies may constitute the basis for functional protocols, whose task is to compute a specific function over the data maintained at nodes. Our components are typically no more complicated than a cellular automaton or a swarm model which makes them ideal objects for research. Practical applications based on them can also benefit from a potentially more stable foundation and predictability, a key concern in fully distributed systems.

Additional details about the proposed paradigm can be found in a paper published in the Proceedings of the EU-NSF Strategic Research Workshop on Unconventional Programming Paradigms (UPP'04) [BJM04]. A previous paper on the subject, published in the Proceedings of AAMAS Workshop on Engineering Self-Organizing Applications (ESOA'03), illustrates how a load-balancing protocol can be obtained combining other, simpler building blocks [JMB04].

Our current bag of protocols includes:


Topology Management

We have developed protocols for maintaining both unstructured and structured topologies. Newscast [VJvS03,JGKvS04] is a membership protocol aimed at maintaining robust, connected random topologies; T-Man [JB05,MJB05] can be used to build structured topologies like grids and tori; SG-1 [Mon04] constructs superpeer-based topologies.


Decentralized Aggregation

Aggregation is a common name for a set of functions that provide global, statistical information about a distributed system. Examples of aggregation functions include network size, total free storage, maximum load, average uptime, location and description of hotspots, etc. OverStat [JM04,MJB04a,MJB04b] is a collection of decentralized aggregation protocols that compute a broad range of statistical functions, including means, sum, products, counting, variance, etc.


Load-Balancing based on Aggregation

Decentralized aggregation can be used as a building block to obtain a near-optimal load-balancing protocol [JMB04].


Search

Search is a central function for any overlay network.Our research derives inspiration from natural immune systems to improve various aspects of P2P search. In order to improve the performance, we have a two-fold strategy (a) devising a fast propagation scheme of the query message packets, and (b) arranging the peers to form clusters of peers which host similar data so that the search operation can be consequently speeded up. Our aim is to build up a semi-structured P2P network, with the same level of robustness provided by decentralized P2P network, offering however better quality of search service.


Monitoring of performance and management of quality in virtual paths

Path management refers to the finding, establishment, monitoring and maintenance of virtual connection in communication networks. In BISON we have been looking into the use of ant based systems to do path management and monitoring in a distributed fashion. As an example of use, in [HWH05], path management in a Norwegian IP network is studied.

Bibliography

BJM04
Ozalp Babaoglu, Márk Jelasity, and Alberto Montresor.
Grassroots approach to self-management in large-scale distributed systems.
In Proceedings of the EU-NSF Strategic Research Workshop on Unconventional Programming Paradigms, Mont Saint-Michel, France, September 2004.
[PDF], [Bibtex].

JMB04
Márk Jelasity, Alberto Montresor, and Ozalp Babaoglu.
A modular paradigm for building self-organizing peer-to-peer applications.
In Giovanna Di Marzo Serugendo, Anthony Karageorgos, Omer F. Rana, and Franco Zambonelli, editors, Engineering Self-Organising Systems: Nature-Inspired Approaches to Software Engineering, number 2977 in Lecture Notes in Artificial Intelligence, pages 265-282. Springer-Verlag, April 2004.
[PDF], [Bibtex].

VJvS03
Spyros Voulgaris, Márk Jelasity, and Maarten van Steen.
A robust and scalable peer-to-peer gossiping protocol.
In Proceedings of the 2nd International Workshop on Agents and Peer-to-Peer Computing (AP2PC03), Melbourne, Australia, July 2003.
[PDF], [Bibtex].

JGKvS04
Márk Jelasity, Rachid Guerraoui, Anne-Marie Kermarrec, and Maarten van Steen.
The peer sampling service: Experimental evaluation of unstructured gossip-based implementations.
In Proceedings of the 5th International Middleware Conference, Toronto, Canada, October 2004.
[PDF], [Bibtex].

JB05
Márk Jelasity and Ozalp Babaoglu.
T-Man: Gossip-based overlay topology management.
In Proceedings of Engineering Self-Organising Applications (ESOA'05), July 2005.
[PDF], [Bibtex].

MJB05
Alberto Montresor, Márk Jelasity, and Ozalp Babaoglu.
Chord on demand.
In Proceedings of the 5th International Conference on Peer-to-Peer Computing (P2P 2005), pages 87-94, Konstanz, Germany, August 2005. IEEE.
[PDF], [Bibtex].

Mon04
Alberto Montresor.
A robust protocol for building superpeer overlay topologies.
In Proceedings of the 4th International Conference on Peer-to-Peer Computing (P2P 2004), pages 202-209, Zurich, Switzerland, August 2004. IEEE.
[PDF], [Bibtex].

JM04
Márk Jelasity and Alberto Montresor.
Epidemic-style proactive aggregation in large overlay networks.
In Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04), pages 102-109, Tokyo, Japan, March 2004. IEEE Computer Society.
[PDF], [Bibtex].

MJB04a
Alberto Montresor, Márk Jelasity, and Ozalp Babaoglu.
Robust aggregation protocols for large-scale overlay networks.
In Proceedings of the 2004 International Conference on Dependable Systems and Networks (DSN'04), pages 19-28, Florence, Italy, June 2004. IEEE Computer Society.
[PDF], [Bibtex].

MJB04b
Alberto Montresor, Márk Jelasity, and Ozalp Babaoglu.
Decentralized ranking in large-scale overlay networks.
Technical Report UBLCS-2004-18, University of Bologna, Department of Computer Science, Bologna, Italy, December 2004.
[PDF], [Bibtex].

HWH05
Poul E. Heegaard, Otto Wittner, and Bjarne Helvik.
Self-managed virtual path management in dynamic networks.
In Ozalp Babaoglu, Márk Jelasity, Alberto Montresor, Christof Fetzer, Stefano Leonardi, Aad van Moorsel, and Maarten van Steen, editors, Self-Star Properties in Complex Information Systems, volume 3460 of Lecture Notes in Computer Science. Springer-Verlag, 2005.
[PDF], [Bibtex].