Search Algorithms for Distributed Data Structures in P2P Networks

The search problem in distributed systems has been evaluated and various proposals have been made to solve them. The problem is particularly pronounced when considering P2P networks, because the different types of P2P network topologies used to dictate the search mechanisms that are used. Specifically, search mechanisms may be key-based, as in structured P2P networks that use distributed data structures such as Distributed Hash Tables (DHTs), Sets, Links, and Trees, or keyword-based for unstructured P2P networks. Online systems today utilize metadata to support search algorithms. Metadata searches are trivial in unstructured networks but are a challenge to the structured networks because of the distributed data structures (DDS). This work proposes to introduce algorithms that support metadata searches in structured P2P networks that utilize DHT overlays. DDSs are introduced into the system as storage layers that support complex data structures. We show that this can be done and searching can be achieved with acceptable performance.

[1]  Jean-Marc Nicod,et al.  The Distributed Spanning Tree Structure , 2009, IEEE Transactions on Parallel and Distributed Systems.

[2]  S.-H. Gary Chan,et al.  Distributed Hash Tables: Design and Applications , 2010 .

[3]  Jamie Callan,et al.  DISTRIBUTED INFORMATION RETRIEVAL , 2002 .

[4]  Kyoung Soo Bok,et al.  Cooperative Caching for Efficient Data Search in Mobile P2P Networks , 2017, Wirel. Pers. Commun..

[5]  Hui Zhang,et al.  Global network positioning: a new approach to network distance prediction , 2002, CCRV.

[6]  Mehdi Safari,et al.  Metadata and the Web , 2004, Webology.

[7]  Takashige Hoshiai,et al.  Decentralized Meta-Data Strategies: Effective Peer-to-Peer Search , 2003 .

[8]  Kalman Graffi,et al.  Distributed data structures improvement for collective retrieval time , 2016, 2016 19th International Symposium on Wireless Personal Multimedia Communications (WPMC).

[9]  David R. Karger,et al.  Looking up data in P2P systems , 2003, CACM.

[10]  Taoufik En-Najjary,et al.  Long Term Study of Peer Behavior in the kad DHT , 2009, IEEE/ACM Transactions on Networking.

[11]  David R. Karger,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM '01.

[12]  Adir Even,et al.  The metadata enigma , 2006, CACM.

[13]  Patrick Valduriez,et al.  Data currency in replicated DHTs , 2007, SIGMOD '07.

[14]  Sonja Buchegger,et al.  A case for P2P infrastructure for social networks - opportunities & challenges , 2009, 2009 Sixth International Conference on Wireless On-Demand Network Systems and Services.

[15]  Antony I. T. Rowstron,et al.  PAST: a large-scale, persistent peer-to-peer storage utility , 2001, Proceedings Eighth Workshop on Hot Topics in Operating Systems.

[16]  Tim Moors,et al.  Survey of Research towards Robust Peer-to-Peer Networks: Search Methods , 2007, RFC.

[17]  J. Crawford,et al.  Setting the stage. , 2021, The New England journal of medicine.

[18]  Reginald L. Lagendijk,et al.  Distributed Content Based Video Identification in Peer-to-Peer Networks: Requirements and Solutions , 2017, IEEE Transactions on Multimedia.

[19]  Kalman Graffi,et al.  Comparative evaluation of peer-to-peer systems using PeerfactSim.KOM , 2013, 2013 International Conference on High Performance Computing & Simulation (HPCS).

[20]  Kalman Graffi,et al.  Sets, lists and trees: Distributed data structures on distributed hash tables , 2016, 2016 IEEE 35th International Performance Computing and Communications Conference (IPCCC).

[21]  Kalman Graffi.  PeerfactSim.KOM: A P2P system simulator — Experiences and lessons learned , 2011, 2011 IEEE International Conference on Peer-to-Peer Computing.

[22]  Sam Joseph,et al.  P2P MetaData Search Layers , 2003, AP2PC.