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Internet Engineering Task Force                              O. Kassinen
Internet-Draft                                                T. Koskela
Intended status: Informational                                E. Harjula
Expires: September 2, 2010                                 M. Ylianttila
                                                      University of Oulu
                                                           March 1, 2010


              Taxonomy for P2P Group Management Solutions
              draft-kassinen-p2psip-group-taxonomy-00.txt

Abstract

   We analyze existing or proposed P2P group management solutions.
   Based on the analysis, we present a comprehensive taxonomy for the
   solutions.  The highest level of the taxonomoy classifies the P2P
   group management solutions according to their motivation, group-
   forming criteria, methods for applying the criteria, and technical
   realization.

Status of this Memo

   This Internet-Draft is submitted to IETF in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
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   This Internet-Draft will expire on September 2, 2010.

Copyright Notice

   Copyright (c) 2010 IETF Trust and the persons identified as the
   document authors.  All rights reserved.




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   This document is subject to BCP 78 and the IETF Trust's Legal
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   (http://trustee.ietf.org/license-info) in effect on the date of
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   described in the BSD License.


Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
     1.1.  Requirements Language  . . . . . . . . . . . . . . . . . .  3
   2.  Existing Example Solutions for P2P Group Management  . . . . .  3
     2.1.  Solution 1: "HIERAS: A DHT Based Hierarchical P2P
           Routing Algorithm" . . . . . . . . . . . . . . . . . . . .  3
     2.2.  Solution 2: "Trust-Based Community Formation in
           Peer-to-Peer File Sharing Networks"  . . . . . . . . . . .  4
     2.3.  Solution 3: "Service-Driven Group Management for
           Mobile P2P Services" . . . . . . . . . . . . . . . . . . .  4
     2.4.  Solution 4: "A Utility-Aware Middleware Architecture
           for Decentralized Group Communication Applications"  . . .  4
     2.5.  Solution 5: "PP-COSE: A P2P Community Search Scheme" . . .  4
     2.6.  Solution 6: "An Interest Group Model for Content
           Location in Peer-to-Peer Systems"  . . . . . . . . . . . .  5
   3.  The Taxonomy . . . . . . . . . . . . . . . . . . . . . . . . .  5
     3.1.  The Four High-Level Properties . . . . . . . . . . . . . .  5
     3.2.  Categories under the Four Properties . . . . . . . . . . .  6
       3.2.1.  Categories of Motivation . . . . . . . . . . . . . . .  7
       3.2.2.  Categories of Criteria . . . . . . . . . . . . . . . .  7
       3.2.3.  Categories of Methods  . . . . . . . . . . . . . . . .  7
       3.2.4.  Categories of Realization  . . . . . . . . . . . . . .  8
   4.  Using the Taxonomy for the Classification of the Example
       Solutions  . . . . . . . . . . . . . . . . . . . . . . . . . .  9
   5.  IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 10
   6.  Security Considerations  . . . . . . . . . . . . . . . . . . . 10
   7.  References . . . . . . . . . . . . . . . . . . . . . . . . . . 10
     7.1.  Normative References . . . . . . . . . . . . . . . . . . . 10
     7.2.  Informative References . . . . . . . . . . . . . . . . . . 11
   Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . . 11









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1.  Introduction

   Several "group" management solutions exist, or have been proposed,
   for peer-to-peer (P2P) networking.

   We have done (in 2010) a literature review of more than 50
   publications about P2P group management solutions.  The literature
   review will be published in a separate research article.

   In this Internet-Draft,

   o  we select from those P2P group management solutions a subset that
      attempts to represent well the versatility of the solutions; and

   o  we propose a simple taxonomy that covers well the P2P group
      management solutions (both the selected subset and the entire body
      of the 50+ reviewed solutions), facilitating the classification of
      the solutions and providing an easy way to overview the properties
      of the existing or proposed solutions.

1.1.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].

   Community: A term for a group, emphasizing that the group's members
   are humans (or the personal network access devices of the humans) who
   are somehow related and can thus be considered a community.

   Group: A group of nodes within a P2P network.  There are many
   different definitions for a group in the various existing
   publications.


2.  Existing Example Solutions for P2P Group Management

   In this section we provide short descriptions about the six selected
   P2P group management solutions.  The six solutions are original
   inventions of different authors.

2.1.  Solution 1: "HIERAS: A DHT Based Hierarchical P2P Routing
      Algorithm"

   In [Paper 1], in a system called HIERAS, the nodes in the P2P network
   are grouped into several Distributed Hash Table (DHT) based overlay
   networks.  Several lower level overlays are created in addition to
   the highest level overlay.  The average link latency between nodes is



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   much lower in the lower level overlays than in the highest level
   overlay, and this is taken into account when selecting nodes to a
   group.  Routing actions are first executed in the lower level
   overlays.  The goal is to improve routing performance.

2.2.  Solution 2: "Trust-Based Community Formation in Peer-to-Peer File
      Sharing Networks"

   In [Paper 2], a mechanism for creating P2P groups for sharing
   academic papers is proposed.  The system creates (software) agents,
   which keep track of the similarity of the ratings of the papers and
   form trusted agent groups in the P2P network.  Agents represent their
   (human) users; the system forms interest-based communities between
   the users.  There are trust measures for individual agents and groups
   of agents.  Each agent must compute the trust in the agents that it
   interacts with.

2.3.  Solution 3: "Service-Driven Group Management for Mobile P2P
      Services"

   In [Paper 3], a peer group management solution based on service
   semantics and resource availability is proposed.  The system is
   designed for mobile peers.  The system involves a centralized server,
   which holds a service schema influencing the way how peers are
   dynamically grouped; super peers, which are linked together by the
   server and act as routing and data-advertisement hubs; and ordinary
   peers, which hold the actual shared content.  The number of overlay
   network levels is determined by service semantics.

2.4.  Solution 4: "A Utility-Aware Middleware Architecture for
      Decentralized Group Communication Applications"

   In [Paper 4], a utility-aware middleware architecture called
   GroupCast for scalable P2P communications is presented.  A utility
   function is presented for quantifying the role of unicast links in
   the network.  A utility-aware distributed spanning tree construction
   algorithm is presented for implementing efficient message
   dissemination in group communication, aiming optimizing the utility
   values of the spanning trees.  Also a utility-aware low-diameter
   unstructured-overlay construction protocol is outlined.  The
   objective of utility-aware overlay construction is that in the
   resulting network, the neighbors of a node have a high utility with
   respect to the node.

2.5.  Solution 5: "PP-COSE: A P2P Community Search Scheme"

   In [Paper 5], a system called PP-COSE is introduced for making peer
   searching efficient.  The P2P system is formed by clusters.  For each



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   cluster, there exists a node called the search router.  The nodes of
   a cluster register to the search router.  The search routers act as
   community managers and provide message routing.  Communities in the
   system are a different concept from the clusters: community
   membership is not bound to cluster membership.  A filter function
   exists to reduce the amount of overhead traffic: unpopular
   communities are filtered out.  Clustering can be based on
   organizational or geographical areas.

2.6.  Solution 6: "An Interest Group Model for Content Location in Peer-
      to-Peer Systems"

   In [Paper 6], a probabilistic decision tree is used for representing
   the users' interests.  Based on the tree, peers with common interests
   are organized into the same group.  Probabilistic decision trees are
   used for representing a user's interests, because the interests
   typically change over time.  The system uses a standard probability
   tree accepted by a majority of users instead of creating a new tree
   for each user.  The aim is to make searches more efficient in
   unstructured P2P networks.  When searching for content, the query is
   first propagated in the interest group, and only if the content is
   not found there, then the query is flooded outside the group.


3.  The Taxonomy

   Based on the analysis of the 50+ existing or proposed P2P group
   management solutions, we present a taxonomy that is suitable for
   classifying the solutions on a suitable level of detail.

3.1.  The Four High-Level Properties

   In the presented taxonomy, the following four high-level properties
   are distinguished for a given P2P group management solution.

   o  Motivation: The reason why groups are formed.

   o  Criteria: The criteria that are used for selecting nodes to a
      specific group.  The criteria are, of course, dependent on the
      motivation.

   o  Methods: The algorihms or other methods for observing and
      evaluating the criteria, leading to the selection of nodes to a
      specific group.

   o  Realization: The kind of underlying P2P network that is used as a
      basis for the solution and enables the running of the specified
      methods.



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   All four high-level properties should be identified for a given P2P
   group management solution.  However, some properties might not be in
   the focus of a given solution (i.e., are not presented in the
   publication), so only a sub-set of the four properties might be
   defined.  In some cases, a publication may also state that some
   aspect of a solution can be implemented with several different means;
   this applies usually to the properties "Method" and "Realization".

   The relationship between the high-level properties is illustrated in
   Figure 1.

                         +-----------------------+
                         |      Motivation       |
                         +-----------------------+
                                    |
                                 defines
                                    |
                                    v
                         +-----------------------+
                         |       Criteria        |
                         +-----------------------+
                                    |
                            are evaluated with
                                    |
                                    v
                         +-----------------------+
                         |        Methods        |
                         +-----------------------+
                                    |
                              work on top of
                                    |
                                    v
                         +-----------------------+
                         |      Realization      |
                         +-----------------------+

                              Classification.

                                 Figure 1

3.2.  Categories under the Four Properties

   In this section, we list the different categories that we have
   observed to exist under the four high-level properties.

   A given P2P group management solution may exhibit the characteristics
   of one or more categories within a high-level property.




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3.2.1.  Categories of Motivation

   o  Search Efficiency: The efficiency of routing in the P2P network or
      (a more specific case) the efficiency of resource searching.

   o  Group Communication: The ability to communicate in a suitable
      group (of human users).

   o  Service Provisioning: Publishing and discovery of services on top
      of a P2P system.

   o  Knowledge Sharing and Collaboration: The ability to share
      important information and collaborate in the context of specific
      tasks, often in a professional setting.

   o  Trust, Security and Privacy Management: Enhance the trust,
      security, and/or privacy in P2P operations.

3.2.2.  Categories of Criteria

   o  Common Interests: The members (humans) of a community share some
      common interests, related to e.g. content.

   o  Node Capability: The terminal devices' capabilities such as CPU
      power or memory.

   o  Level of Trust: How strong is the trust between the users (or
      nodes).

   o  Social and Organizational Memberships: Membership in a social
      group or organization.

   o  Locality:

      *  Physical: How near the nodes are to each other, in terms of
         network latency or other physical network-related metric.

      *  Logical: How near the nodes are to each other, in terms of hop-
         count or other logical network-related metric.

      *  Geographical: How near the nodes are to each other, in terms of
         geographical distance.

3.2.3.  Categories of Methods

   o  Ontology Matching: There exists a suitable ontology, which is used
      for finding similarities between nodes.




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   o  Link Analysis: Based on the observed interaction between nodes,
      patterns of interaction are identified.

   o  Attribute Comparison: The non-technical attributes of nodes are
      compared for finding similarities between nodes.  These attributes
      might include, for example, interests.

   o  Statistical Comparison: Some characteristics of nodes are compared
      with a statistical approach in order to find similarities.

   o  Analysis of Node and Network Performance: The technical attributes
      of nodes or the used network are compared, usually for making the
      network operations more efficient, for example, by minimizing
      latencies.

   o  Usage of Membership Credentials: Digital credentials are delivered
      to the members of a group and checked when needed.

3.2.4.  Categories of Realization

   o  Single Overlay: The group or groups are created within a single
      overlay; the entire system contains only one overlay network.

      *  Structured (DHT): The organization and operation of the overlay
         is based on mathematical rules, usually on Distributed Hash
         Tables (DHT).

      *  Unstructured: The organization and operation of the overlay is
         based on some "less exact" rules.

         +  Pure: The system is completely flat (example: Gnutella 0.4),
            and each node has equal responsibilities.

         +  Hierarchical: There is some structuring, such as edge-peer
            vs. super-peer distinction (example: JXTA).

   o  Multi-overlay: The group or groups are created using multiple
      overlays; the entire system contains multiple overlay networks
      that can be either structured, unstructured, or both.  Multi-
      overlay-based solutions can be further classified to:

      *  Vertical: A vertical system is usually described as a tree,
         where every layer or leaf is an independent DHT overlay
         network.  In the vertical approach, some nodes usually act as
         gatekeepers routing the messages between the different levels
         in the DHT hierarchy.





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      *  Horizontal: All the leaf overlays are connected to a single
         common DHT overlay that is responsible for optimizing the
         routing in the whole network.  Furthermore, the DHT overlay
         also possesses the functionality and policies how to control
         the hierarchy of overlays.  The different leaf overlays can
         either be structured or unstructured P2P networks.


4.  Using the Taxonomy for the Classification of the Example Solutions

   In this section, we apply the taxonomy to the example P2P group
   management solutions that we discussed earlier.

   o  The solution in [Paper 1] has the properties:

      *  Motivation: Search Efficiency.

      *  Criteria: Locality.

      *  Methods: Analysis of Node and Network Performance.

      *  Realization: Multi-overlay, DHT.

   o  The solution in [Paper 2] has the properties:

      *  Motivation: Knowledge Sharing and Collaboration; Trust,
         Security and Privacy Management (more specifically: Trust
         Management).

      *  Criteria: Common Interests; Level of Trust.

      *  Methods: Attribute Comparison.

      *  Realization: Unstructured, Hierarchical.

   o  The solution in [Paper 3] has the properties:

      *  Motivation: Service Provisioning.

      *  Criteria: Common Interests; Node Capability.

      *  Methods: Ontology-matching.

      *  Realization: Multi-overlay.

   o  The solution in [Paper 4] has the properties:





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      *  Motivation: Group Communication.

      *  Criteria: Locality; Node Capability.

      *  Methods: Analysis of Node and Network Performance.

      *  Realization: Unstructured.

   o  The solution in [Paper 5] has the properties:

      *  Motivation: Search Efficiency.

      *  Criteria: Social and Organizational Memberships; Locality.

      *  Methods: Analysis of Node and Network Performance; Usage of
         Membership Credentials.

      *  Realization: Unstructured, Hierarchical.

   o  The solution in [Paper 6] has the properties:

      *  Motivation: Search Efficiency; Knowledge Sharing and
         Collaboration.

      *  Criteria: Common Interests.

      *  Methods: Statistical Comparison.

      *  Realization: Unstructured.


5.  IANA Considerations

   This memo includes no request to IANA.


6.  Security Considerations

   This draft does not introduce any new security issues.


7.  References

7.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, March 1997.




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7.2.  Informative References

   [Paper 1]  Xu, Z., Min, R., and Y. Hu, "HIERAS: A DHT Based
              Hierarchical P2P Routing Algorithm", 2003 International
              Conference on Parallel Processing (ICPP 2003),
              October 2003.

   [Paper 2]  Wang, Y. and J. Vassileva, "Trust-Based Community
              Formation in Peer-to-Peer File Sharing Networks", 2004
              IEEE/WIC/ACM International Conference on Web
              Intelligence (WI 2004), September 2004.

   [Paper 3]  Liotta, A., Ballette, M., Lin, L., Gasparoni, M., Brick,
              P., and N. Papadoglou, "Service-Driven Group Management
              for Mobile P2P Services", Intelligence in Communication
              Systems, Vol. 190/2005, pp. 221--230, October 2005.

   [Paper 4]  Zhang, J., Liu, L., Ramaswamy, L., Zhang, G., and C. Pu,
              "A Utility-Aware Middleware Architecture for Decentralized
              Group Communication Applications", ACM/IFIP/USENIX 2007
              International Conference on Middleware (Middleware 2007),
              November 2007.

   [Paper 5]  Mei, H. and S. Chang, "PP-COSE: A P2P Community Search
              Scheme", Fourth International Conference on Computer and
              Information Technology (CIT 2004), September 2004.

   [Paper 6]  Xue, G., You, J., and Z. Jia, "An Interest Group Model for
              Content Location in Peer-to-Peer Systems", IEEE
              International Conference on E-Commerce Technology for
              Dynamic E-Business (CEC-East 2004), September 2004.


Authors' Addresses

   Otso Kassinen
   University of Oulu
   Oulu,
   Finland

   Phone: +358 8 553 1011
   Email: firstname.lastname@ee.oulu.fi









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   Timo Koskela
   University of Oulu
   Oulu,
   Finland

   Phone: +358 8 553 1011
   Email: firstname.lastname@ee.oulu.fi


   Erkki Harjula
   University of Oulu
   Oulu,
   Finland

   Phone: +358 8 553 1011
   Email: firstname.lastname@ee.oulu.fi


   Mika Ylianttila
   University of Oulu
   Oulu,
   Finland

   Phone: +358 8 553 1011
   Email: firstname.lastname@ee.oulu.fi


























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