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A Membership Management Protocol for Mobile P2P Networks

A Membership Management Protocol for Mobile P2P Networks. Mohamed Karim SBAI , Emna SALHI, Chadi BARAKAT. Mobile Ad hoc Networks. Spontaneous multi-hop wireless networks end-to-end communication  ad hoc routing protocols   Without any established infrastructure  

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A Membership Management Protocol for Mobile P2P Networks

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  1. A Membership Management Protocol for Mobile P2P Networks Mohamed Karim SBAI, Emna SALHI, Chadi BARAKAT

  2. Mobile Ad hoc Networks • Spontaneous multi-hop wireless networks • end-to-end communication  ad hoc routing protocols   • Without any established infrastructure   • Nodes play symmetric roles  No dedicated nodes.   • Using wireless channel   • Limited and shared resources  • Mobility  Network splits  

  3. P2P Networks • Peer-to-peer services (as known in the Internet) • Without dedicated devices (servers)   • Peers play symmetric roles  Both clients and servers.   • Can use fixed servers to track the members of the overlay   • The mechanism are not adapted to mobile constrained environments 

  4. Membership Management Protocol for mobile P2P networks • Objective: Maintaining an up-to-date list of the peers interested in the P2P service. • Challenges:- Minimum cost on the underlying network. - Ensuring the continuity of the service.- Having a good level of the freshness of information.

  5. A membership management protocol for P2P services run over MANET ? • Client / Server  • Flooding-based method  • Multicast-based method  • P2P   • Adaptive and optimal P2P method  ?

  6. Membership Management Protocol • Our solution: A fully distributed protocol for constructing and maintaining minimum spanning trees of interested peers. • robust • adaptive • network friendly • decentralized • Algorithms: • Joining the membershiptree • Leaving the membershiptree • Adapting the membership tree to mobility of nodes • Network split awareness

  7. Joining the membership tree • Looking for the nearest peer  a controlled-scope flooding method • Connecting to the nearest peer and getting the current tree from it • Dissemination of the new arrival information on the tree • Changing some connections of the tree considering the cut property of a minimum spanning tree.

  8. Adapting the tree to mobility of nodes • Two peers that are neighbors in the tree can get closer the tree is still optimal. • Two peers that are not neighbors in the spanning tree get farther from each other  the cost of the tree does not change and no better decision can be made. • Two peers that are neighbors in the spanning tree get farther from each other.  The cost of the tree increases  there might exist a better tree. CASE 1 • Two peers that are not neighbors in the spanning tree get closer to each other  It might be another tree with smaller weight. CASE 2

  9. Adapting the tree to mobility of nodes • CASE I = CASE 2 If one of the peers get nearer to another peer in the tree. Else, no optimization can be made. • CASE 2 : Using the cycle property of a minimum spanning tree to elect the logical link to cut.

  10. Leaving the membership tree • The child of the leaving peer having the highest identifier connects to its parent and becomes the parent for the remaining children.  A new spanning tree • The optimal is reached by having the peers apply the normal approaching adaptation procedure.

  11. Network split awareness • Tagging network nodes that are not interested in the same service. • Tracks continuously the appearance of non tagged nodes in its neighborhood. • A new node not tagged and not belonging to the same membership tree is a good candidate to be asked whether it belongs to the same service but comes from another cluster. • Executing a join procedure in case the node is a peer.

  12. Packet format

  13. Performance evaluation • Performance metrics: • Real cost: number of hops message • Cost corrected by freshness of information • NS-2 Simulations scenario : • 50 nodes / Random way point (2ms, 30s) / OLSR routing protocol • exponentiel distribution of ON and OFF times of peers

  14. Performance evaluation Client/server method

  15. Performance evaluation

  16. Performance evaluation

  17. Performance evaluation

  18. Performance evaluation

  19. Performance evaluation

  20. Performance evaluation

  21. Thank You mksbai@sophia.inria.fr

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