DocumentCode :
3564712
Title :
Network Modeling for Improving Scalability Using Graph Contraction Scheme
Author :
Joon Heo ; Taehwan Kim
Author_Institution :
Nat. Inst. for Math. Sci., Daejeon, South Korea
fYear :
2014
Firstpage :
428
Lastpage :
433
Abstract :
The objective of this work is to suggest the self-organizing algorithm by communication nodes with topological information. This paper describes the noble concept of future Internet architecture, graph contraction based self-organizing networks and the topology-aware address. The proposed network principle abstracts logical layers from large-scale physical networks with topological characteristic of nodes and defines the address of nodes by hierarchical logical layers. This concept can be a solution of some problems of current Internet such as scalability, mobility and the rapid increase of the routing table size. To validate proposed network model, we implemented network simulator focusing on self-organizing with proposed graph contraction algorithm and analyzed the proposed architecture. This simulator can show the organizing process and the allocation of topology-aware address through the three-dimensional windows and 3D viewer.
Keywords :
Internet; graph theory; network theory (graphs); telecommunication network routing; telecommunication network topology; 3D viewer; Internet architecture; communication nodes; graph contraction algorithm; graph contraction scheme; hierarchical logical layers; large-scale physical networks; network modeling; network principle abstracts logical layers; network simulator; routing table size; scalability improvement; self-organizing networks; three-dimensional windows; topological information; topology-aware address allocation; Heuristic algorithms; Internet; Mathematical model; Network topology; Organizing; Scalability; Topology; Simulator; graph theory; network modeling; topology-aware architecture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Modelling and Simulation (UKSim), 2014 UKSim-AMSS 16th International Conference on
Print_ISBN :
978-1-4799-4923-6
Type :
conf
DOI :
10.1109/UKSim.2014.53
Filename :
7046104
Link To Document :
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