DocumentCode :
70505
Title :
How to Make Network Nodes Adaptive?
Author :
Guozhen Cheng ; Hongchang Chen ; Shuqiao Chen ; Hongchao Hu ; Peng Yi
Author_Institution :
Nat. Digital Switching Syst. Eng. & Technol. R&D Center, Zhengzhou, China
Volume :
18
Issue :
3
fYear :
2014
fDate :
Mar-14
Firstpage :
515
Lastpage :
518
Abstract :
The current Internet lacks in adaptability fueling the great interest in defining a new network architecture that can meet the needs of a future Internet. One of the prevailing trends in this context is re-splitting the network function into fine granularity build blocks to breaking through the network ossification and realizing the network functional composition for enhancing network adaptability. In our work, we propose a novel adaptive architecture, i.e., ReNet, differing from existing solutions, which re-abstracts the current protocol stack at special location, and decompose the network and transport layers into the atomic capacities which is finer functional building blocks, and open the network core for adding new building blocks. Then, a nonlinear integer optimal problem is formulated for the composition of atomic capacities driven by users´ requests, with the proposed algorithm to reach appropriate tradeoff between optimal solution and computation cost. Numerical results demonstrate our algorithm can combine the atomic capacities in a feasible scale between cost and optimization. Finally, we give a proof-of-concept paradigm.
Keywords :
Internet; optimisation; protocols; Internet; ReNet; adaptive network nodes; network architecture; network layers; network ossification; nonlinear integer optimal problem; protocol stack; transport layers; Adaptive systems; Atomic layer deposition; Computer architecture; Internet; Optimization; Protocols; Quality of service; Network architecture; functional decomposition; network composition;
fLanguage :
English
Journal_Title :
Communications Letters, IEEE
Publisher :
ieee
ISSN :
1089-7798
Type :
jour
DOI :
10.1109/LCOMM.2014.011714.132622
Filename :
6784560
Link To Document :
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