New theoretical studies and optimal cluster-population determination for hierarchical networks

Authors:
Shih Yu Chang;Hsiao-Chun Wu;Yiyan Wu;Ai-Chun Pang
Affiliations:
Department of Computer Science, National Tsing Hua University, Taiwan;Department of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA;Department of Television Networks and Transmision, Communications Research Centre, Ottawa, Ontario, Canada;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan
Venue:
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Year:
2009

Citing 6
Cited 0

Establishing virtual circuits in large computer networks

Computer Networks and ISDN Systems
An Adaptive Hierarchical Routing Protocol

IEEE Transactions on Computers
A path-finding algorithm for loop-free routing

IEEE/ACM Transactions on Networking (TON)
Optimization of hierarchical routing protocols

Performance Evaluation - Special issue: ATM networks: Performance modelling and analysis
Loop-Free Internet Routing Using Hierarchical Routing Trees

INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
Ad-hoc Networks: Fundamental Properties and Network Topologies

Ad-hoc Networks: Fundamental Properties and Network Topologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

In order to decrease the overhead of the dynamic routing mechanisms in large networks, the hierarchical routing protocols have been proposed in the early 80's. The routing complexity and the routing table size are the two most important functional blocks in a dynamic route guidance system. Although various algorithms exist for finding the best routing policy on a hierarchical network, hardly exists any work in studying and evaluating the aforementioned measures of routing complexity and routing table size for a hierarchical network. In this paper, by applying the random geometry theory, we can generalize the mathematical framework from the previous work which discussed the worst-case deterministic models. Our proposed new framework can carry out the averages of the routing complexity and the routing table size, which can be specified as the functions of the hierarchical network parameters such as the number of the hierarchical levels and the subscriber densities (cluster-population) for each hierarchical level. After establishing the relationship between the structure of a hierarchical network and these two crucial network performance measures (routing complexity and routing table size), we present a novel cluster-population optimization method for hierarchical networks and the associated statistical analysis.