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New dynamic SPT algorithm based on a ball-and-string model
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Source IEEE/ACM Transactions on Networking (TON) archive
Volume 9 ,  Issue 6  (December 2001) table of contents
Pages: 706 - 718  
Year of Publication: 2001
ISSN:1063-6692
Authors
Paolo Narváez  Raza Foundries, Inc., San Jose, CA
Kai-Yeung Siu  Raza Foundries, Inc., San Jose, CA
Hong-Yi Tzeng  Nokia, Mountain View, CA
Publisher
IEEE Press  Piscataway, NJ, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 50,   Citation Count: 5
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DOI Bookmark: 10.1109/90.974525

ABSTRACT

A key functionality in today's widely used interior gateway routing protocols such as OSPF and IS-IS involves the computation of a shortest path tree (SPT). In many existing commercial routers, the computation of an SPT is done from scratch following changes in the link states of the network. As there may coexist multiple SPTs in a network with a set of given link states, such recomputation of an entire SPT not only is inefficient but also causes frequent unnecessary changes in the topology of an existing SPT and creates routing instability.This paper presents a new dynamic SPT algorithm that makes use of the structure of the previously computed SPT. Our algorithm is derived by recasting the SPT problem into an optimization problem in a dual linear programming framework, which can also be interpreted using a ball-and-string model. In this model, the increase (or decrease) of an edge weight in the tree corresponds to the lengthening (or shortening) of a string. By stretching the strings until each node is attached to a tight string, the resulting topology of the model defines an (or multiple) SPT(s). By emulating the dynamics of the ball-and-string model, we can derive an efficient algorithm that propagates changes in distances to all affected nodes in a natural order and in a most economical way. Compared with existing results, our algorithm has the best-known performance in terms of computational complexity as well as minimum changes made to the topology of an SPT. Rigorous proofs for correctness of our algorithm and simulation results illustrating its complexity are also presented.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Paolo Narváez: colleagues
Kai-Yeung Siu: colleagues
Hong-Yi Tzeng: colleagues

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