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J.K. Antonio, G.M. Huang, W.K. Tsai, "A Fast Distributed Shortest Path Algorithm for a Class of Hierarchically Clustered Data Networks," IEEE Transactions on Computers, vol. 41, no. 6, pp. 710724, June, 1992.  
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@article{ 10.1109/12.144623, author = {J.K. Antonio and G.M. Huang and W.K. Tsai}, title = {A Fast Distributed Shortest Path Algorithm for a Class of Hierarchically Clustered Data Networks}, journal ={IEEE Transactions on Computers}, volume = {41}, number = {6}, issn = {00189340}, year = {1992}, pages = {710724}, doi = {http://doi.ieeecomputersociety.org/10.1109/12.144623}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Computers TI  A Fast Distributed Shortest Path Algorithm for a Class of Hierarchically Clustered Data Networks IS  6 SN  00189340 SP710 EP724 EPD  710724 A1  J.K. Antonio, A1  G.M. Huang, A1  W.K. Tsai, PY  1992 KW  shortest path algorithm; hierarchically clustered data networks; singledestination shortest path; allpairs shortest path; computational complexity; graph theory; parallel algorithms. VL  41 JA  IEEE Transactions on Computers ER   
A distributed algorithm is presented that can be used to solve the singledestination shortest path (SDSP) problem or the allpairs shortest path (APSP) problem for a class of clustered data networks. The network graph is assumed to be characterized with a balanced hierarchically clustered (BHC) topology. The BHC topology is introduced in this paper and is shown to be a realistic characterization for a large class of interconnected data networks. For certain types of BHC topologies, the SDSP problem can be solved with computation and communication time complexities of O(log n), assuming one processor is available at each of the n number of nodes. Assuming p processors are available at each node, computation and communication time complexities of O((n/p) log n) and O(n log n) are achievable, respectively, for solving the APSP problem. It is also shown that the algorithm converges in an asynchronous environment.
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