Distributed Computing - IWDC 2004: 6th International by Guru Parulkar (auth.), Arunabha Sen, Nabanita Das, Sajal K.

By Guru Parulkar (auth.), Arunabha Sen, Nabanita Das, Sajal K. Das, Bhabani P. Sinha (eds.)

Last, yet now not least, due to all of the members and authors. we are hoping that they loved the workshop up to the fantastic and culturally bright urban of Kolkata! Bhabani P. Sinha Indian Statistical Institute, Kolkata, India December 2004 Sajal okay. Das collage of Texas, Arlington, united states December 2004 application Chairs’ Message On behalf of the Technical software Committee of the sixth foreign Wo- store on dispensed Computing, IWDC 2004, it used to be our nice excitement to w- come the attendees to Kolkata, India. during the last few years, IWDC has emerged as an across the world popular discussion board for interplay between researchers from academia and industries all over the world. a transparent indicator of this truth is the massive variety of top quality submissions of technical papers bought through the workshop this yr. The workshop application consisted of 12 technical classes with fifty four contributed papers, keynote addresses, 4 tutorials, a panel, a poster consultation and the Prof.A.K.ChoudhuryMemorialLecture.TheIWDCProgramCommittee,c- prising 38 wonderful contributors, labored not easy to arrange the technical p- gram. Following a rigorous assessment approach, out of 157 submissions in basic terms fifty four - pers have been permitted for presentation within the technical classes; 27 of the authorised papers have been classi?ed as common papers and the rest 27 as brief papers. one other eleven papers have been permitted for presentation within the poster consultation, every one with a one-page summary showing within the proceedings.

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Extra info for Distributed Computing - IWDC 2004: 6th International Workshop, Kolkata, India, December 27-30, 2004. Proceedings

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Given two weighted directed graphs, we need to find a node-map between the graphs under which the difference between them is minimum among all possible node maps between the two graphs. To quantify the difference between two graphs, we introduce a similarity measure for a pair of weighted directed graphs, Definition 2. S. Paul, A. Gupta, and A. Sharma The factor in the similarity measure implies a relative closeness measure between the corresponding edges. Let be an edge in G and be the corresponding edge (under some node map in H.

Zuva Fig. 3. (b) Case (ii) of Lemma 1 and lay on the same path from the root to a leaf; hence, can be computed as the difference of their distances from the root. (ii) In this case and lay on different paths which intersect in Their distance is easily computed by their distances from the root and from the distance of from the root, possibly equal to 0. (i) Note that, each node knows its distance from and the distance from of each of its neighbors in G (this information can be obtained during the broadcast phase); hence, in the above lemma can be locally computed at In the convergecast phase of Algorithm 1, a node (either a leaf or an internal node) has to be able to locally compute the best feasible swap for an ancestor.

I) Note that, each node knows its distance from and the distance from of each of its neighbors in G (this information can be obtained during the broadcast phase); hence, in the above lemma can be locally computed at In the convergecast phase of Algorithm 1, a node (either a leaf or an internal node) has to be able to locally compute the best feasible swap for an ancestor. b). Lemma 2. Consider a subset and adjacent to edge for and for and of the ancestors of with Furthermore, let be a feasible swap Consider the two trees then, Proof.

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