Path Algorithms for Contact Sequence Temporal Graphs

Author:

Gheibi Sanaz1,Banerjee Tania1ORCID,Ranka Sanjay1ORCID,Sahni Sartaj1

Affiliation:

1. Department of Computer and Information Sciences and Engineering, University of Florida, Gainesville, FL 32611, USA

Abstract

This paper proposes a new time-respecting graph (TRG) representation for contact sequence temporal graphs. Our representation is more memory-efficient than previously proposed representations and has run-time advantages over the ordered sequence of edges (OSE) representation, which is faster than other known representations. While our proposed representation clearly outperforms the OSE representation for shallow neighborhood search problems, it is not evident that it does so for different problems. We demonstrate the competitiveness of our TRG representation for the single-source all-destinations fastest, min-hop, shortest, and foremost paths problems.

Publisher

MDPI AG

Reference39 articles.

1. Gheibi, S., Banerjee, T., Ranka, S., and Sahni, S. (2021, January 5–8). An Effective Data Structure for Contact Sequence Temporal Graphs. Proceedings of the 2021 IEEE Symposium on Computers and Communications (ISCC), Athens, Greece.

2. Scheideler, C. (2002, January 14–16). Models and techniques for communication in dynamic networks. Proceedings of the Annual Symposium on Theoretical Aspects of Computer Science, Juan les Pins, France.

3. Location updates for efficient routing in ad hoc networks;Stojmenovic;Handb. Wirel. Netw. Mob. Comput.,2002

4. Temporal networks;Holme;Phys. Rep.,2012

5. Liu, Y., Kalagnanam, J.R., and Johnsen, O. (July, January 28). Learning dynamic temporal graphs for oil-production equipment monitoring system. Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France.

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