Abstract
Many of the methods that are used to optimize network structure for information sharing are centralized, which is not always desirable in practice. Often, it is only feasible to have the communicating actors modify the network locally, i.e., without relying on the knowledge of the entire network structure. Such a requirement typically arises in establishing communication between actors (e.g., Unmanned Aerial Vehicles) that either do not have access to a central hub or prefer not to use this direct transmission channel even if available. This paper adopts an actor-oriented modeling approach to develop the Decentralized Deterministic Information Propagation (DDIP) model that enables the creation of networks that exhibit the properties desirable for efficient information sharing. Computational experiments showcase the ability of the DDIP model to form robust networks while being energy-conscious, i.e., without unnecessarily overloading any particular actor.
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Acknowledgments
This work was funded in part by the AFRL Mathematical Modeling and Optimization Institute, by the National Science Foundation Award No. 1635611, and by the U.S. Air Force Summer Faculty Fellowship (granted to the second author by the Air Force Office of Scientific Research).
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Diaz, C., Nikolaev, A., Pasiliao, E. (2018). A Decentralized Deterministic Information Propagation Model for Robust Communication. In: Chen, X., Sen, A., Li, W., Thai, M. (eds) Computational Data and Social Networks. CSoNet 2018. Lecture Notes in Computer Science(), vol 11280. Springer, Cham. https://doi.org/10.1007/978-3-030-04648-4_20
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