Abstract
We study information gathering in ad-hoc radio networks. Initially, each node of the network has a piece of information called a rumor, and the overall objective is to gather all these rumors in the designated target node. The ad-hoc property refers to the fact that the topology of the network is unknown when the computation starts. Aggregation of rumors is not allowed, which means that each node may transmit at most one rumor in one step. We focus on networks with tree topologies, that is we assume that the network is a tree with all edges directed towards the root, but, being ad-hoc, its actual topology is not known. We provide two deterministic algorithms for this problem. For the model that does not assume any collision detection nor acknowledgement mechanisms, we give an \(O(n\log \log n)\)-time algorithm, improving the previous upper bound of \(O(n\log n)\). We then show that this running time can be reduced to O(n), which is asymptotically optimal, if the model allows for acknowledgements of successful transmissions.
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Notes
These structures are also sometimes called strongly k -selective families in the literature.
It needs to be emphasized here that in our model only communication steps contribute to the running time; all calculations are assumed to be instantaneous.
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We would like to thank the anonymous reviewers for multiple comments that helped us improve the paper and for pointing out several references relevant to this work.
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Marek Chrobak was supported by NSF Grants CCF-1217314 and CCF-1536026. Kevin P. Costello was supported by NSA Grant H98230-13-1-0228.
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Chrobak, M., Costello, K.P. Faster Information Gathering in Ad-Hoc Radio Tree Networks. Algorithmica 80, 1013–1040 (2018). https://doi.org/10.1007/s00453-017-0336-y
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DOI: https://doi.org/10.1007/s00453-017-0336-y