The power of adaptivity in source identification with time queries on the path
Theoretical Computer Science, ISSN: 0304-3975, Vol: 911, Page: 92-123
2022
- 3Citations
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Article Description
We study the problem of identifying the source of a stochastic diffusion process spreading on a graph based on the arrival times of the diffusion at a few queried nodes. In a graph G=(V,E), an unknown source node v⁎∈V is drawn uniformly at random, and unknown edge weights w(e) for e∈E, representing the propagation delays along the edges, are drawn independently from a Gaussian distribution of mean 1 and variance σ2. An algorithm then attempts to identify v⁎ by querying nodes q∈V and being told the length of the shortest path between q and v⁎ in graph G weighted by w. We consider two settings: non-adaptive, in which all query nodes must be decided in advance, and adaptive, in which each query can depend on the results of the previous ones. Both settings are motivated by an application of the problem to epidemic processes (where the source is called patient zero), which we discuss in detail. We characterize the query complexity when G is an n -node path. In the non-adaptive setting, Θ(nσ2) queries are needed for σ2≤1, and Θ(n) for σ2≥1. In the adaptive setting, somewhat surprisingly, only Θ(loglog1/σn) are needed when σ2≤1/2, and Θ(loglogn)+Oσ(1) when σ2≥1/2. This is the first mathematical study of source identification with time queries in a non-deterministic diffusion process.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0304397522000901; http://dx.doi.org/10.1016/j.tcs.2022.02.008; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85125803030&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0304397522000901; https://dx.doi.org/10.1016/j.tcs.2022.02.008
Elsevier BV
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