Volume 119, Number 4, August 2017
|Number of page(s)||7|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||06 November 2017|
Hunting for a moving target on a complex network
1 HKUST-DT System and Media Laboratory, Hong Kong University of Science and Technology 999077, Hong Kong
2 Institute of Science and Technology for Brain-Inspired Intellegence, Fudan University - Shanghai 200433, China
3 The University of Western Australia - Crawley, WA 6009, Australia
4 Mineral Resources, CSIRO - Kensington, WA 6009, Australia
Received: 20 July 2017
Accepted: 12 October 2017
Random searching for a mobile target is frequently encountered in many real situations, posing great challenges for theoretical analysis which traditionally deals only with static targets. We investigate mobile-object search on networks in which the target's location is changing with time. We adopt mean first-encounter time to quantify the search time a searcher takes to capture a time-moving target and derive its analytical expression, when it exists. Interestingly, we observe an entirely distinct behavior for a mobile-object search compared to traditional results with a static target. Counter-intuitively, we find that compared with searching for a static target, a mobile object is easier to be captured under the same circumstances. Furthermore, we demonstrate that staying at the hub node is the optimal strategy for hunting for a mobile object on a heterogeneous network. Our findings reveal distinct effects for a mobile object on both search and transport.
PACS: 89.75.Hc – Networks and genealogical trees / 05.40.Fb – Random walks and Levy flights / 05.60.Cd – Classical transport
© EPLA, 2017
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.