Theoretical Computer Science
The complexity of searching a graph
Journal of the ACM (JACM)
Recontamination does not help to search a graph
Journal of the ACM (JACM)
The vertex separation and search number of a graph
Information and Computation
Capture of an intruder by mobile agents
Proceedings of the fourteenth annual ACM symposium on Parallel algorithms and architectures
Contiguous Search in the Hypercube for Capturing an Intruder
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Distributed chasing of network intruders
SIROCCO'06 Proceedings of the 13th international conference on Structural Information and Communication Complexity
Cleaning an arbitrary regular network with mobile agents
ICDCIT'05 Proceedings of the Second international conference on Distributed Computing and Internet Technology
The cost of monotonicity in distributed graph searching
OPODIS'07 Proceedings of the 11th international conference on Principles of distributed systems
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In this paper we consider the problem of capturing an intruder in a networked environment. The intruder is defined as a mobile entity that moves arbitrarily fast inside the network and escapes from a team of software agents. The agents have to collaborate and coordinate their moves in order to isolate the intruder. They move asynchronously and they know the network topology they are in is a particular fractal graph, the Sierpiski graph SGn. We first derive lower bounds on the minimum number of agents, number of moves and time steps required to capture the intruder. We then consider two models: one in which agents have a capability, of "seeing" the state of their neighbors; the second one in which the actions of the agents are leaded by a coordinator. One of our goals is to continue a previous study on what is the impact of visibility on complexity: we have found that in this topology the visibility assumption allows us to reach an optimal bound on the number of agents required for the cleaning strategy. On the other hand, the second strategy relies only on local computations but requires an extra agent and a higher (by a constant) complexity in terms of time and number of moves.