Title
On utilizing speed in networks of mobile agents
Abstract
Population protocols are a model presented recently for networks with a very large, possibly unknown number of mobile agents having small memory. This model has certain advantages over alternative models (such as DTN) for such networks. However, it was shown that the computational power of this model is limited to semi-linear predicates only. Hence, various extensions were suggested. We present a model that enhances the original model of population protocols by introducing a (weak) notion of speed of the agents. This enhancement allows us to design fast converging protocols with only weak requirements (for example, suppose that there are different types of agents, say agents attached to sick animals and to healthy animals, two meeting agents just need to be able to estimate which of them is faster, e.g., using their types, but not to actually know the speeds of their types). Then, using the new model, we study the gathering problem, in which there is an unknown number of anonymous agents that have values they should deliver to a base station (without replications). We develop efficient protocols step by step searching for an optimal solution and adapting to the size of the available memory. The protocols are simple, though their analysis is somewhat involved. We also present a more involved result - a lower bound on the length of the worst execution for any protocol. Our proofs introduce several techniques that may prove useful also in future studies of time in population protocols.
Year
DOI
Venue
2010
10.1145/1835698.1835775
PODC
Keywords
DocType
Citations 
unknown number,weak requirement,efficient protocols step,original model,new model,involved result,available memory,utilizing speed,mobile agent,alternative model,small memory,population protocol,lower bound,upper bound,base station
Conference
27
PageRank 
References 
Authors
1.00
27
4
Name
Order
Citations
PageRank
Joffroy Beauquier144853.52
Janna Burman212313.55
Julien Clement3271.00
Shay Kutten42118226.75