Title
Entropy-Based Framework for Dynamic Coverage and Clustering Problems
Abstract
We propose a computationally efficient framework to solve a large class of dynamic coverage and clustering problems, ranging from those that arise from deployment of mobile sensor networks to classification of cellular data for diagnosing cancer stages. This framework provides the ability to identify natural clusters in the underlying data set. In particular, we define the problem of minimizing instantaneous coverage as a combinatorial optimization problem in a Maximum Entropy Principle (MEP) framework that we formulate specifically for the dynamic setting, and which allows us to address inherent tradeoffs such as those between the resolution of the identified clusters and computational cost. The proposed MEP framework addresses both the coverage and the tracking aspects of these problems. Locating cluster centers of swarms of moving objects and tracking them is cast as a control design problem ensuring that the algorithm achieves progressively better coverage with time. Simulation results are presented that highlight the features of this framework; these results demonstrate that the proposed algorithm attains target coverage costs five to seven times faster than related frame-by-frame methods.
Year
DOI
Venue
2012
10.1109/TAC.2011.2166713
Automatic Control, IEEE Transactions
Keywords
Field
DocType
combinatorial mathematics,maximum entropy methods,optimisation,pattern clustering,MEP framework,cancer stage diagnosis,cellular data classification,clustering problem,combinatorial optimization problem,dynamic coverage,entropy-based framework,maximum entropy principle,mobile sensor network,Maximum entropy principle (MEP)
Cluster (physics),Data mining,Mathematical optimization,Software deployment,Algorithm design,Vehicle dynamics,Ranging,Principle of maximum entropy,Cluster analysis,Mobile telephony,Mathematics
Journal
Volume
Issue
ISSN
57
1
0018-9286
Citations 
PageRank 
References 
9
0.66
19
Authors
3
Name
Order
Citations
PageRank
Puneet Sharma127138.61
Salapaka, S.M.27710.36
Carolyn L. Beck340160.19